WO2011093447A1 - Calculation device, control method for calculation device, control program, and recording medium - Google Patents

Calculation device, control method for calculation device, control program, and recording medium Download PDF

Info

Publication number
WO2011093447A1
WO2011093447A1 PCT/JP2011/051748 JP2011051748W WO2011093447A1 WO 2011093447 A1 WO2011093447 A1 WO 2011093447A1 JP 2011051748 W JP2011051748 W JP 2011051748W WO 2011093447 A1 WO2011093447 A1 WO 2011093447A1
Authority
WO
WIPO (PCT)
Prior art keywords
unit
holding state
parameter
measurement data
state
Prior art date
Application number
PCT/JP2011/051748
Other languages
French (fr)
Japanese (ja)
Inventor
正克 興梠
武志 蔵田
隆一郎 富永
秀人 嶌岡
Original Assignee
独立行政法人産業技術総合研究所
三洋電機株式会社
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 独立行政法人産業技術総合研究所, 三洋電機株式会社 filed Critical 独立行政法人産業技術総合研究所
Priority to JP2011551932A priority Critical patent/JP5565736B2/en
Publication of WO2011093447A1 publication Critical patent/WO2011093447A1/en

Links

Images

Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01CMEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/10Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
    • G01C21/12Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
    • G01C21/16Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01CMEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/20Instruments for performing navigational calculations
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01CMEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C22/00Measuring distance traversed on the ground by vehicles, persons, animals or other moving solid bodies, e.g. using odometers, using pedometers
    • G01C22/006Pedometers

Definitions

  • the present invention relates to a calculation device that calculates a parameter indicating a motion state of a moving body based on an output from a sensor held by the moving body, and more specifically, to specify the position of the moving body,
  • the present invention relates to a calculation device that calculates the amount of movement of a moving object.
  • the conventional positioning device that identifies the position of a moving body
  • external infrastructure devices such as GPS (Global Positioning System) and cell-based positioning, and self-contained measuring devices (specifically In some cases, an autonomous navigation system that sequentially estimates the position and orientation of a moving object using an acceleration sensor or the like is used.
  • the present invention relates to the latter positioning device.
  • a measuring device In the case of an autonomous navigation system, a measuring device is often fixedly mounted on a moving object, and a single type / setting of a moving amount estimating means is used.
  • Patent Documents 1 to 3 Non-Patent Documents 1 to 4 and the like can be cited.
  • the movement amount is estimated by exactly the same calculation process regardless of the mounting / holding posture of the measuring device. Then, the calculation process used for estimating the movement amount is a calculation process assuming a specific state. For this reason, when the mounting / holding posture is unexpected, there is a problem that the calculation of the movement amount cannot be performed or the accuracy of the calculated movement amount is lowered.
  • the moving body is a person
  • various states such as a state in which the measuring device is held by hand and a state in which it is in a pocket are assumed. And in each state, the kind and magnitude
  • the above problem is not limited to a device that calculates the amount of movement, and is a problem that occurs in all devices that calculate parameters indicating the motion state of a moving body based on the detection result of a sensor.
  • the present invention has been made in view of the above-described problems, and an object of the present invention is to calculate a parameter indicating the motion state of the moving body by appropriate arithmetic processing according to the mounting / holding posture of the measuring apparatus with respect to the moving body. It is to provide a computing device or the like.
  • a calculation apparatus is a calculation apparatus that calculates a parameter indicating a moving state of a moving object using measurement data output from one or more sensors held by the moving object. Then, from the measurement data, holding state specifying means for specifying how the sensor is held by the moving body, and calculation processing according to the holding state specified by the holding state specifying means are performed, and the measurement is performed. And a parameter calculating means for calculating a parameter indicating the moving state of the moving body from the data.
  • the control method of the computing device of the present invention uses the measurement data output from one or more sensors held by the moving body to set a parameter indicating the moving state of the moving body.
  • a control method of a computing device to calculate, according to a holding state specifying step for specifying how the sensor is held on a moving body from the measurement data, and a holding state specified in the holding state specifying step And a parameter calculating step of calculating a parameter indicating a moving state of the moving body from the measurement data.
  • the reliability and accuracy of the parameter can be improved.
  • arithmetic processing is prepared in advance for each assumed holding state.
  • the calculation processes corresponding to different holding states may be different or different in the calculation process (for example, mathematical formulas and procedures used).
  • the parameter value corresponding to the holding state is calculated by weighting, switching of the scale factor, or the like.
  • the senor may be any sensor that outputs measurement data necessary for specifying the moving state of the moving body.
  • an acceleration sensor e.g., a Bosch Sensortec BMA150 accelerometer
  • a gyro sensor e.g., a Bosch Sensortec BMA150 accelerometer
  • a geomagnetic sensor e.g., a Bosch Sensortec BMA150 gyro sensor
  • the parameter to be calculated is not particularly limited as long as it indicates the moving state of the moving body.
  • the parameter include a moving direction, a moving speed, and a moving distance. Note that measurement data such as acceleration varies greatly depending on the holding state, and therefore the present invention is particularly suitable for calculating parameters using acceleration.
  • how the sensor is held is determined based on the measurement data as to which of the holding states assumed in advance corresponds to none. Can do. For example, a holding state and a pattern of measurement data output in the holding state may be stored in association with each other.
  • the calculation apparatus responds to the holding state specifying means for specifying how the sensor is held by the moving body and the holding state specified by the holding state specifying means from the measurement data. It is a structure provided with the parameter calculation means which performs a calculation process and calculates the parameter which shows the movement state of the said mobile body from the said measurement data.
  • control method of the computing device of the present invention is specified from the measurement data by the holding state specifying step for specifying how the sensor is held by the moving body and the holding state specifying step. And a parameter calculating step of performing a calculation process according to the holding state and calculating a parameter indicating the moving state of the moving body from the measurement data.
  • the reliability and accuracy of the parameter can be improved. There is an effect.
  • FIG. 1 illustrates an embodiment of the present invention, and is a block diagram illustrating a configuration of a main part of a positioning device. It is a figure which shows an example of the signal specific table used with the said positioning apparatus. It is a flowchart which shows an example of the process which the said positioning apparatus performs. It is a block diagram which shows the principal part structure of the positioning apparatus using an acceleration sensor as a measurement part. It is a block diagram which shows the principal part structure of a positioning apparatus provided with a posture angle estimation part. It is a block diagram which shows the principal part structure of a positioning apparatus provided with a gravity direction estimation part.
  • FIG. 1 is a block diagram showing a main configuration of a positioning device (calculation device) 1.
  • the positioning device 1 includes a measurement unit (sensor) 2, a control unit 3, and a storage unit 4.
  • the positioning device 1 is a device that is attached to or held by a moving body (a person or an object) and outputs a parameter indicating the motion state of the moving body. Specifically, the positioning device 1 calculates a movement vector of the moving body using the measurement data measured by the measuring unit 2 which is a sensor that detects the movement and state change of the moving body. Calculate and output the current position of the moving object.
  • the measurement unit 2 is a sensor that detects the movement state of the moving body, the position where the moving body exists, and the like and outputs the detected value as measurement data as described above. Moreover, the measurement part 2 outputs elapsed time (DELTA) T after outputting measurement data last with measurement data. Thereby, the time-dependent change of measurement data is grasped.
  • DELTA elapsed time
  • the measuring unit 2 may be configured by a sensor corresponding to the type of parameter output by the positioning device 1, the accuracy of the required parameter, and the like.
  • the measurement unit 2 can be configured by any one or a combination of an acceleration sensor, a gyro sensor, a magnetic sensor, and an atmospheric pressure sensor.
  • the control unit 3 controls the positioning device 1 in an integrated manner, and performs control to calculate and output the current position of the moving body using the measurement data output from the measurement unit 2.
  • This control is realized by a holding state estimation unit (holding state identification unit) 10, an adjustment unit 11, a movement amount estimation unit (parameter calculation unit) 12, and a position determination unit 13 provided in the control unit 3.
  • the holding state estimation unit 10 estimates the mounting / holding posture of the positioning device 1 (more precisely, the measurement unit 2) with respect to the moving body (how it is held by the moving body) from the measurement data output by the measuring unit 2. And output state data indicating the estimated posture.
  • the mounting / holding posture is specified using data that associates a presumed mounting / holding posture with a pattern of measurement data detected by the mounting / holding posture, and the mounting / holding posture is determined. It is assumed that the status data corresponding to is output.
  • the mounting / holding posture is specified by using a machine learning framework by AdaBoost, for example, based on measurement data (acceleration, angular velocity, magnetism, atmospheric pressure, etc.) from the measurement unit 2. It can also be realized by configuring a discriminator for identifying the holding posture.
  • AdaBoost machine learning framework
  • identification of the mounting / holding posture using Adaboost is a known technique as described in Non-Patent Document 1, description thereof is omitted here.
  • the measuring unit 2 is configured so as to be able to detect parameters necessary for identifying a mounting / holding posture assumed in advance. Then, it identifies which mounting / holding posture corresponds to the measurement data pattern of the measuring unit 2 and outputs state data indicating the identified mounting / holding posture.
  • the adjustment unit 11 controls the movement amount estimation unit 12 so that a parameter indicating the movement state of the moving body is calculated by a calculation process according to the wearing / holding posture estimated by the holding state estimation unit 10. Specifically, the adjustment unit 11 specifies a control signal corresponding to the state data output from the holding state estimation unit 10 with reference to the signal specification table 20 stored in the storage unit 4, and uses this control signal. The above control is performed by outputting to the movement amount estimation unit 12.
  • the signal specification table 20 will be described later.
  • the movement amount estimation unit 12 calculates a parameter indicating the movement state of the moving body by a calculation process according to the wearing / holding posture estimated by the holding state estimation unit 10. Specifically, the movement amount estimation unit 12 receives the measurement data output from the measurement unit 2 and the control signal output from the adjustment unit 11, and moves the moving object from the measurement data by the arithmetic processing indicated by the control signal. The movement vector indicating the movement direction and the movement distance is calculated and output.
  • the position determination unit 13 determines the current position of the moving object from the movement vector output by the movement amount estimation unit 12.
  • the determined current position is output, for example, by displaying an image indicating the current position of the positioning device 1.
  • the storage unit 4 is a device that stores various data used in the positioning device 1. As shown in the figure, the signal specifying table 20 is stored in the storage unit 4.
  • the signal specification table 20 is a table for the adjustment unit 11 to specify a control signal corresponding to the state data output from the holding state estimation unit 10.
  • the signal specifying table 20 may be as shown in FIG.
  • FIG. 2 is a diagram illustrating an example of the signal identification table 20.
  • the signal specification table 20 is data in which the holding state and the control signal are associated with each other. Specifically, in the signal identification table 20 of FIG. 2, the control signals (1), (2), (3),... Are associated with the holding states 1, 2, 3,.
  • the holding state estimation unit 10 determines that the holding state of the positioning device 1 is any one of 1, 2, 3,. It is assumed that the state corresponds to the state, and the state data indicating the specified holding state is output to the adjustment unit 11. Note that it may be determined from the measurement data output by the measurement unit 2 that it does not correspond to any of the holding states shown in FIG. In this case, status data indicating the closest holding state may be output, or status data indicating that it is not applicable may be output.
  • the adjustment unit 11 refers to the signal identification table 20, and the control signal associated with the output state data corresponds to any of the control signals (1), (2), (3),. You will specify what to do.
  • one control signal is associated with one holding state, but a plurality of control signals may be associated. Thereby, it is possible to finely control the arithmetic processing performed by the movement amount estimation unit 12.
  • a control signal corresponding to a state that does not correspond to any holding state are preferably associated with each other. Therefore, even if it does not correspond to any holding state, it becomes possible to calculate the movement vector by an appropriate calculation process.
  • the adjustment unit 11 outputs the control signal identified with reference to the signal identification table 20 of FIG. 2 to the movement amount estimation unit 12, and the movement amount estimation unit 12 performs arithmetic processing according to the output control signal.
  • the movement vector is calculated by going.
  • the arithmetic processing corresponding to each holding state may be specified based on the result of actually measuring what measurement data is detected in the holding state, for example. Further, for example, it is possible to specify an appropriate arithmetic processing according to the holding state by using a machine learning framework by AdaBoost.
  • the signal identification table 20 is a table in which a presumed holding state is associated with a control signal for causing the movement amount estimating unit 12 to execute a calculation process according to the holding state.
  • FIG. 3 is a flowchart illustrating an example of processing executed by the positioning device 1.
  • the holding state estimation unit 10 confirms whether or not measurement data is input from the measurement unit 2 (S1), and when the measurement data is input (YES in S1), the holding state of the positioning device 1 is determined from the measurement data. (Mounting / holding posture) is estimated (S2). Then, state data indicating the estimated holding state is output to the adjustment unit 11.
  • the adjustment unit 11 that has received the state data refers to the signal identification table 20 to identify a control signal corresponding to the received state data, and generates the identified control signal (S3).
  • the adjustment unit 11 outputs the generated control signal to the movement amount estimation unit 12.
  • the movement amount estimation unit 12 that has received the control signal performs a calculation process according to the received control signal and calculates a movement vector (S4). Thereafter, the movement amount estimation unit 12 transmits the calculated movement vector to the position determination unit 13, and calculates and outputs the current position of the positioning device 1 based on the movement vector received by the position determination unit 13 that has received the movement vector. Then, the process ends.
  • FIG. 4 is a block diagram showing a main configuration of the positioning device 1 using an acceleration sensor as the measuring unit 2.
  • the illustrated positioning apparatus 1 includes an acceleration sensor 2a as a measuring unit.
  • the acceleration sensor 2a is a triaxial acceleration sensor that detects acceleration vectors in three axial directions perpendicular to each other and outputs the acceleration vectors as acceleration data.
  • Non-Patent Document 2 and Patent Document 2 describe whether a person is walking, running, or going up and down stairs from 3-axis acceleration data output by a 3-axis acceleration sensor held by a person. Is described.
  • feature vectors are extracted from triaxial acceleration data using wavelet packet transformation, and each state (walking, running, etc.) is clustered using a self-organization method described in Non-Patent Document 3 or the like. Yes.
  • the holding state can be estimated from the triaxial acceleration data. That is, the holding state estimation unit 10 in FIG. 4 determines which of holding states clustered in advance by a self-organization method from feature vectors extracted from time-series triaxial acceleration data using wavelet packet transformation. Identify.
  • the movement amount estimation unit 12 in FIG. 4 calculates a movement vector by performing arithmetic processing according to the control signal received from the adjustment unit 11 using the triaxial acceleration data.
  • the calculation process which calculates a movement vector from triaxial acceleration data is well-known, description is abbreviate
  • Example with posture angle estimation unit By calculating the attitude angle of the moving body with respect to the world coordinate system, it is possible to determine the gravity direction of the moving body (usually different from the gravity direction of the world coordinate system). can do.
  • FIG. 5 is a block diagram illustrating a main configuration of a positioning device (calculation device) 30 including a posture angle estimation unit.
  • the same reference number is attached
  • the positioning device 30 includes an acceleration sensor 2a and a gyro sensor 2b as measurement units.
  • the gyro sensor 2b detects an angular velocity vector and outputs angular velocity data.
  • the gyro sensor 2b outputs angular velocity data in the triaxial direction, but it may be biaxial or less.
  • the posture angle estimation unit (posture angle calculation means) 14 calculates the posture angle of the moving body holding the positioning device 30 using the acceleration data output from the acceleration sensor 2a and the angular velocity data output from the gyro sensor 2b. To do.
  • the posture angle estimation unit 14 outputs the calculated posture angle to the holding state estimation unit 10 and the movement amount estimation unit 12.
  • the posture angle estimation unit 14 By acquiring the posture angle as time-series data, it is possible to measure the change of the posture angle in addition to acceleration, deceleration, movement of the center of gravity, etc., regarding the movement created by the moving body. As a result, the state of the moving body can be estimated more accurately and finely. That is, by providing the posture angle estimation unit 14, it is possible to increase the estimation accuracy of the holding state, increase the variation of the holding state that can be detected, and the like.
  • the movement amount estimation unit 12 specifies the movement direction of the moving body using the posture angle output from the posture angle estimation unit 14, and calculates a movement vector based on this.
  • requiring a moving direction from an attitude angle is well-known, description is abbreviate
  • the motion state of the moving body can be specified with higher accuracy also by calculating the gravity direction of the moving body. Note that, as described above, the gravity direction of the moving body is usually different from the gravity direction of the world coordinate system.
  • FIG. 6 is a block diagram illustrating a main configuration of a positioning device (calculation device) 40 including a gravity direction estimation unit.
  • the same reference number is attached
  • the gravity direction estimation unit (gravity direction identification means) 15 calculates the gravity direction vector of the positioning device 40 (more precisely, the measurement unit 2) using the measurement data output from the measurement unit 2. Further, the gravity direction estimation unit 15 outputs the calculated gravity direction vector to the holding state estimation unit 10 and the movement amount estimation unit 12.
  • the gravity direction vector can be specified by tracking the gravity acceleration vector using the acceleration vector and the angular velocity vector. For this reason, the positioning device 40 needs to include at least an acceleration sensor and a gyro sensor as the measurement unit 2.
  • Non-Patent Document 2 describes that a gravitational acceleration vector is tracked using an input of an acceleration vector and an angular velocity vector using a Kalman filter framework.
  • the gravity direction estimation unit 15 can also be realized by such a technique.
  • the holding state estimation unit 10 can estimate the holding state with high accuracy by using the gravity direction vector output by the gravity direction estimation unit 15, and increase the number of detectable holding states. It becomes possible.
  • the movement amount estimation unit 12 can decompose the measurement data (acceleration data, angular velocity data, etc.) into the gravity direction component and the other by using the gravity direction vector output from the gravity direction estimation unit 15. The estimation accuracy of the movement vector can be improved.
  • FIG. 7 is a block diagram showing a main configuration of a positioning device that calculates a pedestrian movement vector.
  • the same reference number is attached
  • the positioning device 50 includes a walking motion detection unit (parameter calculation unit) 12a, a stride estimation unit (parameter calculation unit) 12b, a movement direction detection unit 12c, and a movement vector as a movement amount estimation unit.
  • a calculation unit 12d is provided.
  • the adjustment part 11 transmits a control signal to the walking motion detection part 12a and the stride estimation part 12b, and performs the arithmetic processing which exhibits the highest performance according to the holding
  • the measurement unit 2 includes a three-axis acceleration sensor, a three-axis angular velocity sensor, and a three-axis geomagnetic sensor.
  • the movement vector of the pedestrian is calculated and the current position of the pedestrian is output.
  • the walking motion detection unit 12a identifies whether or not a walking motion is being performed from the measurement data output by the measurement unit 2 by a calculation process according to the control signal received from the adjustment unit 11. That is, the walking motion detection unit 12a can detect the walking motion by a plurality of arithmetic processes, and detects the walking motion by the arithmetic process specified by the control signal among these arithmetic processes.
  • the walking motion detection unit 12a compares the pattern of change with time of the acceleration data output from the measurement unit 2 with the pattern of change with time of the acceleration data generated when the walking motion is performed. Identifies that a walking action is taking place.
  • the pattern of change with time of the acceleration data is a pattern in which the acceleration changes with a constant period and amplitude, and a technique for calculating the walking speed from this amplitude is known (for example, Patent Document 3).
  • the walking motion detection unit 12a specifies the amplitude of the pattern and notifies the stride estimation unit 12b of the specified amplitude. Note that the walking motion detection method, the movement direction detection method, and the movement distance calculation method are not limited to the above examples.
  • the stride length estimation unit 12b calculates a walking speed from the amplitude output by the walking motion detection unit 12a by a calculation process according to the control signal received from the adjustment unit 11. And the stride (distance walked at the elapsed time) is calculated by multiplying the calculated walking speed by the elapsed time.
  • the measurement data output from the measurement unit 2 such as acceleration data and angular velocity data has its signal intensity increased or decreased depending on the holding state.
  • the signal intensity can also be expressed as an amplitude in a waveform (sine curve or the like) drawn by plotting measurement data in time series, for example.
  • Patent Document 1 describes that whether or not a walking motion is performed is determined based on whether or not such signal intensity exceeds a predetermined threshold.
  • the control signal transmitted to the walking motion detector 12a may detect the walking motion with a threshold corresponding to the holding state.
  • a holding signal with a low signal strength is associated with a control signal that detects a walking motion with a small threshold
  • a holding signal with a high signal strength is associated with a control signal that detects a walking motion with a large threshold.
  • a control signal transmitted to the walking motion detection unit 12a for example, a walking motion may be detected with a sensitivity (scale factor) corresponding to the holding state. Also with this configuration, it is possible to cancel the influence of the holding state on the signal intensity and reliably detect the walking motion.
  • the moving direction detection unit 12c detects the direction in which the pedestrian is moving using the measurement data. Note that a known method can be applied to the detection of the moving direction, and for example, it can be detected from acceleration data and angular velocity data.
  • the movement vector calculation unit 12d calculates a movement vector by multiplying the stride (walking distance) output from the step estimation unit 12b by the direction output from the movement direction detection unit 12c, and outputs the calculated movement vector to the position determination unit 13. .
  • the position determination part 13 can pinpoint the present position of the pedestrian who has the positioning apparatus 50.
  • the positioning device of this embodiment has two movement amount estimation units with different estimation accuracy of the movement amount, and the main point is that these movement amount estimation units are selectively used according to the posture estimated by the holding posture estimation unit 10. It is a special feature point.
  • the same reference number is attached
  • FIG. 8 is a block diagram showing a main configuration of the positioning device (calculation device) 60.
  • the positioning device 60 includes a control unit 3 and a storage unit 4.
  • the acceleration sensor 2a, the gyro sensor 2b, and the geomagnetic sensor 2c are provided as a measurement part. That is, the positioning device 60 estimates the movement vector using the acceleration, angular velocity, and geomagnetism as input data.
  • the positioning device 60 includes a display unit 5.
  • the display unit 5 is a device that displays an image according to the control of the control unit 3.
  • the positioning device 60 has a function of displaying the current position of the user who owns the positioning device 60 on a map using the estimated movement vector. Therefore, the display unit 5 displays a map image, information indicating the current position of the user, and the like.
  • the control unit 3 includes a holding state estimation unit 10, an adjustment unit 11, a position determination unit (parameter calculation means) 13, and a display control unit 18.
  • a high-precision movement amount estimation unit 16 and a simple movement amount estimation unit (simple parameter calculation means) 17 are provided as the movement amount estimation unit.
  • the holding state estimation unit 10 estimates the holding state of the positioning device 60 using the measurement data output from the measurement unit, generates state data indicating the estimated holding state, and outputs the state data to the adjustment unit 11.
  • the holding state estimation unit 10 outputs state data indicating that the positioning device 60 is in an unexpected state when the input measurement data does not correspond to any of the holding states assumed in advance.
  • the holding state is not limited to the above example, and can be easily applied as long as it can be identified using a machine learning framework such as AdaBoost. Further, it is not always necessary to use a machine learning framework, and any holding state that can be identified based on measurement data may be used. However, when adding / changing the holding state, the adjusting unit 11, the high-precision moving amount estimating unit 16, and the simple moving amount estimating unit are configured so that an optimal movement vector according to the holding state is estimated. There is a need to.
  • the adjustment unit 11 controls the movement amount estimation unit 12 so that a parameter indicating the motion state of the moving body is calculated by a calculation process according to the state data output from the holding state estimation unit 10. Specifically, the adjustment unit 11 specifies a control signal corresponding to the state data using the signal specification table 20 of the storage unit 4, and uses the specified control signal for the high-precision movement amount estimation unit 16 and the simple movement amount estimation unit. The above control is performed by outputting to 17.
  • the high-accuracy movement amount estimation unit 16 has a configuration corresponding to the movement amount estimation unit 12 in FIG. 1 and estimates a movement vector from measurement data based on a control signal output from the adjustment unit 11. More specifically, the high-precision movement amount estimation unit 16 estimates a pedestrian movement vector.
  • FIG. 9 is a block diagram showing a main configuration of the high-precision movement amount estimation unit 16.
  • the high-precision movement amount estimation unit 16 includes a walking motion detection unit (parameter calculation unit) 16a, a stride estimation unit (parameter calculation unit) 16b, a movement direction detection unit (parameter calculation unit) 16c, and a movement vector calculation.
  • Unit (parameter calculation means) 16d These have the same functions as the walking motion detection unit 12a, the stride estimation unit 12b, the movement direction detection unit 12c, and the movement vector calculation unit 12d in FIG.
  • the walking motion detection unit 16a uses the triaxial acceleration data output from the acceleration sensor 2a and the triaxial angular velocity data output from the gyro sensor 2b in accordance with the control signal received from the adjustment unit 11. Perform arithmetic processing. Thereby, the walking motion detection unit 16a detects the walking motion, calculates the amplitude, and outputs the amplitude to the stride estimation unit 16b.
  • the stride length estimation unit 16b calculates the walking speed from the amplitude output by the walking motion detection unit 16a by a calculation process according to the control signal received from the adjustment unit 11. Then, the stride (movement distance) is calculated from the calculated walking speed, and is output to the movement vector calculation unit 16d.
  • the moving direction detection unit 16c performs arithmetic processing according to the control signal received from the adjustment unit 11, using the triaxial angular velocity data output from the gyro sensor 2b and the triaxial geomagnetic data output from the geomagnetic sensor 2c.
  • the moving direction of the positioning device 60 is specified.
  • the detection of the moving direction may also be performed by a calculation process according to the control signal received from the adjustment unit 11. For example, the contribution of the measurement data output by the measurement unit in the holding state where the reliability of the output measurement data is considered to be low is reduced or excluded from the measurement data output by the measurement unit in the other holding state
  • the azimuth may be specified by the arithmetic processing.
  • the movement vector calculation unit 16d calculates a movement vector (referred to as a movement vector (high accuracy)) by multiplying the stride (walking distance) output from the stride estimation unit 16b by the direction output from the movement direction detection unit 16c.
  • the movement vector (high accuracy) is output to the position determination unit 13.
  • the simple movement amount estimation unit 17 performs a calculation process according to the control signal transmitted by the adjustment unit 11, thereby moving the movement vector (movement vector) from the measurement data output by the measurement unit. (Referred to as “simple”) is calculated, and the calculated movement vector (simple) is output to the position determining unit 13.
  • the simple movement amount estimation unit 17 is different from the high accuracy movement amount estimation unit 16 in that the amount of data used for the arithmetic processing is smaller than that of the high accuracy movement amount estimation unit 16. Specifically, the simple movement amount estimation unit 17 performs calculation processing using all of the three-axis acceleration data, the three-axis angular velocity data, and the three-axis geomagnetic data, while the high-precision movement amount estimation unit 16 performs the calculation process. Axial acceleration data and triaxial geomagnetic data are used, and triaxial angular velocity data is not used.
  • FIG. 10 is a block diagram illustrating a main configuration of the simple movement amount estimation unit 17.
  • the simple movement amount estimation unit 17 includes a walking motion detection unit (simple parameter calculation unit) 17a, a stride estimation unit (simple parameter calculation unit) 17b, a movement direction detection unit (simple parameter calculation unit) 17c, and a movement.
  • a vector calculation unit (simple parameter calculation means) 17d is provided. These have the same functions as the walking motion detection unit 16a, the stride length estimation unit 16b, the movement direction detection unit 16c, and the movement vector calculation unit 16d of the high-precision movement amount estimation unit 16.
  • the walking motion detection unit 17a performs arithmetic processing according to the control signal received from the adjustment unit 11 using the triaxial acceleration data output from the acceleration sensor 2a. Thereby, the walking motion detection unit 17a detects the walking motion, calculates the amplitude, and outputs the amplitude to the stride estimation unit 17b. That is, the walking motion detection unit 17a is different from the walking motion detection unit 16a in that the triaxial angular velocity data is not used for the calculation process.
  • the stride length estimation unit 17b calculates a walking speed from the amplitude output by the walking motion detection unit 17a by a calculation process according to the control signal received from the adjustment unit 11. Then, the stride (movement distance) is calculated from the calculated walking speed, and is output to the movement vector calculation unit 17d.
  • the moving azimuth detecting unit 17c performs arithmetic processing according to the control signal received from the adjusting unit 11, and specifies the moving azimuth of the positioning device 60 from the three-axis geomagnetic data output from the geomagnetic sensor 2c. That is, the moving direction detection unit 17c is different from the moving direction detection unit 16c in that the direction is specified without using the triaxial angular velocity data.
  • the movement vector calculation unit 17d calculates a movement vector (simple) by multiplying the stride (walking distance) output by the stride estimation unit 17b by the azimuth output by the movement azimuth detection unit 17c, and sets the calculated movement vector (simple) as the position.
  • the data is output to the determination unit 13.
  • the simple movement amount estimation unit 17 is not limited to the above example as long as the amount of data used for the arithmetic processing is smaller than that of the high-precision movement amount estimation unit 16.
  • the high-accuracy movement amount estimation unit 16 uses triaxial data, only the biaxial or uniaxial data may be used.
  • the amount of data used may be reduced while using the same kind of data, for example, by making the period for acquiring data from the measurement unit longer than that of the high-precision movement amount estimation unit 16.
  • both the movement vector (high accuracy) output from the high-accuracy movement amount estimation unit 16 and the movement vector (simple) output from the simple movement amount estimation unit 17 are input to the position determination unit 13. Then, the position determination unit 13 determines whether to use the movement vector (high accuracy), the movement vector (simple), or both based on the control signal transmitted by the adjustment unit (switching unit) 11. Based on this determination, position data is calculated.
  • the movement vector is calculated by a simple average or a weighted average of the movement vector (high accuracy) and the movement vector (simple). Even if the calculation process by the high-accuracy movement amount estimation unit 16 is performed, in the holding posture where it is assumed that a calculation result with high reliability cannot be obtained, the movement vector (simple) is replaced with the movement vector (simple). By taking into account partial elements of (high accuracy), the estimation accuracy of the movement vector can be increased.
  • the adjustment unit 11 moves the movement vector (high accuracy) or the movement vector (high accuracy) and the movement vector ( A simple control signal is output.
  • a control signal for outputting a movement vector (simple) is transmitted.
  • the position determination unit 13 calculates the current position using a movement vector corresponding to the control signal from the adjustment unit 11.
  • the display control unit 18 performs control to display an image on the display unit 5. Specifically, the display control unit 18 displays a map image on the display unit 5 based on the map data 21 stored in the storage unit 4. Further, the display control unit 18 displays a mark indicating that the user exists at the position indicated by the position data received from the position determination unit 13 on the displayed map.
  • Example of detecting transition status For example, when the operation of changing the positioning device is performed, the acceleration or the like generated by this operation is detected by the measurement unit 2. Thus, there is a possibility that the moving direction and moving distance of the user may not be accurately calculated from the measurement data detected when the user holding the positioning device changes the positioning device.
  • FIG. 11 is a block diagram illustrating a main configuration of a positioning device (calculation device) 70 that estimates a transition state.
  • a positioning device calculation device
  • the positioning device 70 is configured such that the drive control signal is input from the holding state estimation unit 10 to the measurement unit, and the measurement data input from the measurement unit to the simple movement amount estimation unit 17 is a biaxial angular velocity. It differs from the positioning device 60 in that it is data, triaxial acceleration data, and triaxial geomagnetic data.
  • FIG. 12 is a block diagram illustrating a main configuration of the holding state estimation unit 10.
  • the holding state estimation unit 10 includes a holding state identification unit 10a, a transition state detection unit 10b, and a holding state determination unit 10c.
  • the holding state identifying unit 10a identifies the holding state of the positioning device 70 from the measurement data output by the measuring unit, and outputs state identification data indicating the identified holding state to the holding state determining unit 10c.
  • the holding state identification unit 10a corresponds to any one of the holding states assumed in advance using the triaxial acceleration data, the triaxial angular velocity data, and the triaxial geomagnetic data. State identification data indicating the identification result is output.
  • the transition state detection unit 10b performs a transition state detection process to detect that the positioning device 70 is in the transition state from the measurement data output by the measurement unit. And when it detects that it exists in a transition state, that is output to the holding
  • the holding state determination unit (measurement control means) 10c determines the holding state of the positioning device 70 based on the outputs of the holding state identification unit 10a and the transition state detection unit 10b. Then, state data indicating the determined holding state is generated and output to the adjustment unit 11.
  • the holding state determination unit 10c when the transition state detection unit 10b outputs that the transition state detection unit 10b is in the transition state, the holding state determination unit 10c outputs a drive control signal to the measurement unit 2 and stops some data measurement by the measurement unit 2.
  • the output destination of the measurement data is switched from the high-precision movement amount estimation unit 16 to the simple movement amount estimation unit 17.
  • the drive control by the holding state determination unit 10c is not limited to the above example, and is used by the simple movement amount estimation unit 17 by, for example, lowering the drive frequency of the measurement unit 2, in other words, lowering the output frequency of measurement data.
  • the amount of data to be performed may be smaller than that of the high-precision movement amount estimation unit 16.
  • the positioning device 70 does not perform the movement vector calculation by the high-precision movement amount estimation unit 16 in the transition state, and only performs the movement vector calculation by the simple movement amount estimation unit 17 while reducing the data amount output by the measurement unit 2. . Thereby, the power consumption in the measurement part 2 can be reduced.
  • the high-accuracy movement amount estimation unit 16 receives triaxial acceleration data, triaxial angular velocity data, and triaxial geomagnetic data, whereas the simple movement amount estimation unit. 17, it is assumed that triaxial acceleration data, biaxial angular velocity data, and triaxial geomagnetic data are input.
  • the holding state determination unit 10c outputs a drive control signal to the measurement unit 2 to change the angular velocity measured by the gyro sensor 2b from three axes to two axes. Switch to. Then, the block for calculating the movement vector is switched from the high-precision movement amount estimation unit 16 to the simple movement amount estimation unit 17.
  • the holding state determination unit 10c performs the same processing as that in the transition state even when the state identification data indicating that it does not correspond to any of the holding postures assumed in advance is received from the holding state identification unit 10a. . This is because when the holding posture assumed in advance does not correspond, even if the high-accuracy movement amount estimation unit 16 is used, improvement in calculation accuracy cannot be expected.
  • FIG. 13 is a block diagram illustrating a main configuration of the simple movement amount estimation unit 17.
  • the walking motion detector 17a calculates the amplitude from the triaxial acceleration data and the biaxial angular velocity data
  • the stride estimation unit 17b calculates the stride from this amplitude.
  • the moving direction detection unit 17c specifies the direction from the triaxial geomagnetic data and the biaxial angular velocity data
  • the movement vector calculation unit 17d calculates a movement vector (simple) from the stride and the direction.
  • the simple movement amount estimation unit 17 uses less angular velocity data (from three axes to two axes) than the high-precision movement amount estimation unit 16 shown in FIG.
  • the walking motion detection unit 17a, the stride length estimation unit 17b, the movement direction detection unit 17c, and the movement vector calculation unit 17d are output by the adjustment unit 11 according to a calculation process corresponding to the control signal corresponding to the transition state, The stride, azimuth, and movement vector (simple) are calculated.
  • the orientation and position are changed. Control is performed so as not to change, or to make the change smaller than periods other than those described above. Accordingly, it is possible to prevent the current position from being estimated to be a position greatly deviated from the actual position by the measurement data output in the transition state or the period of the unexpected holding posture.
  • the walking motion detection unit 17a detects a walking motion using time-series acceleration data. For this reason, the adjustment unit 11 transmits a control signal to the walking motion detection unit 17a, and contributes the acceleration data output by the measurement unit during a period that does not correspond to either the transition state or the holding posture assumed in advance.
  • the walking motion is detected by a calculation process that is smaller than the acceleration data output by the measurement unit during other periods.
  • the contribution of the acceleration data output by the measurement unit during a period that does not correspond to any of the transition state or the presumed holding posture may be completely removed.
  • the adjustment unit 11 also contributes the acceleration data output by the measurement unit during a period other than the transition state or the presumed holding posture to the stride length estimation unit 17b.
  • the step length may be detected by a calculation process that is smaller than the acceleration data output by the measuring unit or is excluded.
  • the adjustment unit 11 similarly applies the measurement data (angular velocity data and geomagnetic data) output by the measurement unit during the period in which the moving direction detection unit 17c does not correspond to either the transition state or the presumed holding posture. May be made smaller than the acceleration data output by the measurement unit during other periods, or the orientation may be specified by a calculation process that is excluded.
  • the azimuth error is particularly affected by the positioning error, only the moving azimuth may be controlled by the adjustment unit 11. That is, if the moving direction is estimated incorrectly, a position that is far from the actual position is estimated. Therefore, it is preferable to perform control so that at least the moving direction is not changed in the transition state or the like.
  • the moving direction detection unit 17c may store a change history of the direction, and specify the most likely direction from the change history as the current direction.
  • the position determination unit 13 may store a position change history, and specify the most likely position as the current position from the change history.
  • FIG. 14 is a flowchart illustrating an example of the transition state detection process.
  • a transition state is specified by detecting a pattern in which the acceleration changes abruptly based on the triaxial acceleration data using the fact that the acceleration changes abruptly at the time of transition.
  • the data used for specifying the transition state may not be the measurement data itself output by the measurement unit 2. For example, it is naturally possible to use data obtained by filtering measurement data with a low-pass filter or the like.
  • the transition state detection unit 10b acquires triaxial acceleration data from the acceleration sensor 2a (S10). And the transition state detection part 10b calculates the difference with the acceleration of 1 step before about each axis
  • the transition state detection unit 10b calculates a difference average value (dif_a_ave) for a certain period for each axis using the difference calculated in S11 (S12). Further, the transition state detection unit 10b sets a threshold value (DFTH) for determining whether or not the transition state is set (S13).
  • DFTH threshold value
  • the threshold value (DFTH) a predetermined value may be used. However, since the magnitude of the acceleration detected in the transition state is proportional to the magnitude of the walking speed at that time, it is possible to set a threshold (DFTH) according to the walking speed or acceleration from a predetermined time before to the present. preferable. That is, the transition state detection unit 10b sets a threshold value (DFTH) proportional to the walking speed or acceleration.
  • the value of the measurement data output from the measurement unit 2 increases as the walking speed increases. For this reason, it may replace with said structure and may employ
  • the threshold value to be set may be changed continuously according to the value of the measurement data (for example, the average value of the values in the three axis directions) or may be changed stepwise.
  • the transition state detection unit 10b checks whether or not the difference average value (dif_a_ave) calculated in S12 is smaller than the threshold value (DFTH) set in S13 (S14). When the transition state detection unit 10b determines that the difference average value (dif_a_ave) is smaller than the threshold value (DFTH) (YES in S14), the transition state detection unit 10b determines that it is not the transition state (S15), and holds that state. It outputs to the determination part 10c and returns to the process of S10.
  • transition state detection unit 10b determines that the difference average value (dif_a_ave) is equal to or greater than the threshold value (DFTH) (NO in S14), the transition state detection unit 10b determines that the transition state is present (S15) and retains that effect. It outputs to the state determination part 10c, and returns to the process of S10.
  • FIG. 15 is a block diagram illustrating a main configuration of a positioning device 80 including two gravity direction estimation units.
  • the same reference number is attached
  • the positioning device 80 includes a high-precision gravity direction estimation unit 15a and a simple gravity direction estimation unit (simple gravity direction specifying means) 15b as gravity direction estimation units.
  • the high precision gravity direction estimation unit 15a has the same function as the gravity direction estimation unit 15 provided in the positioning device 40 of FIG. That is, the high-precision gravity azimuth estimation unit 15a calculates the gravity azimuth vector using the triaxial acceleration data output from the acceleration sensor 2a and the triaxial angular velocity data output from the gyro sensor 2b.
  • the gravity direction vector calculated by the high-precision gravity direction estimation unit 15a is referred to as a gravity direction vector (high accuracy).
  • the high-precision gravity azimuth estimation unit 15 a outputs the calculated gravity azimuth vector (high accuracy) to the holding state estimation unit 10 and the high-precision movement amount estimation unit 16.
  • the gravity direction vector (high accuracy) may also be output to the simple movement amount estimation unit 17.
  • the simple gravity azimuth estimation unit 15b calculates the gravity azimuth vector using the acceleration data and the angular velocity data in the same manner as the high precision gravity azimuth estimation unit 15a, but the amount of data used is larger than that of the high precision gravity azimuth estimation unit 15a. There are few differences.
  • the simple gravity direction estimation unit 15b calculates the gravity direction vector using the biaxial angular velocity data and the triaxial acceleration data.
  • the gravity direction vector calculated by the simple gravity direction estimation unit 15b is referred to as a gravity direction vector (simple).
  • the simple gravity direction estimation unit 15 b outputs the calculated gravity direction vector (simple) to the holding state estimation unit 10 and the simple movement amount estimation unit 17. Note that the gravity direction vector (simple) may also be output to the high-precision movement amount estimation unit 16.
  • the holding state estimation unit 10 of the positioning device 80 estimates the holding state using the gravity direction vector (high accuracy) or the gravity direction vector (simple) output as described above.
  • measurement data having a value that is not assumed by the high-precision gravity azimuth estimation unit 15a is input, and therefore, less than the gravity azimuth vector (high accuracy) output by the high-precision gravity azimuth estimation unit 15a.
  • the gravity direction vector (simple) output from the simple gravity direction estimation unit 15b that performs arithmetic processing with the amount of data may be a more appropriate value. For this reason, the estimation accuracy of the gravity direction vector can be improved by performing the calculation process by the simple gravity direction estimation unit 15b in a transition state or an unexpected holding state.
  • FIG. 16 is a block diagram illustrating a main configuration of the holding state estimation unit 10.
  • the gravity direction is input to the holding state identifying unit 10a and the transition state detecting unit 10b.
  • This gravity direction is a gravity direction vector (high accuracy) and a gravity direction vector (simple).
  • the traveling direction component of the positioning device 80 and the direction perpendicular to the three-axis acceleration data, three-axis angular velocity data, and three-axis geomagnetic data are obtained. It can be decomposed into components, whereby the holding state can be identified with high accuracy.
  • the detection of the transition state since the acceleration changes abruptly at the time of transition, it is possible to detect a transitional state by detecting a rapidly changing pattern based on the vertical / traveling direction acceleration. Further, for example, the transition state may be detected when the traveling direction has changed abruptly. In addition, although advancing direction changes also when a mobile body (pedestrian) changes direction, since the degree of the change is larger in the transition state, it is possible to distinguish the direction change and the transition state.
  • the high-precision movement amount estimation unit 16 and the simple movement amount estimation unit 17 of the positioning device 80 also use the gravity direction vector (high accuracy) or the gravity direction vector (simple) output as described above. Estimate.
  • FIG. 17 is a block diagram showing a main configuration of the high-precision movement amount estimation unit 16 to which a gravity direction vector is input.
  • the gravity direction is input to the walking motion detector 16a.
  • the gravity direction is input to the moving direction detector 16c.
  • These gravity directions are gravity direction vectors (high accuracy).
  • the high-precision movement amount estimation unit 16 of the positioning device 80 detects the walking motion, specifies the movement direction, and the like using the gravity direction vector (high accuracy), and thus estimates the movement vector with high accuracy. be able to.
  • FIG. 18 is a block diagram illustrating a main configuration of the simple movement amount estimation unit 17 to which a gravity direction vector is input.
  • the simple movement amount estimation unit 17 of the positioning device 80 includes a walking motion detection unit 17a, a stride estimation unit 17b, a movement direction detection unit 17c, and a movement vector calculation unit 17d, as in FIG. .
  • the gravity direction vector (simple) is input to the walking motion detection unit 17a, and the gravity direction vector (simple) is input to the movement direction detection unit 17c in addition to the triaxial geomagnetic data.
  • the simple movement amount estimation unit 17 of the positioning device 80 uses the gravity direction vector (simple) to detect walking motion, specify the movement direction, and the like.
  • the high-precision movement amount estimation unit 16 and the simple movement amount estimation unit 17 determine which one of the gravity direction vector (high accuracy) and the gravity direction vector (simple) to use according to the state data, and determine the determined gravity A movement vector may be calculated from the orientation vector.
  • the adjustment unit 11 may control whether to use a gravity direction vector (high accuracy) or a gravity direction vector (simple).
  • both the gravity direction vector (high accuracy) and the gravity direction vector (simple) are always output.
  • the gravity direction vector (high accuracy) or the gravity direction vector (simple ) May be output.
  • the measurement device including the measurement unit 2 has been described.
  • the measurement unit 2 may be configured separately from the measurement device. That is, the measuring device of the present invention is not limited to the one incorporating the measuring unit 2, and may be one that is communicably connected to the measuring device. In this case, the measurement data output from the measuring device is received, and the parameter relating to the moving state of the moving body that holds the measuring device is calculated.
  • the simple movement amount estimation part 17 and the simple gravity direction estimation part 15b process using a part of measurement data which the high precision movement amount estimation part 16 and the high precision gravity direction estimation part 15a use.
  • a high-precision sensor for the high-precision movement amount estimation unit 16 and the high-precision gravity direction estimation unit 15a and a low-precision sensor for the simple movement amount estimation unit 17 and the simple gravity direction estimation unit 15b may be mounted. Good.
  • one block (for example, the movement amount estimation unit 12) can execute a plurality of calculation processes, and is designated by a control signal output from the adjustment unit 11 among the plurality of calculation processes.
  • the example which performs a calculation process was demonstrated, it is not restricted to this example.
  • the movement amount estimation unit 12 may be divided into a plurality of blocks that execute one type of calculation process, and the block specified by the control signal output from the adjustment unit 11 may be calculated.
  • the holding state estimation unit 10 outputs the state data directly to the movement amount estimation unit 12 and the like to estimate the movement amount.
  • the unit 12 or the like may determine and execute a calculation process according to the state data.
  • the calculation device of the present invention is a calculation device that calculates a parameter indicating the moving state of the moving body using measurement data output from one or more sensors held by the moving body. From the measurement data, a holding state specifying unit that specifies how the sensor is held by the moving body, and a calculation process according to the holding state specified by the holding state specifying unit are performed. It is a structure provided with the parameter calculation means which calculates the parameter which shows the movement state of a moving body.
  • the measurement data includes acceleration data indicating the magnitude and direction of the acceleration detected by the sensor, and angular velocity data indicating the magnitude and direction of the angular velocity detected by the sensor.
  • Posture angle calculating means for calculating the posture angle of the moving object using the data and the acceleration data
  • the holding state specifying means uses the posture angle calculated by the posture angle calculating means and the measurement data. It is preferable to specify how the sensor is held by the moving body.
  • the gravity direction of the moving object can be specified.
  • the holding state can be specified with higher accuracy. Therefore, according to the above configuration for specifying the holding state using the posture angle and the measurement data, it is possible to improve the specifying accuracy of the holding state, thereby increasing the accuracy with which appropriate arithmetic processing is performed. .
  • the measurement data includes acceleration data indicating the magnitude and direction of the acceleration detected by the sensor, and the calculation device uses the acceleration data to specify a gravity direction specifying means for specifying the gravity direction of the moving body. It is preferable that the holding state specifying unit specifies how the sensor is held by the moving body using the gravity direction specified by the gravity direction specifying unit and the measurement data.
  • the gravity azimuth specified by the gravity azimuth specifying means is the gravity azimuth of the moving object, not the gravity azimuth in the world coordinate system.
  • the holding state of the sensor is not always constant and may change.
  • the holding state changes by changing the sensor.
  • the measurement data detected by the sensor during a period in which the holding state changes from one holding state to another holding state has a value that is significantly different from normal. For this reason, when the parameter is calculated using the measurement data in this period as it is, there is a possibility that a parameter greatly different from the actual motion state is calculated.
  • the holding state specified by the holding state specifying unit includes a transition state in which the holding state of the sensor transitions to another holding state.
  • the transition state is specified as one of the holding states, and the parameter is calculated by the arithmetic processing according to the transition state, so that it is possible to prevent a parameter greatly different from the actual motion state from being calculated. be able to.
  • the holding state changes from the holding state held in the pocket to the holding state held in the hand.
  • the holding state during the period in which the holding state is changing is detected as the transition state.
  • the value of measurement data for example, acceleration data, angular velocity data, geomagnetism data, etc.
  • the value of measurement data rises sharply due to a large change in the position and orientation of the sensor in a short time. Often to do. For this reason, it is possible to detect the transition state by calculating the rate of change of the measurement data over time and determining whether the rate of change exceeds a predetermined threshold.
  • the method of always detecting the transition state with the same threshold value increases the detection accuracy of the transition state.
  • the value of measurement data output by the sensor increases accordingly.
  • the holding state specifying means sets a larger threshold value as the value of the measurement data output from the sensor is larger, and the transition is performed when the change rate of the measurement data exceeds the set threshold value. It is preferable to identify the state.
  • the transition state is specified by setting a threshold value having a large value of the measurement data output from the sensor, it is possible to improve the detection accuracy of the transition state.
  • the calculation device includes a simple parameter calculation unit that calculates a parameter indicating a moving state of the moving body using a part of the measurement data, and the parameter according to the holding state specified by the holding state specifying unit.
  • the parameter calculated by the calculation means is output, the parameter calculated by the simple parameter calculation means is output, or the parameter calculated by the parameter calculation means is combined with the parameter calculated by the simple parameter calculation means
  • switching means for switching whether to output the selected parameter is provided.
  • the parameter calculation unit since the parameter calculation unit is switched according to the holding state, the parameter can be calculated by an appropriate unit according to the holding state. For example, in a state where the value of measurement data is unstable such as a transition state, the parameter calculation accuracy by the parameter calculation means may be reduced. For this reason, in the state where the value of the measurement data is unstable, the parameter can be calculated by a simple calculation process using a small amount of measurement data by switching to the simple parameter calculation means.
  • calculating a parameter using a part of measurement data means calculating the parameter with a data amount smaller than the measurement data.
  • the measurement data includes acceleration data in the triaxial direction and angular velocity data in the triaxial direction
  • the parameter is calculated using only the acceleration data in the triaxial direction, the acceleration data in the triaxial direction and 2 This refers to calculating a parameter using the angular velocity data in the axial direction.
  • the parameter is calculated by reducing the data amount by increasing the period for acquiring the measurement data from the sensor or by increasing the period at which the sensor outputs the measurement data is included.
  • the sensor is controlled, and measurement data not used by the simple parameter calculating unit Among them, it is preferable to include a measurement control means for stopping at least a part of the measurement or reducing the output frequency of the measurement data.
  • the measurement by the sensor is partially stopped or the output frequency of the measurement data is lowered, so that the power consumption of the sensor is reduced. can do.
  • the gravity direction specifying means includes simple gravity direction specifying means for specifying the gravity direction of the moving body using a part of measurement data used for specifying the gravity direction of the moving body
  • the parameter calculating means includes:
  • the parameter is calculated using the gravity azimuth specified by the gravity azimuth specifying means or the simple gravity azimuth specifying means according to the holding state specified by the holding state specifying means.
  • measurement data with a value that is not assumed by the gravity azimuth specifying means is input, so it is more appropriate to obtain the gravity azimuth with a smaller amount of data than the gravity azimuth specified by the gravity azimuth specifying means.
  • a value may be calculated.
  • the parameter estimation accuracy can be increased.
  • the parameter calculation means does not identify the contribution of the measurement data output from the sensor during the period when the holding state specifying means is in the transition state as the holding state specifying means is in the transition state. It is preferable to calculate the parameter by a calculation process that is smaller than the contribution of measurement data output from the sensor during the period.
  • the measurement data output in the transition state is unstable and has low reliability. Therefore, in the above configuration, in the calculation processing in the transition state, the contribution of the measurement data output during the transition state period is relatively small. Thereby, the accuracy of parameters can be improved.
  • the computer may be realized by a computer.
  • a control program for realizing the computer by the computer by operating the computer as each unit of the computer, and recording the program Such computer-readable recording media also fall within the scope of the present invention.
  • each block of the positioning devices 1, 30, 40, 50, 60, and 70 (hereinafter referred to as the positioning device 1 and the like), in particular, the control unit 3 may be configured by hardware logic, as follows. Alternatively, it may be realized by software using a CPU.
  • the positioning device 1 or the like includes a CPU (central processing unit) that executes instructions of a control program that realizes each function, a ROM (read only memory) that stores the program, and a RAM (random access memory) that expands the program. And a storage device (recording medium) such as a memory for storing the program and various data.
  • An object of the present invention is a recording medium in which program codes (execution format program, intermediate code program, source program) of a control program such as the positioning device 1 which is software for realizing the functions described above are recorded so as to be readable by a computer. This can also be achieved by supplying to the positioning device 1 and the like and reading and executing the program code recorded on the recording medium by the computer (or CPU or MPU).
  • Examples of the recording medium include tapes such as magnetic tapes and cassette tapes, magnetic disks such as floppy (registered trademark) disks / hard disks, and disks including optical disks such as CD-ROM / MO / MD / DVD / CD-R.
  • Card system such as IC card, IC card (including memory card) / optical card, or semiconductor memory system such as mask ROM / EPROM / EEPROM / flash ROM.
  • the positioning device 1 or the like may be configured to be connectable to a communication network, and the program code may be supplied via the communication network.
  • the communication network is not particularly limited.
  • the Internet intranet, extranet, LAN, ISDN, VAN, CATV communication network, virtual private network, telephone line network, mobile communication network, satellite communication. A net or the like is available.
  • the transmission medium constituting the communication network is not particularly limited.
  • infrared rays such as IrDA and remote control, Bluetooth ( (Registered trademark), 802.11 wireless, HDR, mobile phone network, satellite line, terrestrial digital network, and the like can also be used.
  • the present invention can also be realized in the form of a computer data signal embedded in a carrier wave in which the program code is embodied by electronic transmission.
  • the parameter indicating the moving state of the moving object can be estimated with high accuracy.
  • the present invention can also be suitably applied to a navigation apparatus that displays a person's current location on a map.
  • Positioning device 2 Measurement unit (sensor) 10 Holding state estimation unit (holding state specifying means) 10c Holding state determination unit (measurement control means) 11 Adjustment unit (switching means) 12 Movement amount estimation unit (parameter calculation means) 12a Walking motion detection unit (parameter calculation means) 12b Stride estimation unit (parameter calculation means) 13 Position determination unit (parameter calculation means) 14 Attitude angle estimation unit (Attitude angle calculation means) 15 Gravity orientation estimation unit (gravity orientation identification means) 15b Simple gravity direction estimation unit (simple gravity direction specifying means) 16a Walking motion detection unit (parameter calculation means) 16b Stride estimation unit (parameter calculation means) 16c Moving direction detection unit (parameter calculation means) 16d movement vector calculation unit (parameter calculation means) 17 Simple movement amount estimation unit (simple parameter calculation means) 17a Walking motion detection unit (simple parameter calculation means) 17b Stride estimation unit (simple parameter calculation means) 17c Moving direction detection unit (simple parameter calculation means) 17d

Landscapes

  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Navigation (AREA)
  • Measurement Of Distances Traversed On The Ground (AREA)

Abstract

In order to estimate the parameter of the motion state of a mobile object with high accuracy, a positioning device (1) is provided with a holding state estimation unit (10) which specifies the holding state of the device in a mobile object from measurement data, and a movement amount estimation unit (12) which performs calculation processing corresponding to the holding state specified by the holding state estimation unit (10) and calculates the movement vector of the mobile object from the measurement data, thereby being able to estimate the movement vector of the mobile object with high accuracy.

Description

計算装置、計算装置の制御方法、制御プログラム、及び記録媒体COMPUTER DEVICE, COMPUTER DEVICE CONTROL METHOD, CONTROL PROGRAM, AND RECORDING MEDIUM
 本発明は、移動体に保持されたセンサからの出力に基づいて、該移動体の運動状態を示すパラメータを算出する計算装置に関し、より詳細には、移動体の位置を特定するために、該移動体の移動量を算出する計算装置に関するものである。 The present invention relates to a calculation device that calculates a parameter indicating a motion state of a moving body based on an output from a sensor held by the moving body, and more specifically, to specify the position of the moving body, The present invention relates to a calculation device that calculates the amount of movement of a moving object.
 移動体の位置を特定する測位装置の従来技術においては、GPS(Global Positioning System)やセル方式測位などの外部のインフラ装置を用いるものと、移動体の内界に関する自蔵式計測装置(具体的には、加速度センサ等)を用いて移動体の位置と姿勢を逐次に推定する自律航法システムを用いるものとがある。 In the conventional positioning device that identifies the position of a moving body, there are two types of devices that use external infrastructure devices such as GPS (Global Positioning System) and cell-based positioning, and self-contained measuring devices (specifically In some cases, an autonomous navigation system that sequentially estimates the position and orientation of a moving object using an acceleration sensor or the like is used.
 本発明は、後者の測位装置に関するものである。自律航法システムの場合、移動体には計測装置が固定して装着されることが多く、また単一の種類・設定の移動量推定手段が使われていた。なお、移動体の運動状態等を計測装置による検知によって特定する先行技術としては、下記の特許文献1~3、非特許文献1~4等が挙げられる。 The present invention relates to the latter positioning device. In the case of an autonomous navigation system, a measuring device is often fixedly mounted on a moving object, and a single type / setting of a moving amount estimating means is used. Note that, as prior arts for specifying the movement state of a moving body by detection by a measuring device, the following Patent Documents 1 to 3, Non-Patent Documents 1 to 4 and the like can be cited.
日本国公開特許公報「特許第4243684号公報(2005年4月28日公開)」Japanese Patent Gazette “Patent No. 4243684 (published on April 28, 2005)” 日本国公開特許公報「特開2007‐241867号公報(2007年9月26日公開)」Japanese Patent Publication “Japanese Laid-Open Patent Publication No. 2007-241867 (published September 26, 2007)” 日本国公開特許公報「特開2009‐93440号公報(2009年4月30日公開)」Japanese Patent Publication “Japanese Unexamined Patent Application Publication No. 2009-93440 (published April 30, 2009)”
 上記のように、従来の測位装置では、計測装置がどのような装着・保持姿勢となっているかにかかわらず、全く同じ演算処理で移動量の推定が行われていた。そして、移動量の推定に用いる演算処理は、特定の状態を想定した演算処理である。このため、想定外の装着・保持姿勢となっているときには、移動量の算出自体を行うことができなかったり、算出された移動量の精度が低下したりするという問題があった。 As described above, in the conventional positioning device, the movement amount is estimated by exactly the same calculation process regardless of the mounting / holding posture of the measuring device. Then, the calculation process used for estimating the movement amount is a calculation process assuming a specific state. For this reason, when the mounting / holding posture is unexpected, there is a problem that the calculation of the movement amount cannot be performed or the accuracy of the calculated movement amount is lowered.
 例えば、移動体が人である場合には、計測装置を手で保持している状態や、ポケットに入れている状態等様々な状態が想定される。そして、各状態では、計測装置が捉える運動の種類や大きさが異なっている。このため、計測装置を保持している人の移動を捕捉する際に最適な移動量推定手段の種類または設定も異なることになる。 For example, when the moving body is a person, various states such as a state in which the measuring device is held by hand and a state in which it is in a pocket are assumed. And in each state, the kind and magnitude | size of the exercise | movement which a measuring device catches differ. For this reason, when the movement of the person holding the measuring device is captured, the type or setting of the optimum movement amount estimation means is also different.
 なお、上記の問題は、移動量を算出する装置に限られず、センサの検出結果に基づいて移動体の運動状態を示すパラメータを算出する装置全般に生じる問題である。 Note that the above problem is not limited to a device that calculates the amount of movement, and is a problem that occurs in all devices that calculate parameters indicating the motion state of a moving body based on the detection result of a sensor.
 本発明は、上記の問題点に鑑みてなされたものであり、その目的は、計測装置の移動体に対する装着・保持姿勢に応じた適切な演算処理によって移動体の運動状態を示すパラメータを算出する計算装置等を提供することである。 The present invention has been made in view of the above-described problems, and an object of the present invention is to calculate a parameter indicating the motion state of the moving body by appropriate arithmetic processing according to the mounting / holding posture of the measuring apparatus with respect to the moving body. It is to provide a computing device or the like.
 上記課題を解決するために、本発明の計算装置は、移動体に保持される1または複数のセンサが出力する計測データを用いて、該移動体の移動状態を示すパラメータを算出する計算装置であって、上記計測データから、上記センサが移動体にどのように保持されているかを特定する保持状態特定手段と、上記保持状態特定手段が特定した保持状態に応じた演算処理を行い、上記計測データから上記移動体の移動状態を示すパラメータを算出するパラメータ算出手段とを備えていることを特徴としている。 In order to solve the above-described problems, a calculation apparatus according to the present invention is a calculation apparatus that calculates a parameter indicating a moving state of a moving object using measurement data output from one or more sensors held by the moving object. Then, from the measurement data, holding state specifying means for specifying how the sensor is held by the moving body, and calculation processing according to the holding state specified by the holding state specifying means are performed, and the measurement is performed. And a parameter calculating means for calculating a parameter indicating the moving state of the moving body from the data.
 また、本発明の計算装置の制御方法は、上記課題を解決するために、移動体に保持される1または複数のセンサが出力する計測データを用いて、該移動体の移動状態を示すパラメータを算出する計算装置の制御方法であって、上記計測データから、上記センサが移動体にどのように保持されているかを特定する保持状態特定ステップと、上記保持状態特定ステップで特定した保持状態に応じた演算処理を行い、上記計測データから上記移動体の移動状態を示すパラメータを算出するパラメータ算出ステップとを含むことを特徴としている。 In addition, in order to solve the above-described problem, the control method of the computing device of the present invention uses the measurement data output from one or more sensors held by the moving body to set a parameter indicating the moving state of the moving body. A control method of a computing device to calculate, according to a holding state specifying step for specifying how the sensor is held on a moving body from the measurement data, and a holding state specified in the holding state specifying step And a parameter calculating step of calculating a parameter indicating a moving state of the moving body from the measurement data.
 上記の構成によれば、センサが移動体にどのように保持されているかに応じた演算処理によって、移動体の移動状態を示すパラメータを算出するので、パラメータの信頼性及び精度を高めることができる。 According to the above configuration, since the parameter indicating the moving state of the moving body is calculated by the arithmetic processing according to how the sensor is held by the moving body, the reliability and accuracy of the parameter can be improved. .
 なお、演算処理は、想定される保持状態毎に予め用意されている。そして、異なる保持状態に対応する演算処理は、その演算過程(例えば用いる数式や手順等)が異なるものであってもよいし、異なっていてもよい。なお、演算過程が同じである場合には、重み付けやスケールファクタの切り替えなどにより、保持状態に応じたパラメータの値を算出する。 Note that arithmetic processing is prepared in advance for each assumed holding state. The calculation processes corresponding to different holding states may be different or different in the calculation process (for example, mathematical formulas and procedures used). When the calculation process is the same, the parameter value corresponding to the holding state is calculated by weighting, switching of the scale factor, or the like.
 また、上記センサは、移動体の移動状態を特定するために必要な計測データを出力するものであればよい。例えば、加速度センサ、ジャイロセンサ、地磁気センサ、気圧センサ等が挙げられる。 Further, the sensor may be any sensor that outputs measurement data necessary for specifying the moving state of the moving body. For example, an acceleration sensor, a gyro sensor, a geomagnetic sensor, an atmospheric pressure sensor, and the like can be given.
 さらに、上記の構成において、算出するパラメータは、移動体の移動状態を示すものであればよく、特に限定されない。上記パラメータとしては、例えば、移動方向、移動速度、移動距離等が挙げられる。なお、加速度等の計測データは、保持状態によって変動が大きいので、本発明は、加速度を用いたパラメータの算出に特に好適である。 Furthermore, in the above configuration, the parameter to be calculated is not particularly limited as long as it indicates the moving state of the moving body. Examples of the parameter include a moving direction, a moving speed, and a moving distance. Note that measurement data such as acceleration varies greatly depending on the holding state, and therefore the present invention is particularly suitable for calculating parameters using acceleration.
 また、上記の構成において、センサがどのように保持されているか(保持状態)は、予め想定した保持状態の何れに該当するか、あるいは何れにも該当しないかを計測データに基づいて判断することができる。例えば、保持状態と、その保持状態のときに出力される計測データのパターンとを対応付けて記憶しておいてもよい。 Further, in the above configuration, how the sensor is held (holding state) is determined based on the measurement data as to which of the holding states assumed in advance corresponds to none. Can do. For example, a holding state and a pattern of measurement data output in the holding state may be stored in association with each other.
 以上のように、本発明の計算装置は、計測データから、センサが移動体にどのように保持されているかを特定する保持状態特定手段と、上記保持状態特定手段が特定した保持状態に応じた演算処理を行い、上記計測データから上記移動体の移動状態を示すパラメータを算出するパラメータ算出手段とを備えている構成である。 As described above, the calculation apparatus according to the present invention responds to the holding state specifying means for specifying how the sensor is held by the moving body and the holding state specified by the holding state specifying means from the measurement data. It is a structure provided with the parameter calculation means which performs a calculation process and calculates the parameter which shows the movement state of the said mobile body from the said measurement data.
 また、本発明の計算装置の制御方法は、以上のように、計測データから、センサが移動体にどのように保持されているかを特定する保持状態特定ステップと、上記保持状態特定ステップで特定した保持状態に応じた演算処理を行い、上記計測データから上記移動体の移動状態を示すパラメータを算出するパラメータ算出ステップとを含む構成である。 In addition, as described above, the control method of the computing device of the present invention is specified from the measurement data by the holding state specifying step for specifying how the sensor is held by the moving body and the holding state specifying step. And a parameter calculating step of performing a calculation process according to the holding state and calculating a parameter indicating the moving state of the moving body from the measurement data.
 上記の構成によれば、センサが移動体にどのように保持されているかに応じた演算処理によって、移動体の移動状態を示すパラメータを算出するので、パラメータの信頼性及び精度を高めることができるという効果を奏する。 According to the above configuration, since the parameter indicating the moving state of the moving body is calculated by the arithmetic processing according to how the sensor is held by the moving body, the reliability and accuracy of the parameter can be improved. There is an effect.
 本発明のさらに他の目的、特徴、および優れた点は、以下に示す記載によって十分わかるであろう。また、本発明の利益は、添付図面を参照した次の説明で明白になるであろう。 Further objects, features, and superior points of the present invention will be fully understood from the following description. The benefits of the present invention will become apparent from the following description with reference to the accompanying drawings.
本発明の一実施形態を示すものであり、測位装置の要部構成を示すブロック図である。BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 illustrates an embodiment of the present invention, and is a block diagram illustrating a configuration of a main part of a positioning device. 上記測位装置で用いられる信号特定テーブルの一例を示す図である。It is a figure which shows an example of the signal specific table used with the said positioning apparatus. 上記測位装置が実行する処理の一例を示すフローチャートである。It is a flowchart which shows an example of the process which the said positioning apparatus performs. 計測部として加速度センサを用いた測位装置の要部構成を示すブロック図である。It is a block diagram which shows the principal part structure of the positioning apparatus using an acceleration sensor as a measurement part. 姿勢角推定部を備える測位装置の要部構成を示すブロック図である。It is a block diagram which shows the principal part structure of a positioning apparatus provided with a posture angle estimation part. 重力方位推定部を備える測位装置の要部構成を示すブロック図である。It is a block diagram which shows the principal part structure of a positioning apparatus provided with a gravity direction estimation part. 歩行者の移動ベクトルを算出する測位装置の要部構成を示すブロック図である。It is a block diagram which shows the principal part structure of the positioning apparatus which calculates the movement vector of a pedestrian. 本発明の他の実施形態にかかる測位装置の要部構成を示すブロック図である。It is a block diagram which shows the principal part structure of the positioning apparatus concerning other embodiment of this invention. 上記測位装置が備える高精度移動量推定部の要部構成を示すブロック図である。It is a block diagram which shows the principal part structure of the highly accurate movement amount estimation part with which the said positioning apparatus is provided. 上記測位装置が備える簡易移動量推定部の要部構成を示すブロック図である。It is a block diagram which shows the principal part structure of the simple movement amount estimation part with which the said positioning apparatus is provided. 遷移状態の推定を行う測位装置の要部構成を示すブロック図である。It is a block diagram which shows the principal part structure of the positioning apparatus which estimates a transition state. 上記測位装置が備える保持状態推定部の要部構成を示すブロック図である。It is a block diagram which shows the principal part structure of the holding | maintenance state estimation part with which the said positioning apparatus is provided. 上記測位装置が備える簡易移動量推定部の要部構成を示すブロック図である。It is a block diagram which shows the principal part structure of the simple movement amount estimation part with which the said positioning apparatus is provided. 上記測位装置が実行する遷移状態検出処理の一例を示すフローチャートである。It is a flowchart which shows an example of the transition state detection process which the said positioning apparatus performs. 重力方位推定部を2つ備えた測位装置の要部構成を示すブロック図である。It is a block diagram which shows the principal part structure of the positioning apparatus provided with two gravity direction estimation parts. 上記測位装置が備える保持状態推定部の要部構成を示すブロック図である。It is a block diagram which shows the principal part structure of the holding | maintenance state estimation part with which the said positioning apparatus is provided. 重力方位ベクトルが入力される高精度移動量推定部の要部構成を示すブロック図である。It is a block diagram which shows the principal part structure of the highly accurate movement amount estimation part to which a gravity direction vector is input. 重力方位ベクトルが入力される簡易移動量推定部の要部構成を示すブロック図である。It is a block diagram which shows the principal part structure of the simple movement amount estimation part to which a gravity direction vector is input.
 〔実施の形態1〕
 本実施形態の測位装置について、図1から図7に基づいて説明する。ここでは、まず、測位装置の概要について、図1に基づいて説明する。図1は、測位装置(計算装置)1の要部構成を示すブロック図である。図示のように、測位装置1は、計測部(センサ)2、制御部3、及び記憶部4を備えている。
[Embodiment 1]
The positioning device of this embodiment will be described with reference to FIGS. Here, first, an outline of the positioning device will be described with reference to FIG. FIG. 1 is a block diagram showing a main configuration of a positioning device (calculation device) 1. As illustrated, the positioning device 1 includes a measurement unit (sensor) 2, a control unit 3, and a storage unit 4.
 測位装置1は、移動体(人や物体)に装着または保持されて、該移動体の運動状態を示すパラメータを出力する装置である。具体的には、測位装置1は、移動体の運動と状態の変化等を検出するセンサである計測部2が測定した計測データを用いて当該移動体の移動ベクトルを算出し、この移動ベクトルから移動体の現在位置を算出して出力する。 The positioning device 1 is a device that is attached to or held by a moving body (a person or an object) and outputs a parameter indicating the motion state of the moving body. Specifically, the positioning device 1 calculates a movement vector of the moving body using the measurement data measured by the measuring unit 2 which is a sensor that detects the movement and state change of the moving body. Calculate and output the current position of the moving object.
 計測部2は、上記のように、移動体の運動状態や移動体が存在する位置等を検出して、その検出値を計測データとして出力するセンサである。また、計測部2は、計測データと共に、最後に計測データを出力した後の経過時間ΔTを出力する。これにより、計測データの経時変化が把握される。 The measurement unit 2 is a sensor that detects the movement state of the moving body, the position where the moving body exists, and the like and outputs the detected value as measurement data as described above. Moreover, the measurement part 2 outputs elapsed time (DELTA) T after outputting measurement data last with measurement data. Thereby, the time-dependent change of measurement data is grasped.
 計測部2は、測位装置1が出力するパラメータの種類、要求されるパラメータの精度等に応じたセンサで構成すればよい。例えば、計測部2は、加速度センサ、ジャイロセンサ、磁気センサ、及び気圧センサの何れかまたは複数の組み合わせによって構成することができる。 The measuring unit 2 may be configured by a sensor corresponding to the type of parameter output by the positioning device 1, the accuracy of the required parameter, and the like. For example, the measurement unit 2 can be configured by any one or a combination of an acceleration sensor, a gyro sensor, a magnetic sensor, and an atmospheric pressure sensor.
 制御部3は、測位装置1を統括的に制御するものであり、計測部2が出力する計測データを用いて移動体の現在位置を算出し、出力する制御を行う。この制御は、制御部3が備える保持状態推定部(保持状態特定手段)10、調整部11、移動量推定部(パラメータ算出手段)12、及び位置決定部13によって実現される。 The control unit 3 controls the positioning device 1 in an integrated manner, and performs control to calculate and output the current position of the moving body using the measurement data output from the measurement unit 2. This control is realized by a holding state estimation unit (holding state identification unit) 10, an adjustment unit 11, a movement amount estimation unit (parameter calculation unit) 12, and a position determination unit 13 provided in the control unit 3.
 保持状態推定部10は、計測部2の出力する計測データから、移動体に対する測位装置1(正確には計測部2)の装着・保持姿勢(移動体にどのように保持されているか)を推定し、推定した姿勢を示す状態データを出力する。 The holding state estimation unit 10 estimates the mounting / holding posture of the positioning device 1 (more precisely, the measurement unit 2) with respect to the moving body (how it is held by the moving body) from the measurement data output by the measuring unit 2. And output state data indicating the estimated posture.
 なお、ここでは、予め想定される装着・保持姿勢と、その装着・保持姿勢で検出される計測データのパターンとを対応付けたデータを用いて装着・保持姿勢を特定し、その装着・保持姿勢に対応する状態データを出力することを想定している。 Here, the mounting / holding posture is specified using data that associates a presumed mounting / holding posture with a pattern of measurement data detected by the mounting / holding posture, and the mounting / holding posture is determined. It is assumed that the status data corresponding to is output.
 このような、装着・保持姿勢の特定は、例えばAdaBoostによる機械学習の枠組みを利用して、計測部2からの計測データ(加速度、角速度、磁気、気圧など)に基づいて、想定される装着・保持姿勢を識別する識別器を構成することによって実現することもできる。なお、Adaboostを用いた装着・保持姿勢の識別は、非特許文献1に記載されているように公知技術であるから、ここでは説明を省略する。 For example, the mounting / holding posture is specified by using a machine learning framework by AdaBoost, for example, based on measurement data (acceleration, angular velocity, magnetism, atmospheric pressure, etc.) from the measurement unit 2. It can also be realized by configuring a discriminator for identifying the holding posture. In addition, since identification of the mounting / holding posture using Adaboost is a known technique as described in Non-Patent Document 1, description thereof is omitted here.
 そこで、測位装置1では、予め想定した装着・保持姿勢を識別するために必要なパラメータを検出できるように計測部2を構成する。そして、計測部2の計測データのパターンから何れの装着・保持姿勢に該当するかを識別し、識別された装着・保持姿勢を示す状態データを出力する。 Therefore, in the positioning device 1, the measuring unit 2 is configured so as to be able to detect parameters necessary for identifying a mounting / holding posture assumed in advance. Then, it identifies which mounting / holding posture corresponds to the measurement data pattern of the measuring unit 2 and outputs state data indicating the identified mounting / holding posture.
 調整部11は、保持状態推定部10が推定した装着・保持姿勢に応じた演算処理によって移動体の運動状態を示すパラメータが算出されるように、移動量推定部12を制御する。具体的には、調整部11は、記憶部4に格納されている信号特定テーブル20を参照して、保持状態推定部10が出力する状態データに対応する制御信号を特定し、この制御信号を移動量推定部12に出力することによって、上記の制御を行う。なお、信号特定テーブル20については後述する。 The adjustment unit 11 controls the movement amount estimation unit 12 so that a parameter indicating the movement state of the moving body is calculated by a calculation process according to the wearing / holding posture estimated by the holding state estimation unit 10. Specifically, the adjustment unit 11 specifies a control signal corresponding to the state data output from the holding state estimation unit 10 with reference to the signal specification table 20 stored in the storage unit 4, and uses this control signal. The above control is performed by outputting to the movement amount estimation unit 12. The signal specification table 20 will be described later.
 移動量推定部12は、保持状態推定部10が推定した装着・保持姿勢に応じた演算処理によって移動体の運動状態を示すパラメータを算出する。具体的には、移動量推定部12は、計測部2が出力する計測データと、調整部11が出力する制御信号とを受信して、該制御信号が示す演算処理によって上記計測データから移動体の移動方向及び移動距離を示す移動ベクトルを算出し、出力する。 The movement amount estimation unit 12 calculates a parameter indicating the movement state of the moving body by a calculation process according to the wearing / holding posture estimated by the holding state estimation unit 10. Specifically, the movement amount estimation unit 12 receives the measurement data output from the measurement unit 2 and the control signal output from the adjustment unit 11, and moves the moving object from the measurement data by the arithmetic processing indicated by the control signal. The movement vector indicating the movement direction and the movement distance is calculated and output.
 位置決定部13は、移動量推定部12が出力する移動ベクトルから移動体の現在位置を決定する。決定した現在位置は、例えば測位装置1の現在位置を示す画像を表示させることで出力される。 The position determination unit 13 determines the current position of the moving object from the movement vector output by the movement amount estimation unit 12. The determined current position is output, for example, by displaying an image indicating the current position of the positioning device 1.
 記憶部4は、測位装置1で使用する各種データを記憶する装置である。図示のように、記憶部4には、信号特定テーブル20が格納されている。 The storage unit 4 is a device that stores various data used in the positioning device 1. As shown in the figure, the signal specifying table 20 is stored in the storage unit 4.
 信号特定テーブル20は、調整部11が、保持状態推定部10が出力する状態データに対応する制御信号を特定するためのテーブルである。信号特定テーブル20は、例えば図2に示すようなものとしてもよい。図2は、信号特定テーブル20の一例を示す図である。 The signal specification table 20 is a table for the adjustment unit 11 to specify a control signal corresponding to the state data output from the holding state estimation unit 10. The signal specifying table 20 may be as shown in FIG. FIG. 2 is a diagram illustrating an example of the signal identification table 20.
 図2に示すように、信号特定テーブル20は、保持状態と、制御信号とが対応付けられたデータである。具体的には、図2の信号特定テーブル20では、保持状態1、2、3、…に制御信号(1)、(2)、(3)、…がそれぞれ対応付けられている。 As shown in FIG. 2, the signal specification table 20 is data in which the holding state and the control signal are associated with each other. Specifically, in the signal identification table 20 of FIG. 2, the control signals (1), (2), (3),... Are associated with the holding states 1, 2, 3,.
 つまり、図2の信号特定テーブル20では、保持状態推定部10は、計測部2が出力する計測データから、測位装置1の保持状態が、図2の1、2、3、…の何れの保持状態に該当するかを特定し、特定した保持状態を示す状態データを調整部11に出力することを想定している。なお、計測部2が出力する計測データから、図2に示される保持状態の何れにも該当しないと判断されることも考えられる。この場合には、最も近い保持状態を示す状態データを出力してもよいし、該当しない旨の状態データを出力してもよい。 That is, in the signal identification table 20 of FIG. 2, the holding state estimation unit 10 determines that the holding state of the positioning device 1 is any one of 1, 2, 3,. It is assumed that the state corresponds to the state, and the state data indicating the specified holding state is output to the adjustment unit 11. Note that it may be determined from the measurement data output by the measurement unit 2 that it does not correspond to any of the holding states shown in FIG. In this case, status data indicating the closest holding state may be output, or status data indicating that it is not applicable may be output.
 そして、調整部11は、信号特定テーブル20を参照して、出力された状態データに対応付けられている制御信号が、制御信号(1)、(2)、(3)、…の何れに該当するかを特定することになる。なお、図示の例では、1つの保持状態に1つの制御信号が対応付けられているが、複数の制御信号を対応付けてもよい。これにより、移動量推定部12の行う演算処理を細かく制御することが可能になる。 Then, the adjustment unit 11 refers to the signal identification table 20, and the control signal associated with the output state data corresponds to any of the control signals (1), (2), (3),. You will specify what to do. In the illustrated example, one control signal is associated with one holding state, but a plurality of control signals may be associated. Thereby, it is possible to finely control the arithmetic processing performed by the movement amount estimation unit 12.
 また、上記のように、保持状態推定部10が、何れの保持状態にも該当しない旨の状態データを出力する構成とした場合には、何れの保持状態にも該当しない状態に対応する制御信号を対応付けておくことが好ましい。これにより、何れの保持状態にも該当しない場合であっても、適切な演算処理で移動ベクトルの算出を行うことが可能になる。 In addition, as described above, when the holding state estimation unit 10 is configured to output state data indicating that it does not correspond to any holding state, a control signal corresponding to a state that does not correspond to any holding state Are preferably associated with each other. Thereby, even if it does not correspond to any holding state, it becomes possible to calculate the movement vector by an appropriate calculation process.
 そして、調整部11は、図2の信号特定テーブル20を参照して特定した制御信号を移動量推定部12に出力し、移動量推定部12は、出力された制御信号に応じた演算処理を行って移動ベクトルを算出することになる。 Then, the adjustment unit 11 outputs the control signal identified with reference to the signal identification table 20 of FIG. 2 to the movement amount estimation unit 12, and the movement amount estimation unit 12 performs arithmetic processing according to the output control signal. The movement vector is calculated by going.
 なお、各保持状態に対応する演算処理は、例えば、その保持状態においてどのような測定データが検出されるかを実際に測定し、その結果に基づいて特定してもよい。また、例えば、AdaBoostによる機械学習の枠組みを利用して、保持状態に応じた適切な演算処理を特定することもできる。 Note that the arithmetic processing corresponding to each holding state may be specified based on the result of actually measuring what measurement data is detected in the holding state, for example. Further, for example, it is possible to specify an appropriate arithmetic processing according to the holding state by using a machine learning framework by AdaBoost.
 このように、信号特定テーブル20は、予め想定している保持状態と、その保持状態に応じた演算処理を移動量推定部12に実行させるための制御信号とが対応付けられたものである。 As described above, the signal identification table 20 is a table in which a presumed holding state is associated with a control signal for causing the movement amount estimating unit 12 to execute a calculation process according to the holding state.
 〔処理の流れ〕
 続いて、測位装置1が実行する処理の流れについて、図3に基づいて説明する。図3は、測位装置1が実行する処理の一例を示すフローチャートである。
[Process flow]
Next, the flow of processing executed by the positioning device 1 will be described with reference to FIG. FIG. 3 is a flowchart illustrating an example of processing executed by the positioning device 1.
 保持状態推定部10は、計測部2から計測データの入力の有無を確認し(S1)、計測データの入力が確認された場合(S1でYES)には、計測データから測位装置1の保持状態(装着・保持姿勢)を推定する(S2)。そして、推定した保持状態を示す状態データを調整部11に出力する。 The holding state estimation unit 10 confirms whether or not measurement data is input from the measurement unit 2 (S1), and when the measurement data is input (YES in S1), the holding state of the positioning device 1 is determined from the measurement data. (Mounting / holding posture) is estimated (S2). Then, state data indicating the estimated holding state is output to the adjustment unit 11.
 次に、状態データを受信した調整部11は、信号特定テーブル20を参照して、受信した状態データに対応する制御信号を特定し、特定した制御信号を生成する(S3)。また、調整部11は、生成した制御信号を移動量推定部12に出力する。 Next, the adjustment unit 11 that has received the state data refers to the signal identification table 20 to identify a control signal corresponding to the received state data, and generates the identified control signal (S3). The adjustment unit 11 outputs the generated control signal to the movement amount estimation unit 12.
 そして、制御信号を受信した移動量推定部12は、受信した制御信号に応じた演算処理を行い、移動ベクトルを算出する(S4)。この後、移動量推定部12は、算出した移動ベクトルを位置決定部13に送信し、移動ベクトルを受信した位置決定部13が受信した移動ベクトルに基づいて測位装置1の現在位置を算出及び出力して処理が終了する。 Then, the movement amount estimation unit 12 that has received the control signal performs a calculation process according to the received control signal and calculates a movement vector (S4). Thereafter, the movement amount estimation unit 12 transmits the calculated movement vector to the position determination unit 13, and calculates and outputs the current position of the positioning device 1 based on the movement vector received by the position determination unit 13 that has received the movement vector. Then, the process ends.
 〔加速度センサを用いる例〕
 次に、計測部2として加速度センサを用いた場合の例を図4に基づいて説明する。図4は、計測部2として加速度センサを用いた測位装置1の要部構成を示すブロック図である。図示の測位装置1は、計測部として加速度センサ2aを備えている。加速度センサ2aは、互いに垂直な3軸方向の加速度ベクトルを検出して、加速度データとして出力する3軸加速度センサである。
[Example using acceleration sensor]
Next, an example in which an acceleration sensor is used as the measurement unit 2 will be described with reference to FIG. FIG. 4 is a block diagram showing a main configuration of the positioning device 1 using an acceleration sensor as the measuring unit 2. The illustrated positioning apparatus 1 includes an acceleration sensor 2a as a measuring unit. The acceleration sensor 2a is a triaxial acceleration sensor that detects acceleration vectors in three axial directions perpendicular to each other and outputs the acceleration vectors as acceleration data.
 このような3軸加速度センサを用いることにより、保持状態を特定し、また移動ベクトルを算出することができることが知られている。例えば、非特許文献2や特許文献2には、人に保持された3軸加速度センサが出力する3軸の加速度データから、人が歩いているか、走っているか、階段の昇降を行っているか等の運動状態を推定することが記載されている。 It is known that a holding state can be specified and a movement vector can be calculated by using such a three-axis acceleration sensor. For example, Non-Patent Document 2 and Patent Document 2 describe whether a person is walking, running, or going up and down stairs from 3-axis acceleration data output by a 3-axis acceleration sensor held by a person. Is described.
 この技術においては、ウェーブレットパケット変換を用いて3軸加速度データから特徴ベクトルを抽出し、非特許文献3等に記載の自己組織化手法を用いて各状態(歩行、走行等)のクラスタリングを行っている。 In this technology, feature vectors are extracted from triaxial acceleration data using wavelet packet transformation, and each state (walking, running, etc.) is clustered using a self-organization method described in Non-Patent Document 3 or the like. Yes.
 このような技術を応用することにより、3軸加速度データから保持状態を推定することができる。すなわち、図4の保持状態推定部10は、ウェーブレットパケット変換を用いて時系列の3軸加速度データから抽出した特徴ベクトルから、予め自己組織化手法でクラスタリングされた保持状態の何れに該当するかを特定する。 By applying such technology, the holding state can be estimated from the triaxial acceleration data. That is, the holding state estimation unit 10 in FIG. 4 determines which of holding states clustered in advance by a self-organization method from feature vectors extracted from time-series triaxial acceleration data using wavelet packet transformation. Identify.
 また、図4の移動量推定部12は、3軸加速度データを用いて調整部11から受信した制御信号に応じた演算処理を行うことによって、移動ベクトルを算出する。なお、3軸加速度データから移動ベクトルを算出する演算処理は公知であるから、ここでは説明を省略する。 Further, the movement amount estimation unit 12 in FIG. 4 calculates a movement vector by performing arithmetic processing according to the control signal received from the adjustment unit 11 using the triaxial acceleration data. In addition, since the calculation process which calculates a movement vector from triaxial acceleration data is well-known, description is abbreviate | omitted here.
 〔姿勢角推定部を備えた例〕
 世界座標系に対する移動体の姿勢角を算出することにより、移動体の重力方位(世界座標系の重力方向とは通常異なる)を決定することができ、これにより、運動状態をより高精度に特定することができる。
[Example with posture angle estimation unit]
By calculating the attitude angle of the moving body with respect to the world coordinate system, it is possible to determine the gravity direction of the moving body (usually different from the gravity direction of the world coordinate system). can do.
 ここでは、姿勢角を算出する姿勢角推定部を備えた測位装置について、図5に基づいて説明する。図5は、姿勢角推定部を備える測位装置(計算装置)30の要部構成を示すブロック図である。なお、図1、図4の測位装置1と同様の構成については同一の参照番号を付し、その説明を省略する。 Here, a positioning device including an attitude angle estimation unit that calculates an attitude angle will be described with reference to FIG. FIG. 5 is a block diagram illustrating a main configuration of a positioning device (calculation device) 30 including a posture angle estimation unit. In addition, about the structure similar to the positioning apparatus 1 of FIG. 1, FIG. 4, the same reference number is attached | subjected and the description is abbreviate | omitted.
 図示のように、測位装置30は、計測部として加速度センサ2aとジャイロセンサ2bとを備えている。ジャイロセンサ2bは、角速度ベクトルを検出して角速度データを出力する。ここでは、ジャイロセンサ2bは、3軸方向の角速度データを出力することを想定しているが、2軸以下であっても構わない。 As illustrated, the positioning device 30 includes an acceleration sensor 2a and a gyro sensor 2b as measurement units. The gyro sensor 2b detects an angular velocity vector and outputs angular velocity data. Here, it is assumed that the gyro sensor 2b outputs angular velocity data in the triaxial direction, but it may be biaxial or less.
 姿勢角推定部(姿勢角算出手段)14は、加速度センサ2aが出力する加速度データと、ジャイロセンサ2bが出力する角速度データとを用いて測位装置30を保持している移動体の姿勢角を算出する。また、姿勢角推定部14は、算出した姿勢角を保持状態推定部10と、移動量推定部12に出力する。 The posture angle estimation unit (posture angle calculation means) 14 calculates the posture angle of the moving body holding the positioning device 30 using the acceleration data output from the acceleration sensor 2a and the angular velocity data output from the gyro sensor 2b. To do. The posture angle estimation unit 14 outputs the calculated posture angle to the holding state estimation unit 10 and the movement amount estimation unit 12.
 姿勢角を時系列のデータとして取得することにより、移動体が作り出す運動について、加速、減速、重心の移動等に加えて、姿勢角の変化を計測することが可能となる。これによって、より正確かつ細やかに移動体の状態を推定することができる。すなわち、姿勢角推定部14を設けることにより、保持状態の推定精度を高めることや、検出可能な保持状態のバリエーションを増やすこと等も可能になる。 By acquiring the posture angle as time-series data, it is possible to measure the change of the posture angle in addition to acceleration, deceleration, movement of the center of gravity, etc., regarding the movement created by the moving body. As a result, the state of the moving body can be estimated more accurately and finely. That is, by providing the posture angle estimation unit 14, it is possible to increase the estimation accuracy of the holding state, increase the variation of the holding state that can be detected, and the like.
 また、移動量推定部12は、姿勢角推定部14が出力する姿勢角を用いて移動体の移動方向を特定し、これに基づき移動ベクトルを算出する。なお、姿勢角から移動方向を求める方法は公知であるから、ここでは説明を省略する。 Also, the movement amount estimation unit 12 specifies the movement direction of the moving body using the posture angle output from the posture angle estimation unit 14, and calculates a movement vector based on this. In addition, since the method of calculating | requiring a moving direction from an attitude angle is well-known, description is abbreviate | omitted here.
 〔重力方位推定部を備えた例〕
 移動体の重力方位を算出することによっても、移動体の運動状態をより高精度に特定することができる。なお、上記のように、移動体の重力方位は、世界座標系の重力方向とは通常異なっている。
[Example with gravity direction estimation unit]
The motion state of the moving body can be specified with higher accuracy also by calculating the gravity direction of the moving body. Note that, as described above, the gravity direction of the moving body is usually different from the gravity direction of the world coordinate system.
 ここでは、重力方位を算出する重力方位推定部を備えた測位装置について、図6に基づいて説明する。図6は、重力方位推定部を備える測位装置(計算装置)40の要部構成を示すブロック図である。なお、図1、図4の測位装置1と同様の構成については同一の参照番号を付し、その説明を省略する。 Here, a positioning device including a gravity direction estimation unit for calculating the gravity direction will be described with reference to FIG. FIG. 6 is a block diagram illustrating a main configuration of a positioning device (calculation device) 40 including a gravity direction estimation unit. In addition, about the structure similar to the positioning apparatus 1 of FIG. 1, FIG. 4, the same reference number is attached | subjected and the description is abbreviate | omitted.
 重力方位推定部(重力方位特定手段)15は、計測部2が出力する計測データを用いて測位装置40(正確には計測部2)の重力方位ベクトルを算出する。また、重力方位推定部15は、算出した重力方位ベクトルを保持状態推定部10と、移動量推定部12に出力する。 The gravity direction estimation unit (gravity direction identification means) 15 calculates the gravity direction vector of the positioning device 40 (more precisely, the measurement unit 2) using the measurement data output from the measurement unit 2. Further, the gravity direction estimation unit 15 outputs the calculated gravity direction vector to the holding state estimation unit 10 and the movement amount estimation unit 12.
 なお、重力方位ベクトルは、加速度ベクトルと角速度ベクトルとを用いて重力加速度ベクトルをトラッキングすることで特定することができる。このため、測位装置40は、計測部2として、少なくとも加速度センサとジャイロセンサとを備えている必要がある。なお、非特許文献2には、カルマンフィルタの枠組みを用いて、加速度ベクトルと角速度ベクトルとを入力として重力加速度ベクトルをトラッキングすることが記載されている。重力方位推定部15は、このような技術によって実現することもできる。 The gravity direction vector can be specified by tracking the gravity acceleration vector using the acceleration vector and the angular velocity vector. For this reason, the positioning device 40 needs to include at least an acceleration sensor and a gyro sensor as the measurement unit 2. Non-Patent Document 2 describes that a gravitational acceleration vector is tracked using an input of an acceleration vector and an angular velocity vector using a Kalman filter framework. The gravity direction estimation unit 15 can also be realized by such a technique.
 重力方位ベクトルは、重力に対する姿勢角を表すものであるから、保持状態を推定する上で大きなヒントになる。すなわち、保持状態推定部10は、重力方位推定部15が出力する重力方位ベクトルを用いることによって、保持状態を高精度に推定することができ、また検出可能な保持状態のバリエーションを増やすこと等も可能になる。 Since the gravity direction vector represents the attitude angle with respect to gravity, it is a great hint for estimating the holding state. That is, the holding state estimation unit 10 can estimate the holding state with high accuracy by using the gravity direction vector output by the gravity direction estimation unit 15, and increase the number of detectable holding states. It becomes possible.
 また、移動量推定部12は、重力方位推定部15が出力する重力方位ベクトルを用いることによって、計測データ(加速度データ、角速度データ等)を重力方向成分とそれ以外とに分解することができるので、移動ベクトルの推定精度を高めることができる。 Further, the movement amount estimation unit 12 can decompose the measurement data (acceleration data, angular velocity data, etc.) into the gravity direction component and the other by using the gravity direction vector output from the gravity direction estimation unit 15. The estimation accuracy of the movement vector can be improved.
 〔移動体が歩行者である場合の構成例〕
 続いて、移動体が歩行者であることを想定して構成した測位装置の例を図7に基づいて説明する。図7は、歩行者の移動ベクトルを算出する測位装置の要部構成を示すブロック図である。なお、図1、図4の測位装置1と同様の構成については同一の参照番号を付し、その説明を省略する。
[Configuration example when the moving body is a pedestrian]
Next, an example of a positioning device configured on the assumption that the moving body is a pedestrian will be described with reference to FIG. FIG. 7 is a block diagram showing a main configuration of a positioning device that calculates a pedestrian movement vector. In addition, about the structure similar to the positioning apparatus 1 of FIG. 1, FIG. 4, the same reference number is attached | subjected and the description is abbreviate | omitted.
 測位装置50(計算装置)は、図示のように、移動量推定部として、歩行動作検出部(パラメータ算出手段)12a、歩幅推定部(パラメータ算出手段)12b、移動方位検出部12c、及び移動ベクトル算出部12dを備えている。調整部11は、このうち歩行動作検出部12a及び歩幅推定部12bに制御信号を送信して、保持状態に応じた、最も高い性能を発揮する演算処理を行わせる。 As illustrated, the positioning device 50 (calculation device) includes a walking motion detection unit (parameter calculation unit) 12a, a stride estimation unit (parameter calculation unit) 12b, a movement direction detection unit 12c, and a movement vector as a movement amount estimation unit. A calculation unit 12d is provided. Among these, the adjustment part 11 transmits a control signal to the walking motion detection part 12a and the stride estimation part 12b, and performs the arithmetic processing which exhibits the highest performance according to the holding | maintenance state.
 なお、ここでは、計測部2として3軸加速度センサ、3軸角速度センサ、及び3軸地磁気センサを備えていることを想定している。また、ここでは、歩行者の移動ベクトルを算出して、歩行者の現在位置を出力することを想定している。 Here, it is assumed that the measurement unit 2 includes a three-axis acceleration sensor, a three-axis angular velocity sensor, and a three-axis geomagnetic sensor. Here, it is assumed that the movement vector of the pedestrian is calculated and the current position of the pedestrian is output.
 歩行動作検出部12aは、調整部11から受信した制御信号に応じた演算処理により、計測部2が出力する計測データから、歩行動作が行われているか否かを特定する。つまり、歩行動作検出部12aは、複数通りの演算処理で歩行動作の検出が可能であり、これらの演算処理のうち、制御信号で指定された演算処理によって歩行動作を検出する。 The walking motion detection unit 12a identifies whether or not a walking motion is being performed from the measurement data output by the measurement unit 2 by a calculation process according to the control signal received from the adjustment unit 11. That is, the walking motion detection unit 12a can detect the walking motion by a plurality of arithmetic processes, and detects the walking motion by the arithmetic process specified by the control signal among these arithmetic processes.
 具体的には、歩行動作検出部12aは、計測部2が出力する加速度データの経時変化のパターンと、歩行動作が行われているときに生じる加速度データの経時変化のパターンとを比較することによって、歩行動作が行われていることを特定する。また、この加速度データの経時変化のパターンは、一定の周期及び振幅で加速度が変化するパターンであり、この振幅から歩行速度を算出する技術が知られている(例えば特許文献3等)。このため、歩行動作検出部12aは、上記パターンの振幅を特定し、特定した振幅を歩幅推定部12bに通知する。なお、歩行動作の検出方法、移動方位の検出方法、及び移動距離の算出方法は、上記の例に限られない。 Specifically, the walking motion detection unit 12a compares the pattern of change with time of the acceleration data output from the measurement unit 2 with the pattern of change with time of the acceleration data generated when the walking motion is performed. Identifies that a walking action is taking place. In addition, the pattern of change with time of the acceleration data is a pattern in which the acceleration changes with a constant period and amplitude, and a technique for calculating the walking speed from this amplitude is known (for example, Patent Document 3). For this reason, the walking motion detection unit 12a specifies the amplitude of the pattern and notifies the stride estimation unit 12b of the specified amplitude. Note that the walking motion detection method, the movement direction detection method, and the movement distance calculation method are not limited to the above examples.
 歩幅推定部12bは、調整部11から受信した制御信号に応じた演算処理により、歩行動作検出部12aが出力する振幅から歩行速度を算出する。そして、算出した歩行速度に経過時間を乗じて歩幅(その経過時間に歩いた距離)を算出する。 The stride length estimation unit 12b calculates a walking speed from the amplitude output by the walking motion detection unit 12a by a calculation process according to the control signal received from the adjustment unit 11. And the stride (distance walked at the elapsed time) is calculated by multiplying the calculated walking speed by the elapsed time.
 ここで、加速度データや角速度データ等の計測部2が出力する計測データは、その信号強度が保持状態に応じて増減することが経験的に知られている。なお、信号強度は、例えば計測データを時系列にプロットすることによって描かれる波形(サインカーブ等)における振幅として表すこともできる。そして、特許文献1では、このような信号強度が所定の閾値を超えているか否かによって、歩行動作が行われているか否かを判定することが記載されている。 Here, it is empirically known that the measurement data output from the measurement unit 2 such as acceleration data and angular velocity data has its signal intensity increased or decreased depending on the holding state. The signal intensity can also be expressed as an amplitude in a waveform (sine curve or the like) drawn by plotting measurement data in time series, for example. Patent Document 1 describes that whether or not a walking motion is performed is determined based on whether or not such signal intensity exceeds a predetermined threshold.
 このため、歩行動作検出部12aに送信する制御信号は、保持状態に応じた閾値で歩行動作を検出させるものとしてもよい。つまり、信号強度が弱い保持状態には、小さい閾値で歩行動作を検出させる制御信号を対応付け、信号強度が強い保持状態には、大きい閾値で歩行動作を検出させる制御信号を対応付けることによって、保持状態が信号強度に与える影響をキャンセルして、歩行動作を確実に検出することが可能になる。また、歩行動作検出部12aに送信する制御信号としては、例えば、保持状態に応じた感度(スケールファクタ)で歩行動作を検出させるものであってもよい。この構成によっても、保持状態が信号強度に与える影響をキャンセルして、歩行動作を確実に検出することが可能になる。 For this reason, the control signal transmitted to the walking motion detector 12a may detect the walking motion with a threshold corresponding to the holding state. In other words, a holding signal with a low signal strength is associated with a control signal that detects a walking motion with a small threshold, and a holding signal with a high signal strength is associated with a control signal that detects a walking motion with a large threshold. By canceling the influence of the state on the signal intensity, it is possible to reliably detect the walking motion. Moreover, as a control signal transmitted to the walking motion detection unit 12a, for example, a walking motion may be detected with a sensitivity (scale factor) corresponding to the holding state. Also with this configuration, it is possible to cancel the influence of the holding state on the signal intensity and reliably detect the walking motion.
 そして、歩幅推定部12bに送信する制御信号としては、保持状態に応じた感度(スケールファクタ)で計測データを振幅に変換させる信号等が想定される。これにより、保持状態の影響で、出力される計測データの値が変化したときにも、正確な歩行速度を算出することができる。 And as a control signal transmitted to the stride length estimation unit 12b, a signal or the like for converting measurement data into amplitude with a sensitivity (scale factor) according to the holding state is assumed. Thereby, even when the value of the measurement data to be output changes due to the influence of the holding state, it is possible to calculate an accurate walking speed.
 移動方位検出部12cは、計測データを用いて歩行者が移動している方位を検出する。なお、移動方位の検出には、公知の手法を適用することもでき、例えば加速度データと角速度データから検出することができる。 The moving direction detection unit 12c detects the direction in which the pedestrian is moving using the measurement data. Note that a known method can be applied to the detection of the moving direction, and for example, it can be detected from acceleration data and angular velocity data.
 移動ベクトル算出部12dは、歩幅推定部12bの出力する歩幅(歩行距離)に移動方位検出部12cが出力する方位を乗じて移動ベクトルを算出し、算出した移動ベクトルを位置決定部13に出力する。これにより、位置決定部13は、測位装置50を所持している歩行者の現在位置を特定することができる。 The movement vector calculation unit 12d calculates a movement vector by multiplying the stride (walking distance) output from the step estimation unit 12b by the direction output from the movement direction detection unit 12c, and outputs the calculated movement vector to the position determination unit 13. . Thereby, the position determination part 13 can pinpoint the present position of the pedestrian who has the positioning apparatus 50. FIG.
 〔実施の形態2〕
 次に、本発明の他の実施形態について、図8~図17に基づいて説明する。本実施形態の測位装置は、移動量の推定精度が異なる2つの移動量推定部を有しており、保持姿勢推定部10の推定する姿勢に応じてこれらの移動量推定部を使い分ける点が主な特徴点である。なお、上記実施形態と同様の構成については同一の参照番号を付し、その説明を省略する。
[Embodiment 2]
Next, another embodiment of the present invention will be described with reference to FIGS. The positioning device of this embodiment has two movement amount estimation units with different estimation accuracy of the movement amount, and the main point is that these movement amount estimation units are selectively used according to the posture estimated by the holding posture estimation unit 10. It is a special feature point. In addition, about the structure similar to the said embodiment, the same reference number is attached | subjected and the description is abbreviate | omitted.
 〔測位装置の要部構成〕
 まず、本実施形態の測位装置の構成について、図8に基づいて説明する。図8は、測位装置(計算装置)60の要部構成を示すブロック図である。図示のように、測位装置60は、制御部3及び記憶部4を備えている。また、計測部として、加速度センサ2a、ジャイロセンサ2b、及び地磁気センサ2cを備えている。つまり、測位装置60では、加速度、角速度、及び地磁気を入力データとして移動ベクトルの推定を行う。
[Main components of positioning device]
First, the configuration of the positioning device of the present embodiment will be described with reference to FIG. FIG. 8 is a block diagram showing a main configuration of the positioning device (calculation device) 60. As illustrated, the positioning device 60 includes a control unit 3 and a storage unit 4. Moreover, the acceleration sensor 2a, the gyro sensor 2b, and the geomagnetic sensor 2c are provided as a measurement part. That is, the positioning device 60 estimates the movement vector using the acceleration, angular velocity, and geomagnetism as input data.
 さらに、測位装置60は、表示部5を備えている。表示部5は、制御部3の制御に従って画像を表示するデバイスである。ここでは、測位装置60は、推定した移動ベクトルを用いて、当該測位装置60を所持しているユーザの現在位置を地図上で表示する機能を有していることを想定している。このため、表示部5には、地図の画像やユーザの現在位置を示す情報等が表示される。 Furthermore, the positioning device 60 includes a display unit 5. The display unit 5 is a device that displays an image according to the control of the control unit 3. Here, it is assumed that the positioning device 60 has a function of displaying the current position of the user who owns the positioning device 60 on a map using the estimated movement vector. Therefore, the display unit 5 displays a map image, information indicating the current position of the user, and the like.
 制御部3は、保持状態推定部10、調整部11、位置決定部(パラメータ算出手段)13、及び表示制御部18を含む構成である。また、移動量推定部として、高精度移動量推定部16及び簡易移動量推定部(簡易パラメータ算出手段)17を備えている。 The control unit 3 includes a holding state estimation unit 10, an adjustment unit 11, a position determination unit (parameter calculation means) 13, and a display control unit 18. In addition, a high-precision movement amount estimation unit 16 and a simple movement amount estimation unit (simple parameter calculation means) 17 are provided as the movement amount estimation unit.
 保持状態推定部10は、計測部が出力する計測データを用いて、測位装置60の保持状態を推定し、推定した保持状態を示す状態データを生成して調整部11に出力する。また、保持状態推定部10は、入力された計測データが、予め想定した保持状態の何れにも該当しない場合に、測位装置60が想定外状態であることを示す状態データを出力する。 The holding state estimation unit 10 estimates the holding state of the positioning device 60 using the measurement data output from the measurement unit, generates state data indicating the estimated holding state, and outputs the state data to the adjustment unit 11. The holding state estimation unit 10 outputs state data indicating that the positioning device 60 is in an unexpected state when the input measurement data does not correspond to any of the holding states assumed in advance.
 なお、保持状態は、上記の例に限られず、例えばAdaBoost等の機械学習の枠組みを用いて識別可能な状態であれば容易に適用できる。また、必ずしも機械学習の枠組みを用いる必要はなく、計測データに基づいて識別可能な保持状態であればよい。ただし、保持状態を追加・変更する場合には、その保持状態に応じた最適な移動ベクトルが推定されるように、調整部11、高精度移動量推定部16、及び簡易移動量推定部を構成する必要がある。 Note that the holding state is not limited to the above example, and can be easily applied as long as it can be identified using a machine learning framework such as AdaBoost. Further, it is not always necessary to use a machine learning framework, and any holding state that can be identified based on measurement data may be used. However, when adding / changing the holding state, the adjusting unit 11, the high-precision moving amount estimating unit 16, and the simple moving amount estimating unit are configured so that an optimal movement vector according to the holding state is estimated. There is a need to.
 調整部11は、移動体の運動状態を示すパラメータが、保持状態推定部10の出力する状態データに応じた演算処理で算出されるように、移動量推定部12を制御する。具体的には、調整部11は、記憶部4の信号特定テーブル20を用いて状態データに対応する制御信号を特定し、特定した制御信号を高精度移動量推定部16及び簡易移動量推定部17に出力することによって上記の制御を行う。 The adjustment unit 11 controls the movement amount estimation unit 12 so that a parameter indicating the motion state of the moving body is calculated by a calculation process according to the state data output from the holding state estimation unit 10. Specifically, the adjustment unit 11 specifies a control signal corresponding to the state data using the signal specification table 20 of the storage unit 4, and uses the specified control signal for the high-precision movement amount estimation unit 16 and the simple movement amount estimation unit. The above control is performed by outputting to 17.
 高精度移動量推定部16は、図1の移動量推定部12に相当する構成であり、調整部11が出力する制御信号に基づいて、計測データから移動ベクトルを推定する。より詳細には、高精度移動量推定部16は、歩行者の移動ベクトルを推定する。 The high-accuracy movement amount estimation unit 16 has a configuration corresponding to the movement amount estimation unit 12 in FIG. 1 and estimates a movement vector from measurement data based on a control signal output from the adjustment unit 11. More specifically, the high-precision movement amount estimation unit 16 estimates a pedestrian movement vector.
 ここで、高精度移動量推定部16のより詳細な構成を図9に基づいて説明する。図9は、高精度移動量推定部16の要部構成を示すブロック図である。高精度移動量推定部16は、図示のように、歩行動作検出部(パラメータ算出手段)16a、歩幅推定部(パラメータ算出手段)16b、移動方位検出部(パラメータ算出手段)16c、及び移動ベクトル算出部(パラメータ算出手段)16dを備えている。これらは、図7の歩行動作検出部12a、歩幅推定部12b、移動方位検出部12c、及び移動ベクトル算出部12dと同様の機能を有するものである。 Here, a more detailed configuration of the high-precision movement amount estimation unit 16 will be described with reference to FIG. FIG. 9 is a block diagram showing a main configuration of the high-precision movement amount estimation unit 16. As shown in the figure, the high-precision movement amount estimation unit 16 includes a walking motion detection unit (parameter calculation unit) 16a, a stride estimation unit (parameter calculation unit) 16b, a movement direction detection unit (parameter calculation unit) 16c, and a movement vector calculation. Unit (parameter calculation means) 16d. These have the same functions as the walking motion detection unit 12a, the stride estimation unit 12b, the movement direction detection unit 12c, and the movement vector calculation unit 12d in FIG.
 具体的には、歩行動作検出部16aは、加速度センサ2aが出力する3軸加速度データと、ジャイロセンサ2bが出力する3軸角速度データとを用いて、調整部11から受信した制御信号に応じた演算処理を行う。これにより、歩行動作検出部16aは、歩行動作を検出すると共に、振幅を算出して歩幅推定部16bに出力する。 Specifically, the walking motion detection unit 16a uses the triaxial acceleration data output from the acceleration sensor 2a and the triaxial angular velocity data output from the gyro sensor 2b in accordance with the control signal received from the adjustment unit 11. Perform arithmetic processing. Thereby, the walking motion detection unit 16a detects the walking motion, calculates the amplitude, and outputs the amplitude to the stride estimation unit 16b.
 歩幅推定部16bは、調整部11から受信した制御信号に応じた演算処理によって、歩行動作検出部16aが出力する振幅から歩行速度を算出する。そして、算出した歩行速度から歩幅(移動距離)を算出し、移動ベクトル算出部16dに出力する。 The stride length estimation unit 16b calculates the walking speed from the amplitude output by the walking motion detection unit 16a by a calculation process according to the control signal received from the adjustment unit 11. Then, the stride (movement distance) is calculated from the calculated walking speed, and is output to the movement vector calculation unit 16d.
 移動方位検出部16cは、ジャイロセンサ2bが出力する3軸角速度データと、地磁気センサ2cが出力する3軸地磁気データとを用いて、調整部11から受信した制御信号に応じた演算処理を行い、測位装置60の移動方位を特定する。このように、移動方位の検出についても、調整部11から受信した制御信号に応じた演算処理で行うようにしてもよい。例えば、出力される計測データの信頼性が低いと考えられる保持状態において計測部が出力した計測データの寄与を、それ以外の保持状態において計測部が出力した計測データよりも小さくするか、あるいは除いた演算処理によって方位を特定してもよい。 The moving direction detection unit 16c performs arithmetic processing according to the control signal received from the adjustment unit 11, using the triaxial angular velocity data output from the gyro sensor 2b and the triaxial geomagnetic data output from the geomagnetic sensor 2c. The moving direction of the positioning device 60 is specified. Thus, the detection of the moving direction may also be performed by a calculation process according to the control signal received from the adjustment unit 11. For example, the contribution of the measurement data output by the measurement unit in the holding state where the reliability of the output measurement data is considered to be low is reduced or excluded from the measurement data output by the measurement unit in the other holding state The azimuth may be specified by the arithmetic processing.
 移動ベクトル算出部16dは、歩幅推定部16bの出力する歩幅(歩行距離)に移動方位検出部16cが出力する方位を乗じて移動ベクトル(移動ベクトル(高精度)と呼ぶ)を算出し、算出した移動ベクトル(高精度)を位置決定部13に出力する。 The movement vector calculation unit 16d calculates a movement vector (referred to as a movement vector (high accuracy)) by multiplying the stride (walking distance) output from the stride estimation unit 16b by the direction output from the movement direction detection unit 16c. The movement vector (high accuracy) is output to the position determination unit 13.
 簡易移動量推定部17は、高精度移動量推定部16と同様に、調整部11が送信する制御信号に応じた演算処理を行うことによって、計測部が出力する計測データから移動ベクトル(移動ベクトル(簡易)と呼ぶ)を算出し、算出した移動ベクトル(簡易)を位置決定部13に出力する。 Similar to the high-precision movement amount estimation unit 16, the simple movement amount estimation unit 17 performs a calculation process according to the control signal transmitted by the adjustment unit 11, thereby moving the movement vector (movement vector) from the measurement data output by the measurement unit. (Referred to as “simple”) is calculated, and the calculated movement vector (simple) is output to the position determining unit 13.
 ただし、簡易移動量推定部17は、演算処理に使用するデータ量が高精度移動量推定部16よりも少ない点で高精度移動量推定部16と異なっている。具体的には、簡易移動量推定部17は、高精度移動量推定部16が3軸加速度データ、3軸角速度データ、及び3軸地磁気データの全てを用いて演算処理を行うのに対し、3軸加速度データと3軸地磁気データとを用い、3軸角速度データは用いない。 However, the simple movement amount estimation unit 17 is different from the high accuracy movement amount estimation unit 16 in that the amount of data used for the arithmetic processing is smaller than that of the high accuracy movement amount estimation unit 16. Specifically, the simple movement amount estimation unit 17 performs calculation processing using all of the three-axis acceleration data, the three-axis angular velocity data, and the three-axis geomagnetic data, while the high-precision movement amount estimation unit 16 performs the calculation process. Axial acceleration data and triaxial geomagnetic data are used, and triaxial angular velocity data is not used.
 想定外の保持状態となっている場合には、高精度移動量推定部16で想定していないような値の計測データが入力され得るので、高精度移動量推定部16の出力する移動ベクトル(高精度)よりも、少ないデータ量で演算処理を行う簡易移動量推定部17の出力する移動ベクトル(簡易)の方が妥当な値となることがある。このため、想定外の保持状態となっている場合等に、簡易移動量推定部17による演算処理を行うことで、移動ベクトルの推定精度を高めることができる。 In the case of an unexpected holding state, measurement data having a value that is not assumed by the high-precision movement amount estimation unit 16 can be input, so that the movement vector ( The movement vector (simple) output from the simple movement amount estimation unit 17 that performs arithmetic processing with a small amount of data may be more appropriate than (high accuracy). For this reason, when it is in an unexpected holding state or the like, the calculation accuracy of the movement vector can be increased by performing the calculation process by the simple movement amount estimation unit 17.
 ここで、簡易移動量推定部17のより詳細な構成を図10に基づいて説明する。図10は、簡易移動量推定部17の要部構成を示すブロック図である。図示のように、簡易移動量推定部17は、歩行動作検出部(簡易パラメータ算出手段)17a、歩幅推定部(簡易パラメータ算出手段)17b、移動方位検出部(簡易パラメータ算出手段)17c、及び移動ベクトル算出部(簡易パラメータ算出手段)17dを備えている。これらは、高精度移動量推定部16の歩行動作検出部16a、歩幅推定部16b、移動方位検出部16c、及び移動ベクトル算出部16dと同様の機能を有するものである。 Here, a more detailed configuration of the simple movement amount estimation unit 17 will be described with reference to FIG. FIG. 10 is a block diagram illustrating a main configuration of the simple movement amount estimation unit 17. As illustrated, the simple movement amount estimation unit 17 includes a walking motion detection unit (simple parameter calculation unit) 17a, a stride estimation unit (simple parameter calculation unit) 17b, a movement direction detection unit (simple parameter calculation unit) 17c, and a movement. A vector calculation unit (simple parameter calculation means) 17d is provided. These have the same functions as the walking motion detection unit 16a, the stride length estimation unit 16b, the movement direction detection unit 16c, and the movement vector calculation unit 16d of the high-precision movement amount estimation unit 16.
 具体的には、歩行動作検出部17aは、加速度センサ2aが出力する3軸加速度データを用いて、調整部11から受信した制御信号に応じた演算処理を行う。これにより、歩行動作検出部17aは、歩行動作を検出すると共に、振幅を算出して歩幅推定部17bに出力する。すなわち、歩行動作検出部17aは、演算処理に3軸角速度データを用いない点が歩行動作検出部16aと異なっている。 Specifically, the walking motion detection unit 17a performs arithmetic processing according to the control signal received from the adjustment unit 11 using the triaxial acceleration data output from the acceleration sensor 2a. Thereby, the walking motion detection unit 17a detects the walking motion, calculates the amplitude, and outputs the amplitude to the stride estimation unit 17b. That is, the walking motion detection unit 17a is different from the walking motion detection unit 16a in that the triaxial angular velocity data is not used for the calculation process.
 歩幅推定部17bは、調整部11から受信した制御信号に応じた演算処理によって、歩行動作検出部17aが出力する振幅から歩行速度を算出する。そして、算出した歩行速度から歩幅(移動距離)を算出し、移動ベクトル算出部17dに出力する。 The stride length estimation unit 17b calculates a walking speed from the amplitude output by the walking motion detection unit 17a by a calculation process according to the control signal received from the adjustment unit 11. Then, the stride (movement distance) is calculated from the calculated walking speed, and is output to the movement vector calculation unit 17d.
 移動方位検出部17cは、調整部11から受信した制御信号に応じた演算処理を行い、地磁気センサ2cが出力する3軸地磁気データから測位装置60の移動方位を特定する。すなわち、移動方位検出部17cは、3軸角速度データを用いずに方位を特定する点が移動方位検出部16cと異なっている。 The moving azimuth detecting unit 17c performs arithmetic processing according to the control signal received from the adjusting unit 11, and specifies the moving azimuth of the positioning device 60 from the three-axis geomagnetic data output from the geomagnetic sensor 2c. That is, the moving direction detection unit 17c is different from the moving direction detection unit 16c in that the direction is specified without using the triaxial angular velocity data.
 移動ベクトル算出部17dは、歩幅推定部17bの出力する歩幅(歩行距離)に移動方位検出部17cが出力する方位を乗じて移動ベクトル(簡易)を算出し、算出した移動ベクトル(簡易)を位置決定部13に出力する。 The movement vector calculation unit 17d calculates a movement vector (simple) by multiplying the stride (walking distance) output by the stride estimation unit 17b by the azimuth output by the movement azimuth detection unit 17c, and sets the calculated movement vector (simple) as the position. The data is output to the determination unit 13.
 なお、簡易移動量推定部17は、演算処理に使用するデータ量が高精度移動量推定部16よりも少ないものであればよく、上記の例に限られない。例えば、高精度移動量推定部16が3軸のデータを使用する場合に、2軸または1軸のデータのみを使用するものであってもよい。また、例えば、計測部からデータを取得する周期を高精度移動量推定部16よりも長くする等により、同種のデータを用いつつ使用データ量を減らしてもよい。 The simple movement amount estimation unit 17 is not limited to the above example as long as the amount of data used for the arithmetic processing is smaller than that of the high-precision movement amount estimation unit 16. For example, when the high-accuracy movement amount estimation unit 16 uses triaxial data, only the biaxial or uniaxial data may be used. For example, the amount of data used may be reduced while using the same kind of data, for example, by making the period for acquiring data from the measurement unit longer than that of the high-precision movement amount estimation unit 16.
 測位装置60では、高精度移動量推定部16が出力する移動ベクトル(高精度)と、簡易移動量推定部17が出力する移動ベクトル(簡易)との両方が位置決定部13に入力される。そして、位置決定部13は、調整部(切替手段)11が送信する制御信号に基づき、移動ベクトル(高精度)を用いるか、移動ベクトル(簡易)を用いるか、これら両方を用いるかを決定し、この決定に基づいて位置データを算出する。 In the positioning device 60, both the movement vector (high accuracy) output from the high-accuracy movement amount estimation unit 16 and the movement vector (simple) output from the simple movement amount estimation unit 17 are input to the position determination unit 13. Then, the position determination unit 13 determines whether to use the movement vector (high accuracy), the movement vector (simple), or both based on the control signal transmitted by the adjustment unit (switching unit) 11. Based on this determination, position data is calculated.
 なお、移動ベクトル(高精度)と移動ベクトル(簡易)の両方を用いる場合には、移動ベクトル(高精度)と移動ベクトル(簡易)の単純平均や重み付け平均等によって移動ベクトルを算出する。高精度移動量推定部16による演算処理を行ったとしても、余り信頼性の高い演算結果が得られないことが想定される保持姿勢では、このように、移動ベクトル(簡易)に、移動ベクトル(高精度)の部分的な要素を加味することで、移動ベクトルの推定精度を高めることができる。 When both the movement vector (high accuracy) and the movement vector (simple) are used, the movement vector is calculated by a simple average or a weighted average of the movement vector (high accuracy) and the movement vector (simple). Even if the calculation process by the high-accuracy movement amount estimation unit 16 is performed, in the holding posture where it is assumed that a calculation result with high reliability cannot be obtained, the movement vector (simple) is replaced with the movement vector (simple). By taking into account partial elements of (high accuracy), the estimation accuracy of the movement vector can be increased.
 調整部11は、保持姿勢推定部10の出力する姿勢データが、予め想定した保持姿勢の何れかを示している場合には、移動ベクトル(高精度)または移動ベクトル(高精度)と移動ベクトル(簡易)の両方を出力させる制御信号を送信する。一方、保持姿勢推定部10の出力する姿勢データが、予め想定した保持姿勢の何れにも該当しない場合には、移動ベクトル(簡易)を出力させる制御信号を送信する。そして、位置決定部13は、調整部11からの制御信号に応じた移動ベクトルを用いて現在位置を算出する。 When the posture data output from the holding posture estimation unit 10 indicates any of the holding postures assumed in advance, the adjustment unit 11 moves the movement vector (high accuracy) or the movement vector (high accuracy) and the movement vector ( A simple control signal is output. On the other hand, if the posture data output by the holding posture estimation unit 10 does not correspond to any of the holding postures assumed in advance, a control signal for outputting a movement vector (simple) is transmitted. Then, the position determination unit 13 calculates the current position using a movement vector corresponding to the control signal from the adjustment unit 11.
 表示制御部18は、表示部5に画像を表示させる制御を行う。具体的には、表示制御部18は、記憶部4に格納されている地図データ21を基に、表示部5に地図の画像を表示させる。また、表示制御部18は、表示させた地図上において、位置決定部13から受信した位置データが示す位置に、ユーザが存在していることを示すマークを表示させる。 The display control unit 18 performs control to display an image on the display unit 5. Specifically, the display control unit 18 displays a map image on the display unit 5 based on the map data 21 stored in the storage unit 4. Further, the display control unit 18 displays a mark indicating that the user exists at the position indicated by the position data received from the position determination unit 13 on the displayed map.
 〔遷移状態を検出する例〕
 ここで、例えば、測位装置を持ち替える動作を行った場合には、この動作によって生じた加速度等が計測部2によって検出される。このように、測位装置を保持しているユーザが、測位装置の持ち替えなどを行ったときに検出される計測データからは、ユーザの移動方位や移動距離が正確に算出されないおそれがある。
[Example of detecting transition status]
Here, for example, when the operation of changing the positioning device is performed, the acceleration or the like generated by this operation is detected by the measurement unit 2. Thus, there is a possibility that the moving direction and moving distance of the user may not be accurately calculated from the measurement data detected when the user holding the positioning device changes the positioning device.
 そこで、ここでは、保持状態がある状態から他の状態に変化するまでの状態である遷移状態の推定を行う例を図11に基づいて説明する。図11は、遷移状態の推定を行う測位装置(計算装置)70の要部構成を示すブロック図である。なお、図8の測位装置60と同様の構成については、同一の参照番号を付し、その説明を省略する。 Therefore, here, an example in which a transition state that is a state from a state in which a holding state is changed to another state is estimated will be described with reference to FIG. FIG. 11 is a block diagram illustrating a main configuration of a positioning device (calculation device) 70 that estimates a transition state. In addition, about the structure similar to the positioning apparatus 60 of FIG. 8, the same reference number is attached | subjected and the description is abbreviate | omitted.
 図示のように、測位装置70は、保持状態推定部10から計測部に駆動制御信号が入力される点、及び、計測部から簡易移動量推定部17に入力される計測データが、2軸角速度データ、3軸加速度データ、及び3軸地磁気データとなっている点が、測位装置60と異なっている。 As shown in the figure, the positioning device 70 is configured such that the drive control signal is input from the holding state estimation unit 10 to the measurement unit, and the measurement data input from the measurement unit to the simple movement amount estimation unit 17 is a biaxial angular velocity. It differs from the positioning device 60 in that it is data, triaxial acceleration data, and triaxial geomagnetic data.
 まず、保持状態推定部10の詳細を図12に基づいて説明する。図12は、保持状態推定部10の要部構成を示すブロック図である。図示のように、保持状態推定部10は、保持状態識別部10a、遷移状態検出部10b、及び保持状態判定部10cを備えている。 First, details of the holding state estimation unit 10 will be described with reference to FIG. FIG. 12 is a block diagram illustrating a main configuration of the holding state estimation unit 10. As shown in the figure, the holding state estimation unit 10 includes a holding state identification unit 10a, a transition state detection unit 10b, and a holding state determination unit 10c.
 保持状態識別部10aは、計測部が出力する計測データから測位装置70の保持状態を識別し、識別した保持状態を示す状態識別データを保持状態判定部10cに出力する。具体的には、保持状態識別部10aは、3軸加速度データ、3軸角速度データ、及び3軸地磁気データを用いて、予め想定している保持状態の何れに該当するか、または何れにも該当しないかを識別して、その識別結果を示す状態識別データを出力する。 The holding state identifying unit 10a identifies the holding state of the positioning device 70 from the measurement data output by the measuring unit, and outputs state identification data indicating the identified holding state to the holding state determining unit 10c. Specifically, the holding state identification unit 10a corresponds to any one of the holding states assumed in advance using the triaxial acceleration data, the triaxial angular velocity data, and the triaxial geomagnetic data. State identification data indicating the identification result is output.
 遷移状態検出部10bは、遷移状態検出処理を行って、計測部が出力する計測データから測位装置70が遷移状態にあることを検出する。そして、遷移状態にあることを検出した場合には、その旨を保持状態判定部10cに出力する。なお、例えば、短時間で保持姿勢が大きく変化したことを検出したとき、または検出される保持姿勢が不安定となっていることを検出したときには、遷移状態であると推定されるので、このような状態を検出することによって、遷移状態を検出することができる。また、遷移時には検出される方位が急激に変化するので、方位の特定に用いる角速度データ及び地磁気データを用いて遷移状態を検出することも可能である。なお、遷移状態検出部10bが実行する遷移状態検出処理の詳細については後述する。 The transition state detection unit 10b performs a transition state detection process to detect that the positioning device 70 is in the transition state from the measurement data output by the measurement unit. And when it detects that it exists in a transition state, that is output to the holding | maintenance state determination part 10c. For example, when it is detected that the holding posture has changed significantly in a short time, or when it is detected that the detected holding posture is unstable, it is estimated that the state is a transition state. By detecting a simple state, a transition state can be detected. In addition, since the direction detected at the time of transition changes abruptly, it is possible to detect the transition state using the angular velocity data and the geomagnetic data used for specifying the direction. The details of the transition state detection process executed by the transition state detection unit 10b will be described later.
 保持状態判定部(測定制御手段)10cは、保持状態識別部10a及び遷移状態検出部10bの出力に基づいて測位装置70の保持状態を判定する。そして、判定した保持状態を示す状態データを生成して調整部11に出力する。 The holding state determination unit (measurement control means) 10c determines the holding state of the positioning device 70 based on the outputs of the holding state identification unit 10a and the transition state detection unit 10b. Then, state data indicating the determined holding state is generated and output to the adjustment unit 11.
 また、保持状態判定部10cは、遷移状態検出部10bが遷移状態である旨を出力したときには、計測部2に駆動制御信号を出力して、計測部2による一部のデータ計測を停止させると共に、計測データの出力先を高精度移動量推定部16から簡易移動量推定部17に切り替える。なお、保持状態判定部10cによる駆動制御は、上記の例に限られず、例えば計測部2の駆動周波数を下げること、言い換えれば計測データの出力頻度を下げることによって、簡易移動量推定部17が使用するデータ量を高精度移動量推定部16よりも少なくしてもよい。 In addition, when the transition state detection unit 10b outputs that the transition state detection unit 10b is in the transition state, the holding state determination unit 10c outputs a drive control signal to the measurement unit 2 and stops some data measurement by the measurement unit 2. The output destination of the measurement data is switched from the high-precision movement amount estimation unit 16 to the simple movement amount estimation unit 17. Note that the drive control by the holding state determination unit 10c is not limited to the above example, and is used by the simple movement amount estimation unit 17 by, for example, lowering the drive frequency of the measurement unit 2, in other words, lowering the output frequency of measurement data. The amount of data to be performed may be smaller than that of the high-precision movement amount estimation unit 16.
 つまり、測位装置70は、遷移状態では高精度移動量推定部16による移動ベクトル算出は行わず、計測部2が出力するデータ量を減らして、簡易移動量推定部17による移動ベクトル算出のみを行う。これにより、計測部2における消費電力を低減することができる。 That is, the positioning device 70 does not perform the movement vector calculation by the high-precision movement amount estimation unit 16 in the transition state, and only performs the movement vector calculation by the simple movement amount estimation unit 17 while reducing the data amount output by the measurement unit 2. . Thereby, the power consumption in the measurement part 2 can be reduced.
 ここでは、図11に示すように、高精度移動量推定部16には、3軸加速度データと、3軸角速度データと、3軸地磁気データとが入力されるのに対し、簡易移動量推定部17には、3軸加速度データと、2軸角速度データと、3軸地磁気データとが入力されることを想定している。 Here, as shown in FIG. 11, the high-accuracy movement amount estimation unit 16 receives triaxial acceleration data, triaxial angular velocity data, and triaxial geomagnetic data, whereas the simple movement amount estimation unit. 17, it is assumed that triaxial acceleration data, biaxial angular velocity data, and triaxial geomagnetic data are input.
 つまり、保持状態判定部10cは、遷移状態検出部10bが遷移状態である旨を出力したときには、計測部2に駆動制御信号を出力して、ジャイロセンサ2bの測定する角速度を3軸から2軸に切り替える。そして、移動ベクトルを算出するブロックを高精度移動量推定部16から簡易移動量推定部17に切り替える。 That is, when the transition state detection unit 10b outputs that the transition state detection unit 10b is in the transition state, the holding state determination unit 10c outputs a drive control signal to the measurement unit 2 to change the angular velocity measured by the gyro sensor 2b from three axes to two axes. Switch to. Then, the block for calculating the movement vector is switched from the high-precision movement amount estimation unit 16 to the simple movement amount estimation unit 17.
 また、保持状態判定部10cは、保持状態識別部10aから、予め想定した保持姿勢の何れにも該当しないことを示す状態識別データを受信した場合にも、遷移状態のときと同様の処理を行う。これは、予め想定した保持姿勢の何れにも該当しない場合には、高精度移動量推定部16を用いたとしても、演算精度の向上が期待できないためである。 Also, the holding state determination unit 10c performs the same processing as that in the transition state even when the state identification data indicating that it does not correspond to any of the holding postures assumed in advance is received from the holding state identification unit 10a. . This is because when the holding posture assumed in advance does not correspond, even if the high-accuracy movement amount estimation unit 16 is used, improvement in calculation accuracy cannot be expected.
 測位装置70の簡易移動量推定部17について図13に基づいて説明する。図13は、簡易移動量推定部17の要部構成を示すブロック図である。図13に示すように、歩行動作検出部17aが、3軸加速度データと2軸角速度データから振幅を算出し、歩幅推定部17bが、この振幅から歩幅を算出する。また、移動方位検出部17cが、3軸地磁気データと2軸角速度データから方位を特定し、移動ベクトル算出部17dが、歩幅と方位から移動ベクトル(簡易)を算出する。このように、簡易移動量推定部17は、図12に示す高精度移動量推定部16と比べて、使用する角速度データが少なく(3軸から2軸に)なっている。 The simple movement amount estimation unit 17 of the positioning device 70 will be described with reference to FIG. FIG. 13 is a block diagram illustrating a main configuration of the simple movement amount estimation unit 17. As shown in FIG. 13, the walking motion detector 17a calculates the amplitude from the triaxial acceleration data and the biaxial angular velocity data, and the stride estimation unit 17b calculates the stride from this amplitude. Further, the moving direction detection unit 17c specifies the direction from the triaxial geomagnetic data and the biaxial angular velocity data, and the movement vector calculation unit 17d calculates a movement vector (simple) from the stride and the direction. Thus, the simple movement amount estimation unit 17 uses less angular velocity data (from three axes to two axes) than the high-precision movement amount estimation unit 16 shown in FIG.
 なお、歩行動作検出部17a、歩幅推定部17b、移動方位検出部17c、及び移動ベクトル算出部17dは、調整部11が出力する、遷移状態に対応する制御信号に応じた演算処理によって、振幅、歩幅、方位、及び移動ベクトル(簡易)の算出を行う。 Note that the walking motion detection unit 17a, the stride length estimation unit 17b, the movement direction detection unit 17c, and the movement vector calculation unit 17d are output by the adjustment unit 11 according to a calculation process corresponding to the control signal corresponding to the transition state, The stride, azimuth, and movement vector (simple) are calculated.
 より詳細には、調整部11は、保持状態判定部10cが遷移状態と判定している期間、または予め想定した保持姿勢の何れにも該当しないと判定している期間には、方位及び位置が変化しないように、または変化が上記以外の期間と比べて小さくなるように制御する。これにより、遷移状態または想定外の保持姿勢となっている期間に出力される計測データによって、現実の位置から大きく外れた位置を現在地と推定してしまうことを防ぐことができる。 More specifically, in the period when the holding state determination unit 10c determines that the holding state determination unit 10c is in the transition state, or the period when the adjustment unit 11 determines that it does not correspond to any of the holding postures assumed in advance, the orientation and position are changed. Control is performed so as not to change, or to make the change smaller than periods other than those described above. Accordingly, it is possible to prevent the current position from being estimated to be a position greatly deviated from the actual position by the measurement data output in the transition state or the period of the unexpected holding posture.
 例えば、歩行動作検出部17aは、時系列の加速度データを用いて歩行動作を検出する。このため、調整部11は、歩行動作検出部17aに制御信号を送信して、遷移状態または予め想定した保持姿勢の何れにも該当しない状態である期間に計測部が出力した加速度データの寄与を、それ以外の期間に計測部が出力した加速度データよりも小さくした演算処理によって歩行動作を検出させる。無論、遷移状態または予め想定した保持姿勢の何れにも該当しない状態である期間に計測部が出力した加速度データの寄与を完全に取り除いてもよい。 For example, the walking motion detection unit 17a detects a walking motion using time-series acceleration data. For this reason, the adjustment unit 11 transmits a control signal to the walking motion detection unit 17a, and contributes the acceleration data output by the measurement unit during a period that does not correspond to either the transition state or the holding posture assumed in advance. The walking motion is detected by a calculation process that is smaller than the acceleration data output by the measurement unit during other periods. Of course, the contribution of the acceleration data output by the measurement unit during a period that does not correspond to any of the transition state or the presumed holding posture may be completely removed.
 また、調整部11は、歩幅推定部17bについても同様に、遷移状態または予め想定した保持姿勢の何れにも該当しない状態である期間に計測部が出力した加速度データの寄与を、それ以外の期間に計測部が出力した加速度データよりも小さくするか、あるいは除いた演算処理によって歩幅を検出させてもよい。 Similarly, the adjustment unit 11 also contributes the acceleration data output by the measurement unit during a period other than the transition state or the presumed holding posture to the stride length estimation unit 17b. The step length may be detected by a calculation process that is smaller than the acceleration data output by the measuring unit or is excluded.
 さらに、調整部11は、移動方位検出部17cについても同様に、遷移状態または予め想定した保持姿勢の何れにも該当しない状態である期間に計測部が出力した計測データ(角速度データ及び地磁気データ)の寄与を、それ以外の期間に計測部が出力した加速度データよりも小さくするか、あるいは除いた演算処理によって方位を特定させてもよい。 Further, the adjustment unit 11 similarly applies the measurement data (angular velocity data and geomagnetic data) output by the measurement unit during the period in which the moving direction detection unit 17c does not correspond to either the transition state or the presumed holding posture. May be made smaller than the acceleration data output by the measurement unit during other periods, or the orientation may be specified by a calculation process that is excluded.
 なお、方位誤差は、測位誤差の影響が特に大きいので、移動方位のみを調整部11の制御対象としてもよい。つまり、移動方位を誤って推定した場合には、現実の位置とかけ離れた位置を推定してしまうので、遷移状態等には少なくとも移動方位を変化させないように制御することが好ましい。 Note that since the azimuth error is particularly affected by the positioning error, only the moving azimuth may be controlled by the adjustment unit 11. That is, if the moving direction is estimated incorrectly, a position that is far from the actual position is estimated. Therefore, it is preferable to perform control so that at least the moving direction is not changed in the transition state or the like.
 また、遷移状態等における移動方位及び現在位置については、移動方位及び位置を求めようとする時刻より、前または後の時刻における移動方位及び位置を参照して調整することが望ましい。無論、前後の時刻における移動方位及び位置を参照して調整することがなお好ましい。 Also, it is desirable to adjust the moving direction and the current position in the transition state or the like with reference to the moving direction and the position at the time before or after the time at which the moving direction and the position are to be obtained. Of course, it is still more preferable to adjust with reference to the moving azimuth | direction and position in the time around.
 すなわち、移動方位検出部17cは、方位の変化履歴を記憶しておき、この変化履歴から最も確からしい方位を現在の方位として特定してもよい。また、位置決定部13も同様に、位置の変化履歴を記憶しておき、この変化履歴から最も確からしい位置を現在の位置として特定してもよい。これにより、姿勢識別情報(保持状態を識別するために用いる各種データ)のノイズ成分を低減して、安定した姿勢識別が可能になる。 That is, the moving direction detection unit 17c may store a change history of the direction, and specify the most likely direction from the change history as the current direction. Similarly, the position determination unit 13 may store a position change history, and specify the most likely position as the current position from the change history. As a result, the noise component of the posture identification information (various data used for identifying the holding state) is reduced, and stable posture identification becomes possible.
 〔遷移状態検出処理の流れ〕
 続いて、遷移状態検出部10bが行う遷移状態検出処理の流れについて、図14に基づいて説明する。図14は、遷移状態検出処理の一例を示すフローチャートである。図示の処理では、遷移時には加速度が急激に変化することを利用して、3軸加速度データに基づいて、加速度が急激に変化するパターンを検出することによって、遷移状態であることを特定する。なお、遷移状態の特定に用いるデータは、計測部2が出力する計測データそのものでなくてもよい。例えば、計測データをローパスフィルタ等でフィルタリングしたデータを用いること等も当然可能である。
[Transition state detection process flow]
Next, the flow of the transition state detection process performed by the transition state detection unit 10b will be described based on FIG. FIG. 14 is a flowchart illustrating an example of the transition state detection process. In the illustrated process, a transition state is specified by detecting a pattern in which the acceleration changes abruptly based on the triaxial acceleration data using the fact that the acceleration changes abruptly at the time of transition. Note that the data used for specifying the transition state may not be the measurement data itself output by the measurement unit 2. For example, it is naturally possible to use data obtained by filtering measurement data with a low-pass filter or the like.
 まず、遷移状態検出部10bは、加速度センサ2aから3軸の加速度データを取得する(S10)。そして、遷移状態検出部10bは、1ステップ前の加速度との差分を各軸について算出する(S11)。つまり、遷移状態検出部10bは、一定時間毎に3軸の加速度データを取得してその値を記憶しておく。そして、新たに加速度データを取得したときには、その加速度データと、最後に記憶した加速度データとの差分を計算する。 First, the transition state detection unit 10b acquires triaxial acceleration data from the acceleration sensor 2a (S10). And the transition state detection part 10b calculates the difference with the acceleration of 1 step before about each axis | shaft (S11). That is, the transition state detection unit 10b acquires triaxial acceleration data at regular time intervals and stores the values. When acceleration data is newly acquired, the difference between the acceleration data and the last stored acceleration data is calculated.
 次に、遷移状態検出部10bは、S11で算出した差分を用いて、一定期間の差分平均値(dif_a_ave)を各軸について算出する(S12)。また、遷移状態検出部10bは、遷移状態であるか否かを判定するための閾値(DFTH)を設定する(S13)。 Next, the transition state detection unit 10b calculates a difference average value (dif_a_ave) for a certain period for each axis using the difference calculated in S11 (S12). Further, the transition state detection unit 10b sets a threshold value (DFTH) for determining whether or not the transition state is set (S13).
 閾値(DFTH)としては、予め定められた値を使用してもよい。しかしながら、遷移状態で検出される加速度の大きさは、そのときの歩行速度の大きさに比例するので、所定時間前から現在までの歩行速度または加速度に応じて閾値(DFTH)を設定することが好ましい。つまり、遷移状態検出部10bは、歩行速度または加速度に比例した閾値(DFTH)を設定する。 As the threshold value (DFTH), a predetermined value may be used. However, since the magnitude of the acceleration detected in the transition state is proportional to the magnitude of the walking speed at that time, it is possible to set a threshold (DFTH) according to the walking speed or acceleration from a predetermined time before to the present. preferable. That is, the transition state detection unit 10b sets a threshold value (DFTH) proportional to the walking speed or acceleration.
 なお、歩行速度が大きくなるほど、計測部2が出力する計測データの値が大きくなる。このため、上記の構成に代えて、計測データの値が大きくなるほど、大きな閾値を設定する構成を採用してもよい。また、設定する閾値は、計測データの値(例えば、3軸方向の値の平均値)に応じて連続的に変化させてもよいし、段階的に変化させてもよい。 In addition, the value of the measurement data output from the measurement unit 2 increases as the walking speed increases. For this reason, it may replace with said structure and may employ | adopt the structure which sets a big threshold value, so that the value of measurement data becomes large. Further, the threshold value to be set may be changed continuously according to the value of the measurement data (for example, the average value of the values in the three axis directions) or may be changed stepwise.
 続いて、遷移状態検出部10bは、S12で算出した差分平均値(dif_a_ave)が、S13で設定した閾値(DFTH)よりも小さいか否かを確認する(S14)。そして、遷移状態検出部10bは、差分平均値(dif_a_ave)が閾値(DFTH)よりも小さいと判断した場合(S14でYES)には、遷移状態でないと判断し(S15)、その旨を保持状態判定部10cに出力してS10の処理に戻る。 Subsequently, the transition state detection unit 10b checks whether or not the difference average value (dif_a_ave) calculated in S12 is smaller than the threshold value (DFTH) set in S13 (S14). When the transition state detection unit 10b determines that the difference average value (dif_a_ave) is smaller than the threshold value (DFTH) (YES in S14), the transition state detection unit 10b determines that it is not the transition state (S15), and holds that state. It outputs to the determination part 10c and returns to the process of S10.
 一方、遷移状態検出部10bは、差分平均値(dif_a_ave)が閾値(DFTH)以上であると判断した場合(S14でNO)には、遷移状態であると判断し(S15)、その旨を保持状態判定部10cに出力してS10の処理に戻る。 On the other hand, if the transition state detection unit 10b determines that the difference average value (dif_a_ave) is equal to or greater than the threshold value (DFTH) (NO in S14), the transition state detection unit 10b determines that the transition state is present (S15) and retains that effect. It outputs to the state determination part 10c, and returns to the process of S10.
 〔重力方位推定部を複数設けた例〕
 続いて、重力方位推定部を複数設けた例を図15に基づいて説明する。図15は、重力方位推定部を2つ備えた測位装置80の要部構成を示すブロック図である。なお、図8の測位装置60と同様の構成については、同一の参照番号を付し、その説明を省略する。
[Example of multiple gravity direction estimation units]
Next, an example in which a plurality of gravity direction estimation units are provided will be described with reference to FIG. FIG. 15 is a block diagram illustrating a main configuration of a positioning device 80 including two gravity direction estimation units. In addition, about the structure similar to the positioning apparatus 60 of FIG. 8, the same reference number is attached | subjected and the description is abbreviate | omitted.
 図示のように、測位装置80は、重力方位推定部として、高精度重力方位推定部15aと簡易重力方位推定部(簡易重力方位特定手段)15bとを備えている。 As shown in the figure, the positioning device 80 includes a high-precision gravity direction estimation unit 15a and a simple gravity direction estimation unit (simple gravity direction specifying means) 15b as gravity direction estimation units.
 高精度重力方位推定部15aは、図6の測位装置40が備える重力方位推定部15と同様の機能を有している。すなわち、高精度重力方位推定部15aは、加速度センサ2aが出力する3軸加速度データと、ジャイロセンサ2bが出力する3軸角速度データとを用いて重力方位ベクトルを算出する。なお、ここでは、高精度重力方位推定部15aが算出する重力方位ベクトルを重力方位ベクトル(高精度)と呼ぶ。また、高精度重力方位推定部15aは、算出した重力方位ベクトル(高精度)を保持状態推定部10及び高精度移動量推定部16に出力する。なお、重力方位ベクトル(高精度)は、簡易移動量推定部17にも出力してもよい。 The high precision gravity direction estimation unit 15a has the same function as the gravity direction estimation unit 15 provided in the positioning device 40 of FIG. That is, the high-precision gravity azimuth estimation unit 15a calculates the gravity azimuth vector using the triaxial acceleration data output from the acceleration sensor 2a and the triaxial angular velocity data output from the gyro sensor 2b. Here, the gravity direction vector calculated by the high-precision gravity direction estimation unit 15a is referred to as a gravity direction vector (high accuracy). Further, the high-precision gravity azimuth estimation unit 15 a outputs the calculated gravity azimuth vector (high accuracy) to the holding state estimation unit 10 and the high-precision movement amount estimation unit 16. The gravity direction vector (high accuracy) may also be output to the simple movement amount estimation unit 17.
 簡易重力方位推定部15bも、高精度重力方位推定部15aと同様に、加速度データと角速度データとを用いて重力方位ベクトルを算出するが、使用するデータ量が高精度重力方位推定部15aよりも少ない点で異なっている。図示の例では、簡易重力方位推定部15bは、2軸角速度データと3軸加速度データとを用いて重力方位ベクトルを算出している。なお、ここでは簡易重力方位推定部15bが算出する重力方位ベクトルを重力方位ベクトル(簡易)と呼ぶ。また、簡易重力方位推定部15bは、算出した重力方位ベクトル(簡易)を保持状態推定部10及び簡易移動量推定部17に出力する。なお、重力方位ベクトル(簡易)は、高精度移動量推定部16にも出力してもよい。 The simple gravity azimuth estimation unit 15b calculates the gravity azimuth vector using the acceleration data and the angular velocity data in the same manner as the high precision gravity azimuth estimation unit 15a, but the amount of data used is larger than that of the high precision gravity azimuth estimation unit 15a. There are few differences. In the illustrated example, the simple gravity direction estimation unit 15b calculates the gravity direction vector using the biaxial angular velocity data and the triaxial acceleration data. Here, the gravity direction vector calculated by the simple gravity direction estimation unit 15b is referred to as a gravity direction vector (simple). Further, the simple gravity direction estimation unit 15 b outputs the calculated gravity direction vector (simple) to the holding state estimation unit 10 and the simple movement amount estimation unit 17. Note that the gravity direction vector (simple) may also be output to the high-precision movement amount estimation unit 16.
 測位装置80の保持状態推定部10は、上記のようにして出力される重力方位ベクトル(高精度)または重力方位ベクトル(簡易)を用いて保持状態の推定を行う。保持状態によっては、高精度重力方位推定部15aで想定していないような値の計測データが入力されるので、高精度重力方位推定部15aの出力する重力方位ベクトル(高精度)よりも、少ないデータ量で演算処理を行う簡易重力方位推定部15bの出力する重力方位ベクトル(簡易)の方が妥当な値となることがある。このため、遷移状態や想定外の保持状態となっている場合等に、簡易重力方位推定部15bによる演算処理を行うことで、重力方位ベクトルの推定精度を高めることができる。 The holding state estimation unit 10 of the positioning device 80 estimates the holding state using the gravity direction vector (high accuracy) or the gravity direction vector (simple) output as described above. Depending on the holding state, measurement data having a value that is not assumed by the high-precision gravity azimuth estimation unit 15a is input, and therefore, less than the gravity azimuth vector (high accuracy) output by the high-precision gravity azimuth estimation unit 15a. The gravity direction vector (simple) output from the simple gravity direction estimation unit 15b that performs arithmetic processing with the amount of data may be a more appropriate value. For this reason, the estimation accuracy of the gravity direction vector can be improved by performing the calculation process by the simple gravity direction estimation unit 15b in a transition state or an unexpected holding state.
 保持状態推定部10における重力方位ベクトルの利用について、図16に基づいて説明する。図16は、保持状態推定部10の要部構成を示すブロック図である。図示のように、保持状態識別部10a及び遷移状態検出部10bには、3軸加速度データ、3軸角速度データ、及び3軸地磁気データに加えて、重力方位が入力されている。この重力方位は、重力方位ベクトル(高精度)及び重力方位ベクトル(簡易)である。 The use of the gravity direction vector in the holding state estimation unit 10 will be described with reference to FIG. FIG. 16 is a block diagram illustrating a main configuration of the holding state estimation unit 10. As shown in the drawing, in addition to the triaxial acceleration data, the triaxial angular velocity data, and the triaxial geomagnetic data, the gravity direction is input to the holding state identifying unit 10a and the transition state detecting unit 10b. This gravity direction is a gravity direction vector (high accuracy) and a gravity direction vector (simple).
 重力方位ベクトル(高精度)または重力方位ベクトル(簡易)を用いることによって、3軸加速度データ、3軸角速度データ、及び3軸地磁気データについて、測位装置80の進行方向成分と、それに垂直な方向の成分とに分解することができ、これにより高精度に保持状態の識別をすることができる。 By using the gravity azimuth vector (high accuracy) or the gravity azimuth vector (simple), the traveling direction component of the positioning device 80 and the direction perpendicular to the three-axis acceleration data, three-axis angular velocity data, and three-axis geomagnetic data are obtained. It can be decomposed into components, whereby the holding state can be identified with high accuracy.
 遷移状態の検出についても同様である。すなわち、遷移時には加速度が急激に変化するため、鉛直・進行方向加速度に基づいて、急激に変化するパターンを検知し、遷移状態を検出することができる。また、例えば、進行方位が急激に変化したことをもって、遷移状態を検出してもよい。なお、移動体(歩行者)が方向転換したときにも進行方位は変化するが、その変化の度合いが遷移状態の場合の方が大きいので、方向転換と遷移状態とは識別が可能である。 The same applies to the detection of the transition state. That is, since the acceleration changes abruptly at the time of transition, it is possible to detect a transitional state by detecting a rapidly changing pattern based on the vertical / traveling direction acceleration. Further, for example, the transition state may be detected when the traveling direction has changed abruptly. In addition, although advancing direction changes also when a mobile body (pedestrian) changes direction, since the degree of the change is larger in the transition state, it is possible to distinguish the direction change and the transition state.
 また、測位装置80の高精度移動量推定部16及び簡易移動量推定部17も、上記のようにして出力される重力方位ベクトル(高精度)または重力方位ベクトル(簡易)を用いて移動ベクトルの推定を行う。 In addition, the high-precision movement amount estimation unit 16 and the simple movement amount estimation unit 17 of the positioning device 80 also use the gravity direction vector (high accuracy) or the gravity direction vector (simple) output as described above. Estimate.
 これについて、図17に基づいて説明する。図17は、重力方位ベクトルが入力される高精度移動量推定部16の要部構成を示すブロック図である。図示のように、歩行動作検出部16aには、3軸加速度データに加えて重力方位が入力されている。また、移動方位検出部16cには、3軸地磁気データに加えて重力方位が入力されている。これらの重力方位は、重力方位ベクトル(高精度)である。 This will be described with reference to FIG. FIG. 17 is a block diagram showing a main configuration of the high-precision movement amount estimation unit 16 to which a gravity direction vector is input. As illustrated, in addition to the triaxial acceleration data, the gravity direction is input to the walking motion detector 16a. In addition to the triaxial geomagnetic data, the gravity direction is input to the moving direction detector 16c. These gravity directions are gravity direction vectors (high accuracy).
 このように、測位装置80の高精度移動量推定部16では、重力方位ベクトル(高精度)を用いて歩行動作の検出、移動方位の特定等が行われるので、移動ベクトルを高精度に推定することができる。 As described above, the high-precision movement amount estimation unit 16 of the positioning device 80 detects the walking motion, specifies the movement direction, and the like using the gravity direction vector (high accuracy), and thus estimates the movement vector with high accuracy. be able to.
 同様に、簡易移動量推定部17では、重力方位ベクトル(簡易)を用いて歩行動作の検出、移動方位の特定等が行われる。これについて、図18に基づいて説明する。図18は、重力方位ベクトルが入力される簡易移動量推定部17の要部構成を示すブロック図である。 Similarly, the simple movement amount estimation unit 17 detects the walking motion, specifies the movement direction, and the like using the gravity direction vector (simple). This will be described with reference to FIG. FIG. 18 is a block diagram illustrating a main configuration of the simple movement amount estimation unit 17 to which a gravity direction vector is input.
 図示のように、測位装置80の簡易移動量推定部17は、図10と同様に、歩行動作検出部17a、歩幅推定部17b、移動方位検出部17c、及び移動ベクトル算出部17dを備えている。 As illustrated, the simple movement amount estimation unit 17 of the positioning device 80 includes a walking motion detection unit 17a, a stride estimation unit 17b, a movement direction detection unit 17c, and a movement vector calculation unit 17d, as in FIG. .
 そして、歩行動作検出部17aには、3軸加速度データに加えて重力方位ベクトル(簡易)が入力され、移動方位検出部17cには3軸地磁気データに加えて重力方位ベクトル(簡易)が入力される。 In addition to the triaxial acceleration data, the gravity direction vector (simple) is input to the walking motion detection unit 17a, and the gravity direction vector (simple) is input to the movement direction detection unit 17c in addition to the triaxial geomagnetic data. The
 このように、測位装置80の簡易移動量推定部17では、重力方位ベクトル(簡易)を用いて歩行動作の検出、移動方位の特定等が行われる。 As described above, the simple movement amount estimation unit 17 of the positioning device 80 uses the gravity direction vector (simple) to detect walking motion, specify the movement direction, and the like.
 なお、上述のように、重力方位ベクトル(高精度)の信頼度が高いか、重力方位ベクトル(簡易)の信頼度が高いかは、保持状態によって変わる。このため、重力方位ベクトル(高精度)及び重力方位ベクトル(簡易)の両方を、高精度移動量推定部16及び簡易移動量推定部17に出力してもよい。そして、高精度移動量推定部16及び簡易移動量推定部17は、状態データに応じて、重力方位ベクトル(高精度)及び重力方位ベクトル(簡易)の何れを用いるかを決定し、決定した重力方位ベクトルから移動ベクトルを算出してもよい。なお、重力方位ベクトル(高精度)及び重力方位ベクトル(簡易)の何れを用いるかは、調整部11が制御してもよい。 As described above, whether the reliability of the gravity direction vector (high accuracy) or the reliability of the gravity direction vector (simple) is high depends on the holding state. For this reason, you may output both a gravity direction vector (high precision) and a gravity direction vector (simple) to the high precision movement amount estimation part 16 and the simple movement amount estimation part 17. FIG. Then, the high-precision movement amount estimation unit 16 and the simple movement amount estimation unit 17 determine which one of the gravity direction vector (high accuracy) and the gravity direction vector (simple) to use according to the state data, and determine the determined gravity A movement vector may be calculated from the orientation vector. Note that the adjustment unit 11 may control whether to use a gravity direction vector (high accuracy) or a gravity direction vector (simple).
 また、上記では、重力方位ベクトル(高精度)及び重力方位ベクトル(簡易)の両方を常に出力する例を示したが、保持状態に応じて、重力方位ベクトル(高精度)または重力方位ベクトル(簡易)の何れかのみを出力するようにしてもよい。 In the above example, both the gravity direction vector (high accuracy) and the gravity direction vector (simple) are always output. However, depending on the holding state, the gravity direction vector (high accuracy) or the gravity direction vector (simple ) May be output.
 〔変形例〕
 上記実施形態では、計測部2を備えた計測装置について説明したが、計測部2は、計測装置と別体に構成されていてもよい。すなわち、本発明の計測装置は、計測部2を内蔵したものに限られず、計測装置と通信可能に接続されたものであってもよい。この場合には、計測装置が出力する計測データを受信して、該計測装置を保持する移動体の移動状態に関するパラメータを算出することになる。
[Modification]
In the above embodiment, the measurement device including the measurement unit 2 has been described. However, the measurement unit 2 may be configured separately from the measurement device. That is, the measuring device of the present invention is not limited to the one incorporating the measuring unit 2, and may be one that is communicably connected to the measuring device. In this case, the measurement data output from the measuring device is received, and the parameter relating to the moving state of the moving body that holds the measuring device is calculated.
 また、上記実施形態では、簡易移動量推定部17及び簡易重力方位推定部15bが、高精度移動量推定部16及び高精度重力方位推定部15aが使用する計測データの一部を用いて処理を行う例を説明したが、この例に限られない。例えば、高精度移動量推定部16及び高精度重力方位推定部15a用の高精度のセンサと、簡易移動量推定部17及び簡易重力方位推定部15b用の低精度のセンサとを搭載してもよい。 Moreover, in the said embodiment, the simple movement amount estimation part 17 and the simple gravity direction estimation part 15b process using a part of measurement data which the high precision movement amount estimation part 16 and the high precision gravity direction estimation part 15a use. Although the example to perform was demonstrated, it is not restricted to this example. For example, a high-precision sensor for the high-precision movement amount estimation unit 16 and the high-precision gravity direction estimation unit 15a and a low-precision sensor for the simple movement amount estimation unit 17 and the simple gravity direction estimation unit 15b may be mounted. Good.
 さらに、上記実施形態では、1つのブロック(例えば移動量推定部12)が複数通りの演算処理を実行可能であり、複数通りの演算処理のうち、調整部11が出力する制御信号で指定された演算処理を実行する例を説明したが、この例に限られない。例えば、移動量推定部12を1通りの演算処理を実行する複数のブロックに分けて、調整部11が出力する制御信号で指定されたブロックに演算処理を行わせてもよい。 Furthermore, in the above-described embodiment, one block (for example, the movement amount estimation unit 12) can execute a plurality of calculation processes, and is designated by a control signal output from the adjustment unit 11 among the plurality of calculation processes. Although the example which performs a calculation process was demonstrated, it is not restricted to this example. For example, the movement amount estimation unit 12 may be divided into a plurality of blocks that execute one type of calculation process, and the block specified by the control signal output from the adjustment unit 11 may be calculated.
 また、上記実施形態では、調整部11を介して演算処理の変更を行う例を説明したが、保持状態推定部10が移動量推定部12等に直接に状態データを出力して、移動量推定部12等が、状態データに応じた演算処理を判断し、実行するようにしてもよい。 In the above-described embodiment, the example in which the arithmetic processing is changed via the adjustment unit 11 has been described. However, the holding state estimation unit 10 outputs the state data directly to the movement amount estimation unit 12 and the like to estimate the movement amount. The unit 12 or the like may determine and execute a calculation process according to the state data.
 本発明は上述した各実施形態に限定されるものではなく、請求項に示した範囲で種々の変更が可能であり、異なる実施形態にそれぞれ開示された技術的手段を適宜組み合わせて得られる実施形態についても本発明の技術的範囲に含まれる。 The present invention is not limited to the above-described embodiments, and various modifications are possible within the scope shown in the claims, and embodiments obtained by appropriately combining technical means disclosed in different embodiments. Is also included in the technical scope of the present invention.
 以上のように、本発明の計算装置は、移動体に保持される1または複数のセンサが出力する計測データを用いて、該移動体の移動状態を示すパラメータを算出する計算装置であって、上記計測データから、上記センサが移動体にどのように保持されているかを特定する保持状態特定手段と、上記保持状態特定手段が特定した保持状態に応じた演算処理を行い、上記計測データから上記移動体の移動状態を示すパラメータを算出するパラメータ算出手段とを備える構成である。 As described above, the calculation device of the present invention is a calculation device that calculates a parameter indicating the moving state of the moving body using measurement data output from one or more sensors held by the moving body. From the measurement data, a holding state specifying unit that specifies how the sensor is held by the moving body, and a calculation process according to the holding state specified by the holding state specifying unit are performed. It is a structure provided with the parameter calculation means which calculates the parameter which shows the movement state of a moving body.
 また、上記計測データは、上記センサが検出した加速度の大きさ及び向きを示す加速度データと、上記センサが検出した角速度の大きさ及び向きを示す角速度データとを含み、上記計算装置は、上記角速度データ及び上記加速度データを用いて、上記移動体の姿勢角を算出する姿勢角算出手段を備え、上記保持状態特定手段は、上記姿勢角算出手段が算出した姿勢角と上記計測データとを用いて、上記センサが移動体にどのように保持されているかを特定することが好ましい。 The measurement data includes acceleration data indicating the magnitude and direction of the acceleration detected by the sensor, and angular velocity data indicating the magnitude and direction of the angular velocity detected by the sensor. Posture angle calculating means for calculating the posture angle of the moving object using the data and the acceleration data, and the holding state specifying means uses the posture angle calculated by the posture angle calculating means and the measurement data. It is preferable to specify how the sensor is held by the moving body.
 姿勢角を算出することにより、移動体の重力方位を特定することができる。そして、重力方位が特定されることによって、保持状態をより高精度に特定することが可能になる。したがって、姿勢角と計測データとを用いて保持状態を特定する上記の構成によれば、保持状態の特定精度を向上させることができ、これにより適切な演算処理が行われる確度を高めることができる。 重力 By calculating the attitude angle, the gravity direction of the moving object can be specified. By specifying the gravity direction, the holding state can be specified with higher accuracy. Therefore, according to the above configuration for specifying the holding state using the posture angle and the measurement data, it is possible to improve the specifying accuracy of the holding state, thereby increasing the accuracy with which appropriate arithmetic processing is performed. .
 また、保持状態の特定精度を向上させることにより、より細かな保持状態を区別して検出することが可能になる。このため、上記の構成によれば、予め想定される保持状態のバリエーションを増やして、より適した演算処理でパラメータの算出を行うことも可能になる。 Further, by improving the specific accuracy of the holding state, it becomes possible to distinguish and detect a finer holding state. For this reason, according to said structure, it is also possible to increase the variation of the holding | maintenance state assumed beforehand and to calculate a parameter by more suitable arithmetic processing.
 また、上記計測データは、上記センサが検出した加速度の大きさ及び向きを示す加速度データを含み、上記計算装置は、上記加速度データを用いて、上記移動体の重力方位を特定する重力方位特定手段を備え、上記保持状態特定手段は、上記重力方位特定手段が特定した重力方位と上記計測データとを用いて、上記センサが移動体にどのように保持されているかを特定することが好ましい。 The measurement data includes acceleration data indicating the magnitude and direction of the acceleration detected by the sensor, and the calculation device uses the acceleration data to specify a gravity direction specifying means for specifying the gravity direction of the moving body. It is preferable that the holding state specifying unit specifies how the sensor is held by the moving body using the gravity direction specified by the gravity direction specifying unit and the measurement data.
 重力方位が特定されることによって、保持状態をより高精度に特定することが可能になる。したがって、重力方位と計測データとを用いて保持状態を特定する上記の構成によれば、保持状態の特定精度を向上させることができ、これにより適切な演算処理が行われる確度を高めることができる。なお、上記重力方位特定手段が特定する重力方位は、移動体の重力方位であり、世界座標系における重力方位ではない。 By specifying the gravity direction, it becomes possible to specify the holding state with higher accuracy. Therefore, according to the above configuration that specifies the holding state using the gravity direction and the measurement data, it is possible to improve the specifying accuracy of the holding state, thereby increasing the accuracy with which appropriate calculation processing is performed. . Note that the gravity azimuth specified by the gravity azimuth specifying means is the gravity azimuth of the moving object, not the gravity azimuth in the world coordinate system.
 また、保持状態の特定精度を向上させることにより、より細かな保持状態を区別して検出することが可能になる。このため、上記の構成によれば、予め想定される保持状態のバリエーションを増やして、より適した演算処理でパラメータの算出を行うことも可能になる。 Further, by improving the specific accuracy of the holding state, it becomes possible to distinguish and detect a finer holding state. For this reason, according to said structure, it is also possible to increase the variation of the holding | maintenance state assumed beforehand and to calculate a parameter by more suitable arithmetic processing.
 ここで、センサの保持状態は、常に一定であるとは限らず、変化することが考えられる。例えば、移動体が人である場合には、センサを持ち変えることによって保持状態が変化することが考えられる。そして、保持状態が、ある保持状態から他の保持状態に変化する期間にセンサで検出される計測データは、通常と大きく異なる値となる。このため、この期間における計測データをそのまま用いてパラメータの算出を行った場合には、実際の運動状態とは大きく異なるパラメータが算出されるおそれがある。 Here, the holding state of the sensor is not always constant and may change. For example, when the moving body is a person, it is conceivable that the holding state changes by changing the sensor. The measurement data detected by the sensor during a period in which the holding state changes from one holding state to another holding state has a value that is significantly different from normal. For this reason, when the parameter is calculated using the measurement data in this period as it is, there is a possibility that a parameter greatly different from the actual motion state is calculated.
 そこで、上記保持状態特定手段が特定する保持状態には、上記センサの保持状態が他の保持状態へと遷移している遷移状態が含まれることが好ましい。 Therefore, it is preferable that the holding state specified by the holding state specifying unit includes a transition state in which the holding state of the sensor transitions to another holding state.
 上記の構成によれば、遷移状態を保持状態の1つとして特定し、遷移状態に応じた演算処理でパラメータの算出を行うので、実際の運動状態とは大きく異なるパラメータが算出されることを防ぐことができる。 According to the above configuration, the transition state is specified as one of the holding states, and the parameter is calculated by the arithmetic processing according to the transition state, so that it is possible to prevent a parameter greatly different from the actual motion state from being calculated. be able to.
 例えば、ポケットに保持していたセンサを取り出したときには、保持状態がポケットに保持されている保持状態から手に持たれている保持状態へと変化する。上記の構成では、このように保持状態が変化している期間の保持状態を遷移状態として検出する。 For example, when the sensor held in the pocket is taken out, the holding state changes from the holding state held in the pocket to the holding state held in the hand. In the above configuration, the holding state during the period in which the holding state is changing is detected as the transition state.
 ここで、遷移状態では、センサの位置や向きが短時間に大きく変化することに起因して、センサの出力する計測データ(例えば、加速度データや角速度データ、地磁気データ等)の値が急激に上昇することが多い。このため、計測データの変化率を経時的に算出して、その変化率が予め定めた閾値を超えるか否かを判断することにより、遷移状態の検出が可能となる。 Here, in the transition state, the value of measurement data (for example, acceleration data, angular velocity data, geomagnetism data, etc.) output by the sensor rises sharply due to a large change in the position and orientation of the sensor in a short time. Often to do. For this reason, it is possible to detect the transition state by calculating the rate of change of the measurement data over time and determining whether the rate of change exceeds a predetermined threshold.
 しかしながら、センサの出力する計測データの値は、該センサを保持している移動体の運動状態に依存するため、常に同じ値の閾値で遷移状態の検出を行う方法では、遷移状態の検出精度に限りがある。例えば、移動体の移動速度が上がれば、それに応じてセンサが出力する計測データの値も上昇する。 However, since the value of the measurement data output by the sensor depends on the motion state of the moving object holding the sensor, the method of always detecting the transition state with the same threshold value increases the detection accuracy of the transition state. There is a limit. For example, if the moving speed of the moving body increases, the value of measurement data output by the sensor increases accordingly.
 このため、上記保持状態特定手段は、上記センサが出力する計測データの値が大きいほど大きい値の閾値を設定し、上記計測データの変化率が、設定した上記閾値を超えたときに、上記遷移状態であると特定することが好ましい。 For this reason, the holding state specifying means sets a larger threshold value as the value of the measurement data output from the sensor is larger, and the transition is performed when the change rate of the measurement data exceeds the set threshold value. It is preferable to identify the state.
 上記の構成によれば、センサが出力する計測データの値が大きい値の閾値を設定して遷移状態の特定を行うので、遷移状態の検出精度を向上させることができる。 According to the above configuration, since the transition state is specified by setting a threshold value having a large value of the measurement data output from the sensor, it is possible to improve the detection accuracy of the transition state.
 また、上記計算装置は、上記計測データの一部を用いて上記移動体の移動状態を示すパラメータを算出する簡易パラメータ算出手段と、上記保持状態特定手段が特定した保持状態に応じて、上記パラメータ算出手段の算出するパラメータを出力するか、上記簡易パラメータ算出手段の算出するパラメータを出力するか、または上記パラメータ算出手段の算出するパラメータと上記簡易パラメータ算出手段の算出するパラメータとを合成して算出したパラメータを出力するかを切り替える切替手段とを備えていることが好ましい。 In addition, the calculation device includes a simple parameter calculation unit that calculates a parameter indicating a moving state of the moving body using a part of the measurement data, and the parameter according to the holding state specified by the holding state specifying unit. The parameter calculated by the calculation means is output, the parameter calculated by the simple parameter calculation means is output, or the parameter calculated by the parameter calculation means is combined with the parameter calculated by the simple parameter calculation means Preferably, switching means for switching whether to output the selected parameter is provided.
 上記の構成によれば、保持状態に応じてパラメータの算出を行う手段を切り替えるので、保持状態に応じた適切な手段でパラメータの算出を行うことができる。例えば、遷移状態等のように、計測データの値が不安定な状態では、パラメータ算出手段によるパラメータ算出精度も落ちることが考えられる。このため、計測データの値が不安定な状態においては、簡易パラメータ算出手段に切り替えることによって、少ない計測データを用いた簡易な演算処理でパラメータを算出することができる。 According to the above configuration, since the parameter calculation unit is switched according to the holding state, the parameter can be calculated by an appropriate unit according to the holding state. For example, in a state where the value of measurement data is unstable such as a transition state, the parameter calculation accuracy by the parameter calculation means may be reduced. For this reason, in the state where the value of the measurement data is unstable, the parameter can be calculated by a simple calculation process using a small amount of measurement data by switching to the simple parameter calculation means.
 なお、計測データの一部を用いてパラメータを算出する、とは、計測データよりも少ないデータ量でパラメータを算出することを指す。例えば、計測データに3軸方向の加速度データと3軸方向の角速度データとが含まれる場合に、3軸方向の加速度データのみを用いてパラメータを算出することや、3軸方向の加速度データと2軸方向の角速度データとを用いてパラメータを算出すること等を指す。また、例えば、センサから計測データを取得する周期を長くしたり、センサが計測データを出力する周期を長くしたりする等してデータ量を減らしてパラメータを算出する場合も含む。 Note that calculating a parameter using a part of measurement data means calculating the parameter with a data amount smaller than the measurement data. For example, when the measurement data includes acceleration data in the triaxial direction and angular velocity data in the triaxial direction, the parameter is calculated using only the acceleration data in the triaxial direction, the acceleration data in the triaxial direction and 2 This refers to calculating a parameter using the angular velocity data in the axial direction. In addition, for example, a case where the parameter is calculated by reducing the data amount by increasing the period for acquiring the measurement data from the sensor or by increasing the period at which the sensor outputs the measurement data is included.
 上記保持状態特定手段が特定した保持状態が、上記簡易パラメータ算出手段の算出するパラメータが出力される保持状態である場合に、上記センサを制御して、上記簡易パラメータ算出手段が用いない計測データのうち、少なくとも一部の測定を停止させるか、または、上記計測データの出力頻度を下げさせる測定制御手段を備えていることが好ましい。 When the holding state specified by the holding state specifying unit is a holding state in which the parameter calculated by the simple parameter calculating unit is output, the sensor is controlled, and measurement data not used by the simple parameter calculating unit Among them, it is preferable to include a measurement control means for stopping at least a part of the measurement or reducing the output frequency of the measurement data.
 上記の構成によれば、簡易パラメータ算出手段によるパラメータの算出が行われているときには、センサによる測定を一部停止させるか、または、計測データの出力頻度を下げさせるので、センサにおける消費電力を低減することができる。 According to the above configuration, when the parameter is calculated by the simple parameter calculation means, the measurement by the sensor is partially stopped or the output frequency of the measurement data is lowered, so that the power consumption of the sensor is reduced. can do.
 また、上記重力方位特定手段が上記移動体の重力方位を特定するために用いる計測データの一部を用いて上記移動体の重力方位を特定する簡易重力方位特定手段を備え、上記パラメータ算出手段は、上記保持状態特定手段が特定した保持状態に応じて、上記重力方位特定手段または上記簡易重力方位特定手段の特定した重力方位を用いて、上記パラメータを算出することが好ましい。 The gravity direction specifying means includes simple gravity direction specifying means for specifying the gravity direction of the moving body using a part of measurement data used for specifying the gravity direction of the moving body, and the parameter calculating means includes: Preferably, the parameter is calculated using the gravity azimuth specified by the gravity azimuth specifying means or the simple gravity azimuth specifying means according to the holding state specified by the holding state specifying means.
 保持状態によっては、重力方位特定手段で想定していないような値の計測データが入力されるので、重力方位特定手段の特定する重力方位よりも、少ないデータ量で重力方位を求める方が妥当な値が算出されることがある。 Depending on the holding state, measurement data with a value that is not assumed by the gravity azimuth specifying means is input, so it is more appropriate to obtain the gravity azimuth with a smaller amount of data than the gravity azimuth specified by the gravity azimuth specifying means. A value may be calculated.
 したがって、保持状態に応じて重力方位特定手段と簡易重力方位特定手段の何れが出力する重力方位を用いるかを切り替える上記の構成によれば、パラメータの推定精度を高めることができる。 Therefore, according to the above configuration that switches which one of the gravity azimuth specifying means and the simple gravity azimuth specifying means to use according to the holding state, the parameter estimation accuracy can be increased.
 上記パラメータ算出手段は、上記保持状態特定手段が遷移状態であると特定している期間に上記センサから出力される計測データの寄与が、上記保持状態特定手段が遷移状態であると特定していない期間に上記センサから出力される計測データの寄与よりも小さくなる演算処理により、上記パラメータを算出することが好ましい。 The parameter calculation means does not identify the contribution of the measurement data output from the sensor during the period when the holding state specifying means is in the transition state as the holding state specifying means is in the transition state. It is preferable to calculate the parameter by a calculation process that is smaller than the contribution of measurement data output from the sensor during the period.
 上述のように、遷移状態で出力される計測データは、不安定であり、信頼性が低い。そこで、上記構成では、遷移状態における演算処理では、遷移状態の期間に出力される計測データの寄与を相対的に小さくしている。これにより、パラメータの精度を向上させることができる。 As described above, the measurement data output in the transition state is unstable and has low reliability. Therefore, in the above configuration, in the calculation processing in the transition state, the contribution of the measurement data output during the transition state period is relatively small. Thereby, the accuracy of parameters can be improved.
 なお、上記計算装置は、コンピュータによって実現してもよく、この場合には、コンピュータを上記計算装置の各手段として動作させることにより、上記計算装置をコンピュータにて実現させる制御プログラム、及びそれを記録したコンピュータ読み取り可能な記録媒体も本発明の範疇に入る。 The computer may be realized by a computer. In this case, a control program for realizing the computer by the computer by operating the computer as each unit of the computer, and recording the program Such computer-readable recording media also fall within the scope of the present invention.
 なお、測位装置1、30、40、50、60、及び70(以下、測位装置1等と呼ぶ)の各ブロック、特に制御部3は、ハードウェアロジックによって構成してもよいし、次のようにCPUを用いてソフトウェアによって実現してもよい。 Each block of the positioning devices 1, 30, 40, 50, 60, and 70 (hereinafter referred to as the positioning device 1 and the like), in particular, the control unit 3 may be configured by hardware logic, as follows. Alternatively, it may be realized by software using a CPU.
 すなわち、測位装置1等は、各機能を実現する制御プログラムの命令を実行するCPU(central processing unit)、上記プログラムを格納したROM(read only memory)、上記プログラムを展開するRAM(random access memory)、上記プログラムおよび各種データを格納するメモリ等の記憶装置(記録媒体)などを備えている。そして、本発明の目的は、上述した機能を実現するソフトウェアである測位装置1等の制御プログラムのプログラムコード(実行形式プログラム、中間コードプログラム、ソースプログラム)をコンピュータで読み取り可能に記録した記録媒体を、上記測位装置1等に供給し、そのコンピュータ(またはCPUやMPU)が記録媒体に記録されているプログラムコードを読み出し実行することによっても、達成可能である。 That is, the positioning device 1 or the like includes a CPU (central processing unit) that executes instructions of a control program that realizes each function, a ROM (read only memory) that stores the program, and a RAM (random access memory) that expands the program. And a storage device (recording medium) such as a memory for storing the program and various data. An object of the present invention is a recording medium in which program codes (execution format program, intermediate code program, source program) of a control program such as the positioning device 1 which is software for realizing the functions described above are recorded so as to be readable by a computer. This can also be achieved by supplying to the positioning device 1 and the like and reading and executing the program code recorded on the recording medium by the computer (or CPU or MPU).
 上記記録媒体としては、例えば、磁気テープやカセットテープ等のテープ系、フロッピー(登録商標)ディスク/ハードディスク等の磁気ディスクやCD-ROM/MO/MD/DVD/CD-R等の光ディスクを含むディスク系、ICカード(メモリカードを含む)/光カード等のカード系、あるいはマスクROM/EPROM/EEPROM/フラッシュROM等の半導体メモリ系などを用いることができる。 Examples of the recording medium include tapes such as magnetic tapes and cassette tapes, magnetic disks such as floppy (registered trademark) disks / hard disks, and disks including optical disks such as CD-ROM / MO / MD / DVD / CD-R. Card system such as IC card, IC card (including memory card) / optical card, or semiconductor memory system such as mask ROM / EPROM / EEPROM / flash ROM.
 また、測位装置1等を通信ネットワークと接続可能に構成し、上記プログラムコードを通信ネットワークを介して供給してもよい。この通信ネットワークとしては、特に限定されず、例えば、インターネット、イントラネット、エキストラネット、LAN、ISDN、VAN、CATV通信網、仮想専用網(virtual private network)、電話回線網、移動体通信網、衛星通信網等が利用可能である。また、通信ネットワークを構成する伝送媒体としては、特に限定されず、例えば、IEEE1394、USB、電力線搬送、ケーブルTV回線、電話線、ADSL回線等の有線でも、IrDAやリモコンのような赤外線、Bluetooth(登録商標)、802.11無線、HDR、携帯電話網、衛星回線、地上波デジタル網等の無線でも利用可能である。なお、本発明は、上記プログラムコードが電子的な伝送で具現化された、搬送波に埋め込まれたコンピュータデータ信号の形態でも実現され得る。 Alternatively, the positioning device 1 or the like may be configured to be connectable to a communication network, and the program code may be supplied via the communication network. The communication network is not particularly limited. For example, the Internet, intranet, extranet, LAN, ISDN, VAN, CATV communication network, virtual private network, telephone line network, mobile communication network, satellite communication. A net or the like is available. Further, the transmission medium constituting the communication network is not particularly limited. For example, even in the case of wired such as IEEE 1394, USB, power line carrier, cable TV line, telephone line, ADSL line, etc., infrared rays such as IrDA and remote control, Bluetooth ( (Registered trademark), 802.11 wireless, HDR, mobile phone network, satellite line, terrestrial digital network, and the like can also be used. The present invention can also be realized in the form of a computer data signal embedded in a carrier wave in which the program code is embodied by electronic transmission.
 また、発明を実施するための形態の項においてなした具体的な実施態様または実施例は、あくまでも、本発明の技術内容を明らかにするものであって、そのような具体例にのみ限定して狭義に解釈されるべきものではなく、本発明の精神と次に記載する特許請求の範囲内で、いろいろと変更して実施することができるものである。 In addition, the specific embodiments or examples made in the section for carrying out the invention are merely to clarify the technical contents of the present invention, and are limited to such specific examples. The present invention should not be construed in a narrow sense but can be implemented with various modifications within the spirit of the present invention and the scope of the following claims.
 本発明によれば、移動体の移動状態を示すパラメータを高精度に推定することができる。例えば、徒歩で移動する人の移動方位、移動距離等を高精度に推定することができるので、地図上で人の現在地を表示するナビゲーション装置等にも好適に適用することができる。 According to the present invention, the parameter indicating the moving state of the moving object can be estimated with high accuracy. For example, since the moving direction, moving distance, etc. of a person who moves on foot can be estimated with high accuracy, the present invention can also be suitably applied to a navigation apparatus that displays a person's current location on a map.
 1、30、40、50、60、70 測位装置(計算装置)
 2 計測部(センサ)
10 保持状態推定部(保持状態特定手段)
10c 保持状態判定部(測定制御手段)
11 調整部(切替手段)
12 移動量推定部(パラメータ算出手段)
12a 歩行動作検出部(パラメータ算出手段)
12b 歩幅推定部(パラメータ算出手段)
13 位置決定部(パラメータ算出手段)
14 姿勢角推定部(姿勢角算出手段)
15 重力方位推定部(重力方位特定手段)
15b 簡易重力方位推定部(簡易重力方位特定手段)
16a 歩行動作検出部(パラメータ算出手段)
16b 歩幅推定部(パラメータ算出手段)
16c 移動方位検出部(パラメータ算出手段)
16d 移動ベクトル算出部(パラメータ算出手段)
17 簡易移動量推定部(簡易パラメータ算出手段)
17a 歩行動作検出部(簡易パラメータ算出手段)
17b 歩幅推定部(簡易パラメータ算出手段)
17c 移動方位検出部(簡易パラメータ算出手段)
17d 移動ベクトル算出部(簡易パラメータ算出手段)
1, 30, 40, 50, 60, 70 Positioning device (calculation device)
2 Measurement unit (sensor)
10 Holding state estimation unit (holding state specifying means)
10c Holding state determination unit (measurement control means)
11 Adjustment unit (switching means)
12 Movement amount estimation unit (parameter calculation means)
12a Walking motion detection unit (parameter calculation means)
12b Stride estimation unit (parameter calculation means)
13 Position determination unit (parameter calculation means)
14 Attitude angle estimation unit (Attitude angle calculation means)
15 Gravity orientation estimation unit (gravity orientation identification means)
15b Simple gravity direction estimation unit (simple gravity direction specifying means)
16a Walking motion detection unit (parameter calculation means)
16b Stride estimation unit (parameter calculation means)
16c Moving direction detection unit (parameter calculation means)
16d movement vector calculation unit (parameter calculation means)
17 Simple movement amount estimation unit (simple parameter calculation means)
17a Walking motion detection unit (simple parameter calculation means)
17b Stride estimation unit (simple parameter calculation means)
17c Moving direction detection unit (simple parameter calculation means)
17d Movement vector calculation unit (simple parameter calculation means)

Claims (12)

  1.  移動体に保持される1または複数のセンサが出力する計測データを用いて、該移動体の移動状態を示すパラメータを算出する計算装置であって、
     上記計測データから、上記センサが移動体にどのように保持されているかを特定する保持状態特定手段と、
     上記保持状態特定手段が特定した保持状態に応じた演算処理を行い、上記計測データから上記移動体の移動状態を示すパラメータを算出するパラメータ算出手段とを備えていることを特徴とする計算装置。
    A calculation device that calculates a parameter indicating a moving state of a moving body using measurement data output from one or more sensors held by the moving body,
    From the measurement data, holding state specifying means for specifying how the sensor is held by the moving body,
    A calculation apparatus comprising: parameter calculation means for performing a calculation process according to the holding state specified by the holding state specifying means and calculating a parameter indicating a moving state of the moving body from the measurement data.
  2.  上記計測データは、上記センサが検出した加速度の大きさ及び向きを示す加速度データと、上記センサが検出した角速度の大きさ及び向きを示す角速度データとを含み、
     上記角速度データ及び上記加速度データを用いて、上記移動体の姿勢角を算出する姿勢角算出手段を備え、
     上記保持状態特定手段は、上記姿勢角算出手段が算出した姿勢角と上記計測データとを用いて、上記センサが移動体にどのように保持されているかを特定することを特徴とする請求項1に記載の計算装置。
    The measurement data includes acceleration data indicating the magnitude and direction of acceleration detected by the sensor, and angular velocity data indicating the magnitude and direction of angular velocity detected by the sensor,
    A posture angle calculating means for calculating a posture angle of the moving body using the angular velocity data and the acceleration data;
    2. The holding state specifying unit specifies how the sensor is held by a moving body using the posture angle calculated by the posture angle calculating unit and the measurement data. The computing device described in 1.
  3.  上記計測データは、上記センサが検出した加速度の大きさ及び向きを示す加速度データを含み、
     上記加速度データを用いて、上記移動体の重力方位を特定する重力方位特定手段を備え、
     上記保持状態特定手段は、上記重力方位特定手段が特定した重力方位と上記計測データとを用いて、上記センサが移動体にどのように保持されているかを特定することを特徴とする請求項1に記載の計算装置。
    The measurement data includes acceleration data indicating the magnitude and direction of acceleration detected by the sensor,
    Using the acceleration data, comprising gravity direction specifying means for specifying the gravity direction of the moving body,
    2. The holding state specifying unit specifies how the sensor is held by a moving body using the gravity direction specified by the gravity direction specifying unit and the measurement data. The computing device described in 1.
  4.  上記保持状態特定手段が特定する保持状態には、上記センサの保持状態が他の保持状態へと遷移している遷移状態が含まれることを特徴とする請求項1から3の何れか1項に記載の計算装置。 4. The holding state specified by the holding state specifying means includes a transition state in which the holding state of the sensor is transitioning to another holding state. The computing device described.
  5.  上記保持状態特定手段は、上記センサが出力する計測データの値が大きいほど大きい値の閾値を設定し、上記計測データの変化率が、設定した上記閾値を超えたときに、上記遷移状態であると特定することを特徴とする請求項4に記載の計算装置。 The holding state specifying means sets a threshold value that is larger as the value of the measurement data output from the sensor is larger, and is in the transition state when the rate of change of the measurement data exceeds the set threshold value. The calculation apparatus according to claim 4, characterized by:
  6.  上記計測データの一部を用いて上記移動体の移動状態を示すパラメータを算出する簡易パラメータ算出手段と、
     上記保持状態特定手段が特定した保持状態に応じて、上記パラメータ算出手段の算出するパラメータを出力するか、上記簡易パラメータ算出手段の算出するパラメータを出力するか、または上記パラメータ算出手段の算出するパラメータと上記簡易パラメータ算出手段の算出するパラメータとを合成して算出したパラメータを出力するかを切り替える切替手段とを備えていることを特徴とする請求項1から5の何れか1項に記載の計算装置。
    Simple parameter calculating means for calculating a parameter indicating a moving state of the moving body using a part of the measurement data;
    According to the holding state specified by the holding state specifying unit, a parameter calculated by the parameter calculating unit, a parameter calculated by the simple parameter calculating unit, or a parameter calculated by the parameter calculating unit 6. The calculation according to claim 1, further comprising: a switching unit that switches whether to output a parameter calculated by combining the parameter calculated by the simple parameter calculation unit. apparatus.
  7.  上記保持状態特定手段が特定した保持状態が、上記簡易パラメータ算出手段の算出するパラメータが出力される保持状態である場合に、上記センサを制御して、上記簡易パラメータ算出手段が用いない計測データのうち少なくとも一部の測定を停止させるか、または、上記計測データの出力頻度を下げさせる測定制御手段を備えていることを特徴とする請求項6に記載の計算装置。 When the holding state specified by the holding state specifying unit is a holding state in which the parameter calculated by the simple parameter calculating unit is output, the sensor is controlled, and measurement data not used by the simple parameter calculating unit The calculation apparatus according to claim 6, further comprising a measurement control unit that stops at least a part of the measurement or lowers the output frequency of the measurement data.
  8.  上記重力方位特定手段が上記移動体の重力方位を特定するために用いる計測データの一部を用いて上記移動体の重力方位を特定する簡易重力方位特定手段を備え、
     上記パラメータ算出手段は、上記保持状態特定手段が特定した保持状態に応じて、上記重力方位特定手段または上記簡易重力方位特定手段の特定した重力方位を用いて、上記パラメータを算出することを特徴とする請求項3に記載の計算装置。
    The gravity direction specifying means comprises simple gravity direction specifying means for specifying the gravity direction of the moving body using a part of measurement data used for specifying the gravity direction of the moving body,
    The parameter calculating means calculates the parameter using the gravity direction specified by the gravity direction specifying means or the simple gravity direction specifying means according to the holding state specified by the holding state specifying means. The calculation apparatus according to claim 3.
  9.  上記パラメータ算出手段は、上記保持状態特定手段が遷移状態であると特定している期間に上記センサから出力される計測データの寄与が、上記保持状態特定手段が遷移状態であると特定していない期間に上記センサから出力される計測データの寄与よりも小さくなる演算処理により、上記パラメータを算出することを特徴とする請求項4または5に記載の計算装置。 The parameter calculation means does not identify the contribution of the measurement data output from the sensor during the period when the holding state specifying means is in the transition state as the holding state specifying means is in the transition state. The calculation apparatus according to claim 4, wherein the parameter is calculated by an arithmetic process that is smaller than a contribution of measurement data output from the sensor during a period.
  10.  移動体に保持される1または複数のセンサが出力する計測データを用いて、該移動体の移動状態を示すパラメータを算出する計算装置の制御方法であって、
     上記計測データから、上記センサが移動体にどのように保持されているかを特定する保持状態特定ステップと、
     上記保持状態特定ステップで特定した保持状態に応じた演算処理を行い、上記計測データから上記移動体の移動状態を示すパラメータを算出するパラメータ算出ステップとを含むことを特徴とする計算装置の制御方法。
    A control method for a computing device that uses a measurement data output from one or more sensors held by a moving body to calculate a parameter indicating a moving state of the moving body,
    From the measurement data, a holding state specifying step for specifying how the sensor is held by the moving body;
    And a parameter calculation step of calculating a parameter indicating a movement state of the moving body from the measurement data, performing a calculation process according to the holding state specified in the holding state specifying step. .
  11.  請求項1から9の何れか1項に記載の計算装置を動作させるための制御プログラムであって、コンピュータを上記各手段として機能させるための制御プログラム。 A control program for operating the computing device according to any one of claims 1 to 9, wherein the control program causes a computer to function as each of the means.
  12.  請求項11に記載の制御プログラムを記録したコンピュータ読み取り可能な記録媒体。 A computer-readable recording medium on which the control program according to claim 11 is recorded.
PCT/JP2011/051748 2010-01-29 2011-01-28 Calculation device, control method for calculation device, control program, and recording medium WO2011093447A1 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
JP2011551932A JP5565736B2 (en) 2010-01-29 2011-01-28 COMPUTER DEVICE, COMPUTER DEVICE CONTROL METHOD, CONTROL PROGRAM, AND RECORDING MEDIUM

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
JP2010019753 2010-01-29
JP2010-019753 2010-01-29

Publications (1)

Publication Number Publication Date
WO2011093447A1 true WO2011093447A1 (en) 2011-08-04

Family

ID=44319427

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/JP2011/051748 WO2011093447A1 (en) 2010-01-29 2011-01-28 Calculation device, control method for calculation device, control program, and recording medium

Country Status (2)

Country Link
JP (1) JP5565736B2 (en)
WO (1) WO2011093447A1 (en)

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106092133A (en) * 2016-05-27 2016-11-09 北京灵龄科技有限责任公司 Start the decision method of guest mode, device
WO2018116476A1 (en) * 2016-12-22 2018-06-28 富士通株式会社 Information processing device, information processing method, and information processing program
CN109690449A (en) * 2016-09-30 2019-04-26 英特尔公司 Location determination techniques for virtual reality system
JP2019219187A (en) * 2018-06-15 2019-12-26 株式会社東芝 Position measurement device and position measurement method
JP2021148723A (en) * 2020-03-23 2021-09-27 株式会社東海理化電機製作所 Walking discrimination system, mobile device, processor, and computer program

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2006008790A1 (en) * 2004-07-15 2006-01-26 C & N Inc Mobile terminal device
JP2009276282A (en) * 2008-05-16 2009-11-26 Sumitomo Electric Ind Ltd Attitude determination apparatus and method, movement direction determination apparatus, position determination apparatus, and computer program
JP2011069633A (en) * 2009-09-24 2011-04-07 Sanyo Electric Co Ltd Portable device

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2006008790A1 (en) * 2004-07-15 2006-01-26 C & N Inc Mobile terminal device
JP2009276282A (en) * 2008-05-16 2009-11-26 Sumitomo Electric Ind Ltd Attitude determination apparatus and method, movement direction determination apparatus, position determination apparatus, and computer program
JP2011069633A (en) * 2009-09-24 2011-04-07 Sanyo Electric Co Ltd Portable device

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106092133A (en) * 2016-05-27 2016-11-09 北京灵龄科技有限责任公司 Start the decision method of guest mode, device
CN109690449A (en) * 2016-09-30 2019-04-26 英特尔公司 Location determination techniques for virtual reality system
CN109690449B (en) * 2016-09-30 2023-12-05 英特尔公司 Positioning determination techniques for virtual reality systems
WO2018116476A1 (en) * 2016-12-22 2018-06-28 富士通株式会社 Information processing device, information processing method, and information processing program
JPWO2018116476A1 (en) * 2016-12-22 2019-07-18 富士通株式会社 INFORMATION PROCESSING APPARATUS, INFORMATION PROCESSING METHOD, AND INFORMATION PROCESSING PROGRAM
JP2019219187A (en) * 2018-06-15 2019-12-26 株式会社東芝 Position measurement device and position measurement method
JP7059114B2 (en) 2018-06-15 2022-04-25 株式会社東芝 Position measuring device and position measuring method
JP2021148723A (en) * 2020-03-23 2021-09-27 株式会社東海理化電機製作所 Walking discrimination system, mobile device, processor, and computer program

Also Published As

Publication number Publication date
JPWO2011093447A1 (en) 2013-06-06
JP5565736B2 (en) 2014-08-06

Similar Documents

Publication Publication Date Title
JP6359067B2 (en) System and method for improving orientation data
Zhou et al. Use it free: Instantly knowing your phone attitude
US9127947B2 (en) State estimator for rejecting noise and tracking and updating bias in inertial sensors and associated methods
CN107636420B (en) Techniques for pedestrian dead reckoning
US20130204572A1 (en) State detection device, electronic apparatus, and program
JP5565736B2 (en) COMPUTER DEVICE, COMPUTER DEVICE CONTROL METHOD, CONTROL PROGRAM, AND RECORDING MEDIUM
WO2014039552A1 (en) System and method for estimating the direction of motion of an entity associated with a device
KR20150099863A (en) Inertial device, method, and program
US8750897B2 (en) Methods and apparatuses for use in determining a motion state of a mobile device
US20140012536A1 (en) Information processing apparatus, information processing method, program, and recording medium
US20140012539A1 (en) Information processing apparatus, congestion degree map generating apparatus, information processing method, program, and recording medium
US20150241244A1 (en) Low-power orientation estimation
EP3227634B1 (en) Method and system for estimating relative angle between headings
JP5821513B2 (en) Reference value generation method and reference value generation apparatus
KR101226767B1 (en) System and Method for localizationing of Autonomous Vehicle
JP5652195B2 (en) Turning detection device, terminal device and program
JP6147446B1 (en) Inertial sensor initialization using soft constraints and penalty functions
Zhou et al. Pedestrian navigation with foot-mounted inertial sensors in wearable body area networks
Wang et al. Posture recognition and adaptive step detection based on hand-held terminal
CN110579212B (en) Indoor positioning method and device
KR20160108146A (en) Method and electronic device for improving accuracy of measurement of motion sensor

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 11737157

Country of ref document: EP

Kind code of ref document: A1

WWE Wipo information: entry into national phase

Ref document number: 2011551932

Country of ref document: JP

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 11737157

Country of ref document: EP

Kind code of ref document: A1