WO2023182407A1 - Information processing device, information processing method, and program - Google Patents

Information processing device, information processing method, and program Download PDF

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Publication number
WO2023182407A1
WO2023182407A1 PCT/JP2023/011402 JP2023011402W WO2023182407A1 WO 2023182407 A1 WO2023182407 A1 WO 2023182407A1 JP 2023011402 W JP2023011402 W JP 2023011402W WO 2023182407 A1 WO2023182407 A1 WO 2023182407A1
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Prior art keywords
positioning
data
information processing
processing device
observation
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PCT/JP2023/011402
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French (fr)
Japanese (ja)
Inventor
颯海 川手
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ソニーセミコンダクタソリューションズ株式会社
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Publication of WO2023182407A1 publication Critical patent/WO2023182407A1/en

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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/42Determining position
    • G01S19/43Determining position using carrier phase measurements, e.g. kinematic positioning; using long or short baseline interferometry
    • G01S19/44Carrier phase ambiguity resolution; Floating ambiguity; LAMBDA [Least-squares AMBiguity Decorrelation Adjustment] method
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/10Simultaneous control of position or course in three dimensions

Definitions

  • the present disclosure relates to an information processing device, an information processing method, and a program.
  • Patent Document 1 discloses a technology related to an autonomous mobile robot that estimates its own position by using GNSS (Global Navigation Satellite System) and moves along a movement route from its own position to a predetermined movement target position. .
  • GNSS Global Navigation Satellite System
  • the elevation angle of each navigation satellite is determined at the positioning start time (current time, time 5 minutes later, etc.) and positioning end time, and a plurality of satellites whose elevation angles are equal to or greater than a predetermined angle threshold are determined to be receivable.
  • a satellite set consisting of a combination of multiple navigation satellites is selected to estimate self-position with stable accuracy.
  • a type of relative positioning called RTK (Real Time Kinematic) positioning method is used.
  • two GNSS receivers receive signals from four or more satellites, and information is sent and received between the mobile station and the fixed station to correct any discrepancies, thereby improving accuracy. Get high location information.
  • the aim is to calculate self-position with stable accuracy by selecting multiple satellites to receive signals by considering only the position of each satellite, but further improvement in accuracy is required for positioning. .
  • a plurality of sets of usage start times and usage end times of data used for positioning processing are determined for observation data acquired by a mobile station and including signals received from navigation satellites, and the plurality of sets of usage start times and usage end times are determined. and a control unit that calculates a plurality of positioning data through positioning processing based on the observation data used by the reference station and the observation data of the reference station, and generates final positioning data based on the plurality of positioning data.
  • an information processing device is provided.
  • the processor determines a plurality of sets of use start times and use end times of data used for positioning processing for observation data acquired by the mobile station and including signals received from navigation satellites. calculating a plurality of positioning data through positioning processing based on the observation data used by the plurality of sets and the observation data of the reference station; and calculating the final positioning data based on the plurality of positioning data.
  • An information processing method is provided, comprising: generating data.
  • the computer determines multiple sets of usage start times and usage end times of data used for positioning processing for observation data acquired by a mobile station and including signals received from navigation satellites. Then, based on the observation data used by the plurality of sets and the observation data of the reference station, a plurality of positioning data are calculated by a positioning process, and final positioning data is generated based on the plurality of positioning data.
  • a program is provided that functions as a control unit.
  • FIG. 1 is a diagram illustrating an overview of a positioning system according to an embodiment of the present disclosure.
  • FIG. 1 is a block diagram showing an example of the configuration of a moving body 10 according to the present embodiment.
  • FIG. 2 is a block diagram showing an example of the configuration of an information processing device 20 according to the present embodiment.
  • FIG. 7 is a diagram illustrating an example of solution data (positioning data) of positioning processing when unstable data is not removed.
  • FIG. 7 is a diagram illustrating an example of solution data (positioning data) of positioning processing when unstable data is removed based on takeoff and landing times according to the present embodiment.
  • FIG. 6 is a diagram illustrating an improvement in the accuracy of positioning data when the use start time and use end time are determined based on the shooting start and end time according to the present embodiment.
  • FIG. 7 is a diagram illustrating an improvement in accuracy of positioning data when a use start time and a use end time are determined by adding a predetermined margin time to the shooting start and end time according to the present embodiment. It is a figure showing an example of the number of satellites observed by mobile object 10 according to this embodiment.
  • FIG. 6 is a diagram illustrating an improvement in the accuracy of positioning data when the use start time and use end time are determined based on the start and end time of securing a predetermined number of observation satellites according to the present embodiment. It is a figure which shows an example of the Fix rate of several positioning data by embodiment.
  • FIG. 6 is a diagram illustrating generation of final positioning data by connecting Fix solutions according to the present embodiment. It is a figure which shows the comparison result of the Fix solution in several observation data by this embodiment.
  • 7 is a flowchart illustrating an example of the flow of input waveform data generation processing according to the present embodiment.
  • FIG. 1 is a diagram illustrating an overview of a positioning system according to an embodiment of the present disclosure.
  • the positioning system includes a mobile body 10, which is an example of a mobile station, a reference station 3, and an information processing device 20.
  • the mobile body 10 and the reference station 3 each receive signals from a plurality of navigation satellites 2 (2a, 2b).
  • the data acquired by the mobile object 10 and including signals received from a plurality of navigation satellites 2 is referred to as mobile station observation data
  • the data acquired by the reference station 3 and including signals received from a plurality of navigation satellites 2 is referred to as reference station observation data. It is called.
  • the reference station 3 may be, for example, a base station installed on the ground, or may be any base station that can obtain a Log equivalent to a base station, such as an electronic reference point or a virtual reference point.
  • a PPK (Post Processing Kinematic) positioning method is used as an example, which achieves more accurate positioning by correcting mobile station observation data later based on reference station observation data.
  • the PPK positioning method communication between the mobile object 10 and the reference station is not required, so a radio license is not required for observation, and the observation location can be determined without considering whether communication with the reference station is possible. Furthermore, it is possible to avoid limitations in data quality (decrease in positioning accuracy) due to poor communication conditions with the reference station.
  • the mobile object 10 has a function of moving within space by autonomous movement.
  • the mobile object 10 may be, for example, a small flying object (a so-called drone) that autonomously flies in space, such as an unmanned aerial vehicle (UAV).
  • the mobile object 10 has a GNSS receiver and receives (observation) signals from the navigation satellite 2 (GNSS satellite).
  • GNSS satellites include satellites of various countries, such as GPS (Global Positioning System), quasi-zenith satellites, GLONASS, and Galileo.
  • FIG. 1 shows two satellites, the navigation satellite 2a and the navigation satellite 2b, as an example, the present invention is not limited to this.
  • the mobile object 10 estimates its own position (that is, the position of an observation point, data indicating latitude and longitude in this embodiment) by independent positioning that calculates the position based on signals received from four or more navigation satellites 2, and flies autonomously. It is possible.
  • the mobile object 10 may be provided with an imaging unit 130 that performs aerial photography automatically or in response to a user's operation during autonomous flight (autonomous movement).
  • an imaging unit 130 that performs aerial photography automatically or in response to a user's operation during autonomous flight (autonomous movement).
  • three-dimensional display can be realized using the plurality of captured images acquired by the imaging unit 130. Such a plurality of captured images are used, for example, to create a three-dimensional map.
  • the imaging unit 130 is provided in the moving body 10, but the present disclosure is not limited thereto.
  • the information processing device 20 calculates the relative positional relationship between two points (observation point and reference point) based on the mobile station observation data acquired by the mobile object 10 and the reference station observation data acquired by the reference station 3.
  • the position (latitude and longitude) of the observation point is calculated by the relative positioning obtained.
  • Relative positioning is more accurate than independent positioning. For example, a plurality of captured images acquired by the above-mentioned imaging unit 130 are added with the imaging time and location information (also referred to as a geotag) of the imaging point, but at the time of imaging, the position calculated by independent positioning is Information is added and can be subsequently updated to more accurate coordinates (location information) based on the results of the relative positioning.
  • Relative positioning includes DGPS (Differential GPS), which performs positioning independently with multiple receivers and calculates the relative position from the position information of each, and DGPS (Differential GPS), which calculates the relative position from the position information of each receiver.
  • DGPS Different GPS
  • interferometric positioning that determines the relative position between receivers, and generally has higher accuracy than DGPS.
  • interferometric positioning is used in post-processing. More specifically, the PPK positioning method, which is an example of interferometric positioning, is used to correct the data recorded by the mobile object 10 with the data acquired from the reference station 3, thereby achieving more accurate positioning.
  • Patent Document 1 discloses predicting the elevation angle of a satellite during observation and receiving signals from a plurality of satellites exceeding a predetermined angle threshold. No consideration is given to improving accuracy.
  • the accuracy of positioning processing is improved by removing unstable data from observation data and using (stable) observation data in an appropriate range for post-processing.
  • a plurality of appropriate ranges of observation data i.e., each usage observation data based on multiple sets of usage start times and usage end times
  • a solution is obtained for each, and multiple Further accuracy improvement can be achieved by generating final positioning data from the solution.
  • FIG. 2 is a block diagram showing an example of the configuration of the mobile object 10 according to this embodiment.
  • the mobile object 10 includes a control section 110, a position sensor 120, an imaging section 130, an altitude sensor 140, a storage section 150, a communication section 160, and a flight mechanism 170.
  • Control unit 110 The control unit 110 functions as an arithmetic processing device and a control device, and controls overall operations within the mobile body 10 according to various programs.
  • the control unit 110 is realized by, for example, an electronic circuit such as a CPU (Central Processing Unit) or a microprocessor. Further, the control unit 110 may include a ROM (Read Only Memory) that stores programs to be used, calculation parameters, etc., and a RAM (Random Access Memory) that temporarily stores parameters that change as appropriate.
  • ROM Read Only Memory
  • RAM Random Access Memory
  • the control unit 110 also functions as a self-position estimation unit 111, a flight control unit 112, and an observation data storage control unit 113.
  • the self-position estimating unit 111 estimates the self-position based on the data acquired by the position sensor 120.
  • the self-position estimation unit 111 uses GNSS (Global Navigation Satellite System) to calculate latitude and longitude data as the self-position. More specifically, the self-position estimation unit 111 may estimate the self-position by independent positioning that calculates the position based on signals received from four or more navigation satellites 2 (GNSS satellites).
  • GNSS Global Navigation Satellite System
  • the flight control unit 112 controls the flight mechanism 170 to achieve autonomous flight. Specifically, the flight control unit 112 controls the flight mechanism 170 based on the position and attitude of the moving body 10 so that the moving body 10 is in a target state (position, attitude). For example, the flight control unit 112 controls the vehicle to move along a movement route from its own position estimated by the control unit 110 to a predetermined movement target position.
  • the travel route may be a flight route that is newly set and stored in the storage unit 150.
  • the flight control unit 112 is not limited to autonomous flight along a flight route, but can also perform flight control according to user instructions received via the communication unit 160.
  • the attitude (YAW angle) of the moving body 10 is obtained, for example, by an attitude sensor (not shown) such as a gyro sensor or an electronic compass mounted on the moving body 10.
  • the observation data storage control unit 113 controls the storage of observation data including the signal received from the navigation satellite 2 by the position sensor 120 in the storage unit 150.
  • receiving a signal from the navigation satellite 2 is referred to as observation.
  • the point where the signal is received is called an observation point.
  • the moving object 10 can be continuously observed while flying (moving) along a flight path.
  • Observation data also includes signal reception time.
  • the observation data also includes altitude information of the mobile object 10 at the time of observation.
  • control unit 110 performs control to store control logs related to flight and imaging, and captured images obtained by the imaging unit 130 in the storage unit 150 in addition to observation data. So-called Exif information such as the imaging time and a geotag (location information calculated by the self-position estimating unit 111) is added to the captured image.
  • Position sensor 120 is a receiver that receives data used to calculate position. As an example, this is realized by a GNSS receiver that receives navigation satellites 2 such as GPS, quasi-zenith satellites, GLONASS, Galileo, and BeiDou. The signal received from the navigation satellite 2 by the position sensor 120 is stored in the storage unit 150 as observation data. Further, such a signal is also used for self-position estimation by the self-position estimating section 111.
  • the imaging unit 130 includes one or more lenses (optical system) and an imaging device such as a CCD or CMOS, and performs aerial photography automatically or in response to a user's operation during flight.
  • an imaging device such as a CCD or CMOS
  • the altitude sensor 140 calculates the altitude of the mobile object 10 and outputs it to the control unit 110.
  • the altitude sensor 140 is realized by, for example, an atmospheric pressure sensor.
  • the altitude sensor 140 can measure changes in atmospheric pressure and calculate the height of the mobile object 10 (from the ground).
  • the storage unit 150 is realized by a ROM (Read Only Memory) that stores programs, calculation parameters, etc. used in the processing of the control unit 110, and a RAM (Random Access Memory) that temporarily stores parameters that change as appropriate.
  • the storage unit 250 can store flight routes, observation data, captured images, and the like.
  • the communication unit 160 communicates with an external device to transmit and receive data.
  • the communication unit 160 uses, for example, a wired/wireless LAN (Local Area Network), Wi-Fi (registered trademark), Bluetooth (registered trademark), a mobile communication network (LTE (Long Term Evolution), 4G (fourth generation mobile 5G (5th generation mobile communication system)), etc.
  • the communication unit 160 receives flight route information and user operations from the information processing device 20, and also transmits observation data and captured images to the information processing device 20.
  • the flight mechanism 170 is a mechanism for making the mobile body 10 fly.
  • the flight mechanism 170 includes, for example, one or more motors driven by energy supplied from a battery (not shown) mounted on the moving object 10 and one or more propellers (for example, four rotors).
  • the flight mechanism 170 is driven under the control of the flight control unit 112 and allows the mobile object 10 to fly.
  • the configuration of the mobile body 10 has been specifically described above. Note that the configuration of the mobile body 10 according to this embodiment is not limited to the example shown in FIG. 2.
  • the moving body 10 may be provided with an acceleration sensor, a magnetic sensor (an example of a direction sensor), and an obstacle detection sensor (for example, an optical sensor) that detects obstacles.
  • the moving body 10 can fly while avoiding obstacles using an obstacle detection sensor.
  • the sensing result of the obstacle detection sensor may be included in the observation data and stored in the storage unit 150.
  • the moving body 10 may have a configuration that does not include the imaging unit 130.
  • the moving object 10 may have a removable storage medium, and observation data and captured images may be written in the storage medium. Further, each function of the control unit 110 may be realized by a separate processor.
  • FIG. 3 is a block diagram showing an example of the configuration of the information processing device 20 according to this embodiment.
  • the information processing device 20 includes a communication section 210, a control section 220, an operation input section 230, a display section 240, and a storage section 250.
  • the communication unit 210 communicates with an external device and sends and receives data. Further, the communication unit 210 is configured to use, for example, a wired/wireless LAN (Local Area Network), Wi-Fi (registered trademark), Bluetooth (registered trademark), mobile communication network (LTE (Long Term Evolution), 4G (fourth generation It is possible to connect to a network using 5G (5th generation mobile communication system), etc.
  • the communication unit 210 receives observation data from the mobile object 10 via wireless communication.
  • the communication unit 210 transmits user operation information to the mobile body 10 by wireless communication.
  • the communication unit 210 also receives observation data from the reference station 3 via the Internet.
  • Control unit 220 The control unit 220 functions as an arithmetic processing device and a control device, and controls overall operations within the information processing device 20 according to various programs.
  • the control unit 220 is realized by, for example, an electronic circuit such as a CPU (Central Processing Unit) or a microprocessor. Further, the control unit 220 may include a ROM (Read Only Memory) that stores programs to be used, calculation parameters, etc., and a RAM (Random Access Memory) that temporarily stores parameters that change as appropriate.
  • ROM Read Only Memory
  • RAM Random Access Memory
  • the control unit 220 also functions as a mobile station observation data acquisition unit 221, a reference station observation data acquisition unit 222, a usage time determination unit 223, a positioning processing unit 224, a precision improvement unit 225, and a display control unit 226. .
  • the mobile station observation data acquisition unit 221 acquires mobile station observation data obtained by the mobile object 10.
  • the mobile station observation data acquisition unit 221 may receive mobile station observation data from the mobile body 10 via wireless communication via the communication unit 210.
  • the mobile station observation data acquisition unit 221 may read the mobile station observation data from a storage medium such as an SD (Secure Digital) memory card that is taken out from the mobile object 10 and inserted into the information processing device 20.
  • SD Secure Digital
  • the reference station observation data acquisition unit 222 acquires the reference station observation data obtained by the reference station 3.
  • the reference station observation data acquisition unit 222 may connect to the Internet via the communication unit 210 and download the mobile station observation data from a server in which the reference station observation data obtained by the reference station 3 is stored.
  • a base station installed on the ground is assumed as an example of the reference station 3, but the base station is not limited to this, and it is possible to obtain a log equivalent to a base station, such as an electronic reference point or a virtual reference point. There may be.
  • the user specifies from which reference station 3 and when the mobile station observation data is to be acquired.
  • the user operates to obtain mobile station observation data corresponding to the date and time of flight, which is obtained by the reference station 3 located near the location where the mobile object 10 was flown.
  • the usage time determining unit 223 has a function of determining multiple sets of usage start times and usage end times of observation data used for positioning processing, which will be described later, for mobile station observation data. By determining the usage start time and usage end time by the usage time determination unit 223, unstable data can be excluded from the observation data, and stable and appropriate data can be obtained in the positioning process described later. In this embodiment, several criteria for determining unstable data are set, and based on each criterion, observation data in a plurality of appropriate ranges (i.e., each usage observation data with multiple sets of usage start time and usage end time) is set. ), and the positioning processing unit 224 obtains each solution, so that the later-described high-precision unit 225 finally generates more accurate positioning data from the multiple solutions obtained by the positioning processing unit 224. can do.
  • the usage time determining unit 223 can determine multiple sets of usage start times and usage end times using multiple criteria described below.
  • the use time determining unit 223 may determine the use start time and use end time based on the movement start and end time of the mobile body 10 (mobile station).
  • the movement start and end times are, for example, the takeoff and landing times of the mobile body 10.
  • the use time determining unit 223 determines the takeoff time (movement start time) of the mobile object 10 as the use start time of the observation data, and the landing time (movement end time) as the use end time of the observation data.
  • FIG. 4 is a diagram showing an example of solution data (positioning data) of positioning processing when unstable data is not removed.
  • the mobile object 10 performs observation (reception of signals from the navigation satellite 2) with obstacles such as people in the vicinity of the mobile object 10. is performed, and unstable data may be obtained.
  • FIG. 4 data indicating the latitude and longitude of each observation point (including each observation point on the flight route) observed by the mobile object 10 is shown as solution data of the positioning process.
  • a Float solution or a Fixed solution is obtained for the position information (data indicating latitude and longitude) of each observation point.
  • the Fix solution is a solution with higher accuracy (fewer errors) than the Float solution, and the height of the Fix rate (ratio of Fix solutions to all solutions) is a measure of the positioning accuracy. It is desirable to obtain as many highly accurate solutions (Fix solutions) as possible. In this embodiment, the height of positioning accuracy will be explained using a fix rate as an example.
  • an integer value bias (N) is calculated in the process of calculating the number of L (carrier phase).
  • the integer bias is the true ambiguity (the distance between the satellite and the receiver at the beginning of the observation), and should be an integer multiple of the carrier wavelength (an integer, that is, there is no part below the decimal point), but it must be determined from the beginning. Therefore, a calculation method for obtaining an approximate solution (for example, the LAMBDA method; the least-squares ambiguity decorrelation adjustment) is used.
  • the solution positioning data; data indicating latitude and longitude
  • the integer value bias is A solution obtained using integer values
  • the calculation method generally used to find the integer bias is a successive approximation method, so the integer bias is fixed during the period when the carrier wave can be observed continuously (i.e., the solution once found is used in calculations). Therefore, an incorrect solution may adversely affect subsequent calculations, leading to an incorrect solution (decreased accuracy).
  • FIG. 5 is a diagram showing an example of solution data (positioning data) of the positioning process when unstable data is removed based on takeoff and landing times according to the present embodiment.
  • unstable observation data before and after take-off and landing is removed, that is, used observation data that is extracted using the take-off time as the start time of use and the landing time as the end time of use, for example, is used for positioning processing.
  • This makes it possible to reduce the negative influence of unstable data on calculations and increase the fix rate.
  • the calculation result of a fix rate of 98.7% shown in FIG. 5 is an example, an experimental result was obtained in which the fix rate is higher than at least when all observation data is used.
  • the use time determination unit 223 may determine the use start time and use end time by further subtracting a predetermined time from the takeoff and landing time. That is, the use time determination unit 223 may set a predetermined time after takeoff time as the use start time, and a predetermined time before landing time as the use end time.
  • the takeoff and landing times can be determined from the control log acquired from the mobile object 10.
  • the information processing device 20 can also acquire the control log of the mobile object 10 together with the mobile station observation data.
  • the control log includes data related to flight control, and allows acquisition of takeoff and landing times.
  • the use time determining unit 223 can also determine the takeoff and landing times based on the altitude information of the mobile object 10.
  • the altitude information of the mobile object 10 is included in, for example, mobile station observation data.
  • the use time determining unit 223 may set the time when the altitude of the mobile body 10 exceeds a predetermined value as the use start time, and the time when the altitude of the mobile body 10 falls below the predetermined value as the use end time. This makes it possible to exclude unstable data due to insufficient altitude.
  • the use time determining unit 223 may determine the use start time and use end time based on the shooting start and end time of the mobile object 10 (mobile station).
  • the usage time determining unit 223 determines the imaging start time of the mobile object 10 as the observation data usage start time, and the imaging end time as the observation data usage end time.
  • the shooting start and end times may be obtained from the control log obtained from the moving object 10 or from Exif information added to the captured image. It is assumed that photography will be carried out at a target point or in good conditions, such as when the altitude of the mobile object 10 has reached a sufficient height or when the flight is stable, and the observation data while photography is being performed. By using this method, it is expected that the negative impact on positioning processing due to unstable observation data before the start of shooting or after the end of shooting can be reduced.
  • FIG. 6 is a diagram illustrating the improvement in accuracy of positioning data when the use start time and use end time are determined based on the shooting start and end times according to the present embodiment.
  • the left side of FIG. 6 shows the results of positioning processing (positioning data) without time designation, that is, when all observation data are used.
  • the fix rate which indicates high positioning accuracy, was 48.2%.
  • the fix rate is 98.3%, and the positioning accuracy is improved.
  • the use time determining unit 223 may determine the use start time and use end time by adding a predetermined margin time (for example, several seconds to several tens of seconds) to the shooting start and end time. In other words, the use time determining unit 223 may set a predetermined time before the shooting start time as the use start time, and may set a predetermined time after the shooting end time as the use end time.
  • a predetermined margin time for example, several seconds to several tens of seconds
  • FIG. 7 is a diagram illustrating an improvement in accuracy of positioning data when the use start time and use end time are determined by adding a predetermined margin time to the shooting start and end time according to the present embodiment.
  • the left side of FIG. 7 shows the results of positioning processing (positioning data) without time designation, that is, when all observation data are used.
  • the fix rate which indicates high positioning accuracy, was 48.2%.
  • the fix rate is 99.2%, and the positioning accuracy is improved.
  • the fix rates shown in Figures 6 and 7 are just experimental results, but in any case, by using the observation data that is trimmed based on the shooting start and end time for positioning processing, at least when all observation data is used. It is clear that the fix rate increases compared to Note that here, since the photographing is performed by the moving object 10, the photographing start and end time is used, but this is not limited to this, and if the purpose of the flight is to acquire some information other than photographing (various sensing), that information may be used. The acquisition start and end time may also be used.
  • the use time determining unit 223 determines the start time and end time for use based on the start and end time for securing a predetermined number of observation satellites by the mobile object 10 (mobile station). good. This is because the fewer the number of satellites that can be observed, the more likely the data will be unstable.
  • the use time determining unit 223 determines the start time for securing the predetermined number of observation satellites by the mobile object 10 as the start time for using the observation data, and the end time for securing the predetermined number of observation satellites as the end time for using the observation data.
  • the start and end time of securing a predetermined number of observation satellites by the mobile body 10 (mobile station) is obtained from the observation data acquired from the mobile body 10.
  • FIG. 8 is a diagram showing an example of the number of satellites observed by the mobile object 10 according to the present embodiment.
  • the observation data also includes data on the number of satellites observed by the mobile object 10, as shown in FIG.
  • "observed” means that a signal could be received. That is, the number of satellites observed by the mobile body 10 is the number of navigation satellites 2 whose signals could be received by the mobile body 10.
  • the predetermined number of observation satellites may be the maximum number of antennas of the position sensor 120 provided on the mobile object 10.
  • the position sensor 120 is, for example, a GNSS receiver, and its maximum number of antennas (the number of satellites that can be received) may be set as the predetermined number of observation satellites.
  • the maximum number of antennas is 24, and the use time determining unit 223 determines that the use start time is 5:19:02 when 24 antennas can be observed, and 5:19:02 when 24 antennas can no longer be observed. 23 minutes and 16 seconds is determined as the end time of use. Note that the time when the number of observation satellites temporarily decreases (very short time) may be ignored.
  • FIG. 9 is a diagram illustrating the improvement in accuracy of positioning data when the use start time and use end time are determined based on the start and end time of securing a predetermined number of observation satellites according to the present embodiment.
  • the left side of FIG. 9 shows the results of positioning processing (positioning data) without time specification, that is, when all observation data are used. In this case, the fix rate, which indicates high positioning accuracy, was 48.2%.
  • the fix rate is 99.1%, and the positioning accuracy is improved.
  • the usage time determination unit 223 may count the number of satellites that can be observed by the mobile object 10 when the same satellite can be observed by the reference station. In the positioning process described later, the reference station observation data at the corresponding time is also used, so the stability of the observation data of the reference station 3 is also required.
  • the use time determining unit 223 considers the reference station observation data and counts the number of observed satellites as 1 if the same navigation satellite 2 can be observed by the mobile object 10 and the reference station 3. This makes it possible to use more stable observation data.
  • the use time determination unit 223 uses observation data obtained by dividing the observation data so as to exclude a portion where the number of observation satellites temporarily decreases between the start time of securing a predetermined number of observation satellites and the end time of securing a predetermined number of observation satellites. You can also cut it out.
  • the usage time determining unit 223 stores the first usage observation data from the start of securing a predetermined number of observation satellites to a first intermediate time when the number of observation satellites temporarily decreases: A, and the number of observation satellites restored.
  • the second used observation data from the second intermediate time: B to the end time of reservation may be extracted from the mobile station observation data.
  • the usage time determination unit 223 selects the first usage observation data, the second usage observation data, and the third usage observation data (secured from the start time of securing the predetermined number of observation satellites) without excluding any part of the usage data.
  • observation data up to the end time are output to the positioning processing unit 224.
  • the positioning processing unit 224 performs a positioning process using the first used observation data, a positioning process using the second used observation data, and a positioning process using the third used observation data.
  • the observation data from the first intermediate time: A to the second intermediate time: B is unstable data, positioning processing should be performed separately for the first used observation data and the second used observation data. Therefore, the influence of the unstable data is reduced.
  • the positioning processing unit 224 uses the results of the positioning process using the first observation data to be used, the results of the positioning process using the second observation data to be used, and the results of the positioning process using the third observation data to be used.
  • the usage time determination unit 223 determines the usage start time and usage end time based on the signal strength (strength of the signal received from the navigation satellite 2) at the time of observation by the mobile object 10 (mobile station). You may.
  • the usage time determination unit 223 determines the time when the signal strength exceeds a predetermined value as the observation data usage start time, and the time when the signal strength falls below the predetermined value as the observation data usage end time. Information on signal strength is obtained from observation data obtained from the mobile object 10. Note that the time (very short time) during which the signal strength temporarily falls below a predetermined value may be ignored. Further, the usage time determining unit 223 may cut out the usage observation data divided by excluding a certain period of time during which the signal strength was lower than a predetermined value. In this case, the positioning processing unit 224 obtains partial but highly accurate positioning data.
  • the usage time determining unit 223 may determine the usage start time and usage end time based on the environment at the time of observation by the mobile object 10 (mobile station). It is conceivable that the observation data to be used may be observation data in a favorable environment, such as less multipath and no nearby objects (obstacles).
  • the use time determining unit 223 determines the time when the environment of the mobile object 10 satisfies a predetermined condition as the observation data use start time, and the time when the environment no longer satisfies the predetermined condition as the observation data use end time.
  • the predetermined conditions include, for example, that there are few multipaths and that there are no obstacles.
  • the environment information is obtained from observation data acquired from the mobile object 10, a control log, and a log separately recorded by the user during observation. Note that a time (very short time) during which the environment temporarily does not satisfy the predetermined conditions may be ignored. Further, the use time determination unit 223 may cut out the usage observation data divided by excluding a certain period during which the environment does not satisfy a predetermined condition. In this case, the positioning processing unit 224 obtains partial but highly accurate positioning data.
  • the use time determining unit 223 uses a plurality of the above criteria to determine a plurality of sets of use start times and use end times, and outputs a plurality of use observation data to the positioning processing unit 224. For example, the usage time determining unit 223 outputs the usage observation data trimmed at the shooting start and end time and the usage observation data trimmed at the securing start and end time of the number of observation satellites to the positioning processing unit 224.
  • the positioning processing unit 224 performs positioning processing based on the plurality of usage observation data based on the plurality of sets of usage start time and usage end time determined by the usage time determination unit 223 and the observation data of the reference station 3. Calculate positioning data.
  • the positioning process according to this embodiment uses the PPK positioning method as an example.
  • the calculated positioning data is data indicating the latitude and longitude of each observation point.
  • the positioning processing unit 224 performs positioning processing multiple times on one observation data using a filter (also referred to as a parameter set) that distributes various parameters such as a noise threshold. (positioning processing using different filters) may be executed. As a result, even more positioning data (number of observation data used x number of filters) is output.
  • Filters used in positioning processing using the PPK positioning method include, for example, a signal-to-noise ratio threshold (SNR (Signal-to-Noise Ratio) mask), a satellite elevation angle threshold (Elevation Mask), and a mask based on the type of observation satellite (Glonass is Various combinations of masks are possible, such as (excluding, etc.).
  • SNR Signal-to-noise ratio threshold
  • Eleation Mask Satellite elevation angle threshold
  • GaNass is Various combinations of masks are possible, such as (excluding, etc.).
  • the mask described here is an example, and the present embodiment is not limited thereto.
  • the precision improvement unit 225 generates final positioning data based on the plurality of positioning data output from the positioning processing unit 224.
  • further accuracy improvement can be achieved by generating one piece of highly accurate positioning data based on a plurality of pieces of positioning data.
  • the precision improvement unit 225 sets the positioning data with the highest fix rate (that is, the highest accuracy) among the plurality of positioning data as the final positioning data.
  • the precision improvement unit 225 calculates using a stronger filter (positioning process). It is also possible to give priority to the one that has been set and use it as the final positioning data. That is, the precision improvement unit 225 may select the final positioning data from a plurality of positioning data according to the precision of the positioning data and the strength of the filter used in the positioning process.
  • FIG. 10 is a diagram illustrating an example of the fix rate of a plurality of positioning data according to the embodiment.
  • a plurality of positioning data according to the present embodiment can be calculated by a combination of a plurality of used observation data and filters.
  • a strong filter e.g., Elevation Mask 25° (meaning that signals from satellites with an elevation angle of 25° or less are excluded)
  • the Fix of positioning data d1 The rate became 100%.
  • the fix rate of the positioning data d2 was 53.9%. It became.
  • the fix rate of the positioning data d3 was 66%.
  • the fix rate of the positioning data d4 was 100%, as shown in FIG. 10. Furthermore, when using the same weak filter (EL mask 15°) for the observation data used that was trimmed with a margin of 10 seconds at the shooting start and end time, the fix rate of positioning data d5 was 84.6%. It became. Furthermore, when the same weak filter (EL mask 15°) was used for the used observation data that was trimmed at the start and end time of securing a predetermined number of observation satellites, the fix rate of the positioning data d6 was 100%.
  • a weak filter for example, EL mask 15°
  • the precision improvement unit 225 adopts any of the positioning data d1, d4, and d6 with a fix rate of 100% as the final positioning data.
  • the precision improvement unit 225 may employ the positioning data d1 calculated using the strongest filter as the final positioning data. This is because it is thought that by using the strongest filter, more accurate observation data with less noise is used for positioning processing.
  • the precision improvement unit 225 performs positioning processing using a stronger filter, and obtains positioning data with a certain fix rate (for example, 95% or more) (i.e., a certain accuracy). The positioning process may be completed in stages. Further, the precision improvement unit 225 may perform positioning processing a re-set number of times. In this case, the precision improvement unit 225 may employ positioning data with the highest fix rate, or may employ positioning data with a fixed fix rate (for example, 95% or more). If positioning data with a constant fix rate is not obtained, the precision improvement unit 225 may continue to perform positioning processing until it is obtained. Note that the fix rate of each positioning data shown in FIG. 10 is one experimental result, and the present embodiment is not limited to this.
  • FIG. 11 is a table that compares the fix rate of positioning data when the observation data used according to the present embodiment is trimmed and when it is not trimmed.
  • the example shown in FIG. 11 further shows the fix rate of positioning data when a filter including a set of various masks is used when positioning processing is performed using each observation data used.
  • a GLONASS satellite mask (whether GLONASS satellites are used), an SNR mask, and an EL mask are used as the filter.
  • the highest fix rate using various filters without trimming is 41.9%
  • the highest fix rate using various filters with trimming is 100%, making the overall fix rate 41.9%.
  • Positioning accuracy has improved from 100% to 100%.
  • the precision improvement unit 225 may generate final positioning data by combining Fix solutions (parts with high accuracy) among the plurality of positioning data. For example, the precision improvement unit 225 may partially connect the Fix solutions to generate one piece of positioning data.
  • FIG. 12 is a diagram illustrating generation of final positioning data by connecting Fix solutions according to this embodiment.
  • the broken line forming the positioning data is the Float solution
  • the solid line is the Fix solution.
  • the precision improvement unit 225 synthesizes fixed solution parts from a plurality of positioning data partially including fixed solutions as shown in the upper part of FIG. 12 so as to complement each other (the float solution parts), and It is possible to generate all fixed solution positioning data as shown.
  • the fix solution may be extracted from positioning data having a constant fix rate or positioning data using a filter with a constant strength.
  • the precision improvement unit 225 may compare each piece of positioning data and exclude positioning data that includes a fix solution that is clearly different from other fix solutions.
  • FIG. 13 is a diagram showing a comparison result of Fix solutions in a plurality of observation data according to this embodiment.
  • Z coordinates are compared. All the Z coordinate values used here are fixed solutions, but it can be seen that only data 5 is clearly different from data 1 to data 4. Thereby, there is a high possibility that data 5 is an incorrect Fix solution, and by excluding data 5, positioning accuracy can be further improved.
  • the precision improvement unit 225 may compare not only the Fix solution but also the Float solution. Since an incorrect Fix solution may have a larger error than a Float solution, the Float solution may also be used as a reference.
  • the generation of final positioning data by the precision improvement unit 225 has been described above. Thereby, the accuracy of positioning data can be further improved (higher accuracy).
  • the highly accurate positioning data may be stored in the storage unit 250.
  • the display control unit 226 performs control to display the positioning data whose accuracy has been improved by the accuracy improvement unit 225 on the display unit 240.
  • the output of highly accurate positioning data is displayed as an example of output, but the output of highly accurate positioning data is not limited to display.
  • highly accurate positioning data may be transmitted from the communication unit 210 to an external device.
  • the operation input unit 230 attaches an operation from the user and outputs input information to the control unit 220.
  • the operation input unit 230 is realized by various input devices such as a touch panel, a button, a switch, a keyboard, etc., for example.
  • the display unit 240 has a function of displaying various screens such as an operation screen and a screen containing highly accurate final positioning data.
  • the display unit 240 may be realized by, for example, a liquid crystal display (LCD) device, an organic light emitting diode (OLED) device, or the like.
  • the storage unit 250 is realized by a ROM (Read Only Memory) that stores programs, calculation parameters, etc. used in the processing of the control unit 220, and a RAM (Random Access Memory) that temporarily stores parameters that change as appropriate.
  • ROM Read Only Memory
  • RAM Random Access Memory
  • the configuration of the information processing device 20 has been specifically described above. Note that the configuration of the information processing device 20 according to this embodiment is not limited to the example shown in FIG. 3.
  • the information processing device 20 may be realized by a plurality of devices.
  • the functions of the mobile observation data acquisition section 121, the reference station observation data acquisition section 122, the usage time determination section 123, and the positioning processing section 124, and the function of the precision improvement 125 may be realized by different devices.
  • at least one configuration of the information processing device 20 may be provided in an external device. Further, the information processing device 20 does not need to have all the configurations shown in FIG. 3.
  • FIG. 14 is a flowchart illustrating an example of the flow of input waveform data generation processing according to this embodiment.
  • the information processing device 20 first obtains observation data (mobile station observation data) of the mobile object 10 (step S103). Subsequently, the information processing device 20 determines a plurality of sets of usage start times and usage end times of usage observation data used for positioning processing for the acquired observation data (mobile station observation data) of the mobile object 10 (step S106).
  • the information processing device 20 calculates a plurality of positioning data (positioning process) using the plurality of used observation data and the observation data of the reference station (step S109). Next, the information processing device 20 improves the accuracy of the positioning data based on the plurality of positioning data (step S112).
  • the information processing device 20 outputs (displays) highly accurate positioning data (step S115). Then, this operation ends.
  • the positioning process by performing the positioning process multiple times with different filters for each observation data used, it is possible to further calculate a plurality of positioning data and improve the positioning accuracy of the final positioning data.
  • the observation data that has been trimmed from the observation data leads to a reduction in the amount of data used in the positioning process, which also has the effect of shortening the processing time. For example, when the observation data to be used is trimmed based on the shooting start and end time, the length of the data may become half of the total observation data.
  • one or more computer programs for causing hardware such as a CPU, ROM, and RAM built in the mobile body 10 or the information processing device 20 described above to exhibit the functions of the mobile body 10 or the information processing device 20. can also be created. Also provided is a computer readable storage medium storing the one or more computer programs.
  • the present technology can also have the following configuration. (1) Determining multiple sets of usage start times and usage end times of data used for positioning processing for observation data acquired by a mobile station and including signals received from navigation satellites, Calculating a plurality of positioning data through positioning processing based on the observation data used by the plurality of sets and the observation data of the reference station, generating final positioning data based on the plurality of positioning data; An information processing device including a control unit. (2) The information processing device according to (1), wherein the control unit uses a plurality of filters in the positioning process to calculate a plurality of positioning data for each used observation data.
  • the control unit sets the use start time and use end time to a start and end time of movement of the mobile station, a start and end time of photographing by the mobile station, and a start and end time of securing a predetermined number of observation satellites by the mobile station.
  • the control unit determines the use start time and the use end time by adding a predetermined margin time to the start and end time of photographing by the mobile station.
  • the information processing device according to any one of (1) to (9), wherein the observation data includes reception times of the signals continuously acquired by the mobile station while moving.
  • the control unit sets the most accurate positioning data among the plurality of positioning data as the final positioning data.
  • the control unit selects the final positioning data from among the plurality of positioning data according to the degree of accuracy and the strength of the filter used in the positioning process.
  • the information processing device according to item 1.
  • the control unit performs positioning processing using a stronger filter and ends the positioning processing when positioning data with a certain accuracy is obtained. Information processing device.
  • the information processing device wherein a PPK (Post Processing Kinematic) positioning method is used as the interferometric positioning method.
  • the processor determining a plurality of sets of usage start times and usage end times of data used for positioning processing for observation data acquired by a mobile station and including signals received from navigation satellites; Calculating a plurality of positioning data by a positioning process based on each observation data used by the plurality of sets and observation data of a reference station; Generating final positioning data based on the plurality of positioning data; information processing methods, including (20) computer, Determining multiple sets of usage start times and usage end times of data used for positioning processing for observation data acquired by a mobile station and including signals received from navigation satellites, Calculating a plurality of positioning data through positioning processing based on the observation data used by the plurality of sets and the observation data of the reference station, generating final positioning data based on the plurality of positioning data; A program that functions as a control unit.
  • (21) Determining multiple sets of usage start times and usage end times of data used for positioning processing for observation data acquired by a mobile station and including signals received from navigation satellites, calculating a plurality of positioning data through positioning processing based on the observation data used by the plurality of sets and the observation data of the reference station; An information processing device including a control unit.
  • (22) Positioning processing is performed based on the observation data obtained by the mobile station, including the signals received from the navigation satellite, and the observation data of the reference station and the observation data extracted from multiple sets of use start and end times.
  • An information processing device including a control unit that generates final positioning data based on a plurality of positioning data calculated by.

Abstract

[Problem] To provide an information processing device, an information processing method and a program capable of improving the accuracy of positioning processing. [Solution] This information processing device is provided with a control unit which: determines a plurality of sets of a usage start time and a usage end time of data used in positioning processing, with respect to observation data including a signal received from a navigation satellite, the observation data being acquired by a mobile station; calculates a plurality of items of positioning data by means of the positioning processing, on the basis of each item of usage observation data from the plurality of sets and observation data from a reference station; and generates final positioning data on the basis of the plurality of items of positioning data.

Description

情報処理装置、情報処理方法、およびプログラムInformation processing device, information processing method, and program
 本開示は、情報処理装置、情報処理方法、およびプログラムに関する。 The present disclosure relates to an information processing device, an information processing method, and a program.
 従来、航法衛星から受信した信号に含まれる情報を用いて自己位置を推定する技術が知られている。例えば下記特許文献1では、GNSS(Global Navigation Satellite System)の利用により自己位置を推定し、自己位置から所定の移動目標位置に至る移動経路に沿って移動する自律移動ロボットに関する技術が開示されている。 Conventionally, there is a known technology for estimating one's own position using information contained in signals received from navigation satellites. For example, Patent Document 1 below discloses a technology related to an autonomous mobile robot that estimates its own position by using GNSS (Global Navigation Satellite System) and moves along a movement route from its own position to a predetermined movement target position. .
 ここで、航法衛星が地平線の下に隠れたり建物の影に隠れたり等、航法衛星の位置によっては航法衛星からの信号を受信できず、一時的に測位精度が低下することがある。下記特許文献1では、測位開始時刻(現在時刻または5分後の時刻など)と測位終了時刻における各航法衛星の仰角を求め、仰角が所定の角度閾値以上となる複数の衛星を、受信可能な複数の航法衛星の組み合わせからなる衛星セットとして選択し、安定した精度で自己位置を推定している。また、下記特許文献1では、RTK(Real Time Kinematic)測位法と称される相対測位の一種が用いられている。RTK測位法では、移動局と固定局の2つのGNSS受信機で4つ以上の衛星から信号を受信し、移動局と固定局の間で情報を送受信してズレを補正することで、精度の高い位置情報を得る。 Here, depending on the position of the navigation satellite, such as when the navigation satellite is hidden below the horizon or hidden in the shadow of a building, the signal from the navigation satellite may not be received, and the positioning accuracy may temporarily decrease. In Patent Document 1 listed below, the elevation angle of each navigation satellite is determined at the positioning start time (current time, time 5 minutes later, etc.) and positioning end time, and a plurality of satellites whose elevation angles are equal to or greater than a predetermined angle threshold are determined to be receivable. A satellite set consisting of a combination of multiple navigation satellites is selected to estimate self-position with stable accuracy. Further, in Patent Document 1 listed below, a type of relative positioning called RTK (Real Time Kinematic) positioning method is used. In the RTK positioning method, two GNSS receivers, a mobile station and a fixed station, receive signals from four or more satellites, and information is sent and received between the mobile station and the fixed station to correct any discrepancies, thereby improving accuracy. Get high location information.
特開2017-182692号公報Japanese Patent Application Publication No. 2017-182692
 しかしながら、上記技術では、各衛星の位置のみを考慮して信号を受信する複数の衛星を選択して、安定した精度の自己位置の算出を目的としているが、位置測位に関してさらなる精度向上が求められる。 However, with the above technology, the aim is to calculate self-position with stable accuracy by selecting multiple satellites to receive signals by considering only the position of each satellite, but further improvement in accuracy is required for positioning. .
 本開示によれば、移動局により取得された、航行衛星から受信した信号を含む観測データに対して、測位処理に使用するデータの使用開始時刻および使用終了時刻を複数組決定し、前記複数組による各使用観測データと、基準局の観測データと、に基づいて、測位処理により複数の測位データを算出し、前記複数の測位データに基づいて、最終的な測位データを生成する、制御部を備える、情報処理装置が提供される。 According to the present disclosure, a plurality of sets of usage start times and usage end times of data used for positioning processing are determined for observation data acquired by a mobile station and including signals received from navigation satellites, and the plurality of sets of usage start times and usage end times are determined. and a control unit that calculates a plurality of positioning data through positioning processing based on the observation data used by the reference station and the observation data of the reference station, and generates final positioning data based on the plurality of positioning data. , an information processing device is provided.
 また、本開示によれば、プロセッサが、移動局により取得された、航行衛星から受信した信号を含む観測データに対して、測位処理に使用するデータの使用開始時刻および使用終了時刻を複数組決定することと、前記複数組による各使用観測データと、基準局の観測データと、に基づいて、測位処理により複数の測位データを算出することと、前記複数の測位データに基づいて、最終的な測位データを生成することと、を含む、情報処理方法が提供される。 Further, according to the present disclosure, the processor determines a plurality of sets of use start times and use end times of data used for positioning processing for observation data acquired by the mobile station and including signals received from navigation satellites. calculating a plurality of positioning data through positioning processing based on the observation data used by the plurality of sets and the observation data of the reference station; and calculating the final positioning data based on the plurality of positioning data. An information processing method is provided, comprising: generating data.
 また、本開示によれば、コンピュータを、移動局により取得された、航行衛星から受信した信号を含む観測データに対して、測位処理に使用するデータの使用開始時刻および使用終了時刻を複数組決定し、前記複数組による各使用観測データと、基準局の観測データと、に基づいて、測位処理により複数の測位データを算出し、前記複数の測位データに基づいて、最終的な測位データを生成する、制御部として機能させる、プログラムが提供される。 Further, according to the present disclosure, the computer determines multiple sets of usage start times and usage end times of data used for positioning processing for observation data acquired by a mobile station and including signals received from navigation satellites. Then, based on the observation data used by the plurality of sets and the observation data of the reference station, a plurality of positioning data are calculated by a positioning process, and final positioning data is generated based on the plurality of positioning data. A program is provided that functions as a control unit.
本開示の一実施形態による位置測位システムの概要について説明する図である。FIG. 1 is a diagram illustrating an overview of a positioning system according to an embodiment of the present disclosure. 本実施形態による移動体10の構成の一例を示すブロック図である。FIG. 1 is a block diagram showing an example of the configuration of a moving body 10 according to the present embodiment. 本実施形態による情報処理装置20の構成の一例を示すブロック図である。FIG. 2 is a block diagram showing an example of the configuration of an information processing device 20 according to the present embodiment. 不安定なデータを除かなかった場合における測位処理の解データ(測位データ)の一例を示す図である。FIG. 7 is a diagram illustrating an example of solution data (positioning data) of positioning processing when unstable data is not removed. 本実施形態による離着陸時刻に基づいて不安定なデータを除いた場合における測位処理の解データ(測位データ)の一例を示す図である。FIG. 7 is a diagram illustrating an example of solution data (positioning data) of positioning processing when unstable data is removed based on takeoff and landing times according to the present embodiment. 本実施形態による撮影開始終了時刻で使用開始時刻および使用終了時刻を決定した場合の測位データの精度向上について説明する図である。FIG. 6 is a diagram illustrating an improvement in the accuracy of positioning data when the use start time and use end time are determined based on the shooting start and end time according to the present embodiment. 本実施形態による撮影開始終了時刻に所定の余裕時間を追加して使用開始時刻および使用終了時刻を決定した場合の測位データの精度向上について説明する図である。FIG. 7 is a diagram illustrating an improvement in accuracy of positioning data when a use start time and a use end time are determined by adding a predetermined margin time to the shooting start and end time according to the present embodiment. 本実施形態による移動体10で観測した衛星数の一例を示す図である。It is a figure showing an example of the number of satellites observed by mobile object 10 according to this embodiment. 本実施形態による所定の観測衛星数の確保開始終了時刻で使用開始時刻および使用終了時刻を決定した場合の測位データの精度向上について説明する図である。FIG. 6 is a diagram illustrating an improvement in the accuracy of positioning data when the use start time and use end time are determined based on the start and end time of securing a predetermined number of observation satellites according to the present embodiment. 実施形態による複数の測位データのFix率の一例を示す図である。It is a figure which shows an example of the Fix rate of several positioning data by embodiment. 本実施形態による使用観測データの切り出し(トリミング)を行った場合と行わなかった場合の測位データのFix率を比較する表である。It is a table that compares the fix rate of positioning data when cutting out (trimming) the used observation data according to the present embodiment and when not cutting out (trimming) the used observation data. 本実施形態によるFix解の繋ぎ合わせによる最終的な測位データの生成について説明する図である。FIG. 6 is a diagram illustrating generation of final positioning data by connecting Fix solutions according to the present embodiment. 本実施形態による複数の観測データにおけるFix解の比較結果を示す図である。It is a figure which shows the comparison result of the Fix solution in several observation data by this embodiment. 本実施形態による入力波形データの生成処理の流れの一例を示すフローチャートである。7 is a flowchart illustrating an example of the flow of input waveform data generation processing according to the present embodiment.
 以下に添付図面を参照しながら、本開示の好適な実施の形態について詳細に説明する。なお、本明細書及び図面において、実質的に同一の機能構成を有する構成要素については、同一の符号を付することにより重複説明を省略する。 Preferred embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings. Note that, in this specification and the drawings, components having substantially the same functional configurations are designated by the same reference numerals and redundant explanation will be omitted.
 また、説明は以下の順序で行うものとする。
 1.概要
 2.構成例
  2-1.移動体10の構成
  2-2.情報処理装置20の構成
 3.動作処理
 4.効果
 5.補足
Further, the explanation shall be given in the following order.
1. Overview 2. Configuration example 2-1. Configuration of mobile body 10 2-2. Configuration of information processing device 20 3. Operation processing 4. Effect 5. supplement
 <<1.概要>>
 本開示の一実施形態による位置測位システムの概要について図1を参照して説明する。図1は、本開示の一実施形態による位置測位システムの概要について説明する図である。
<<1. Overview >>
An overview of a positioning system according to an embodiment of the present disclosure will be described with reference to FIG. 1. FIG. 1 is a diagram illustrating an overview of a positioning system according to an embodiment of the present disclosure.
 本実施形態による位置測位システムは、図1に示すように、移動局の一例である移動体10と、基準局3と、情報処理装置20と、を含む。移動体10および基準局3は、各々、複数の航法衛星2(2a、2b)から信号を受信する。移動体10により取得された、複数の航法衛星2から受信した信号を含むデータを移動局観測データ、基準局3により取得された、複数の航法衛星2から受信した信号を含むデータを基準局観測データ、と称する。基準局3は、例えば地上に設置される基地局であってもよいし、これに限らず、電子基準点や仮想基準点など、基地局相当のLogが取得できるものであればよい。本実施形態では、移動局観測データを後から基準局観測データに基づいて補正することで、より精度の高い位置測位を実現するPPK(後処理キネマティック;Post Processing Kinematic)測位法を一例として用いる。PPK測位法の場合、移動体10と基準局との通信が不要になるため、観測に無線免許が不要であり、また、基準局との通信可否を考慮せずに観測場所を決定することができる。また、基準局との通信状況の悪さによるデータ品質の制限(位置測位の精度の低下)も回避できる。 As shown in FIG. 1, the positioning system according to the present embodiment includes a mobile body 10, which is an example of a mobile station, a reference station 3, and an information processing device 20. The mobile body 10 and the reference station 3 each receive signals from a plurality of navigation satellites 2 (2a, 2b). The data acquired by the mobile object 10 and including signals received from a plurality of navigation satellites 2 is referred to as mobile station observation data, and the data acquired by the reference station 3 and including signals received from a plurality of navigation satellites 2 is referred to as reference station observation data. It is called. The reference station 3 may be, for example, a base station installed on the ground, or may be any base station that can obtain a Log equivalent to a base station, such as an electronic reference point or a virtual reference point. In this embodiment, a PPK (Post Processing Kinematic) positioning method is used as an example, which achieves more accurate positioning by correcting mobile station observation data later based on reference station observation data. In the case of the PPK positioning method, communication between the mobile object 10 and the reference station is not required, so a radio license is not required for observation, and the observation location can be determined without considering whether communication with the reference station is possible. Furthermore, it is possible to avoid limitations in data quality (decrease in positioning accuracy) due to poor communication conditions with the reference station.
 移動体10は、自律移動により空間内を移動する機能を有する。移動体10は、例えば、無人航空機(UAV;Unmanned aerial vehicle)等の空間内を自律飛行する小型の飛行体(いわゆるドローン)であってもよい。移動体10は、GNSS受信機を有し、航法衛星2(GNSS衛星)からの信号を受信する(観測)。GNSS衛星は、具体的には、GPS(Global Positioning System)、準天頂衛星、GLONASS、Galileo等、各国の衛星が含まれる。なお、図1では、一例として航法衛星2aおよび航法衛星2bの2基の衛星を示してるが、これに限定されない。移動体10は、4以上の航法衛星2から受信した信号に基づいて位置を算出する単独測位により自己位置(すなわち観測点の位置、本実施形態では緯度経度を示すデータ)を推定し、自律飛行し得る。 The mobile object 10 has a function of moving within space by autonomous movement. The mobile object 10 may be, for example, a small flying object (a so-called drone) that autonomously flies in space, such as an unmanned aerial vehicle (UAV). The mobile object 10 has a GNSS receiver and receives (observation) signals from the navigation satellite 2 (GNSS satellite). Specifically, GNSS satellites include satellites of various countries, such as GPS (Global Positioning System), quasi-zenith satellites, GLONASS, and Galileo. Although FIG. 1 shows two satellites, the navigation satellite 2a and the navigation satellite 2b, as an example, the present invention is not limited to this. The mobile object 10 estimates its own position (that is, the position of an observation point, data indicating latitude and longitude in this embodiment) by independent positioning that calculates the position based on signals received from four or more navigation satellites 2, and flies autonomously. It is possible.
 また、本実施形態による移動体10には、自律飛行中(自律移動中)に、自動的にまたはユーザ操作に応じて空撮を行なう撮像部130が設けられていてもよい。撮像部130により取得された複数の撮像画像を用いて、例えば三次元表示を実現し得る。かかる複数の撮像画像は、例えば三次元地図の作成に用いられる。本実施形態では一例として移動体10に撮像部130を設ける構成としているが、本開示はこれに限定されない。 Furthermore, the mobile object 10 according to the present embodiment may be provided with an imaging unit 130 that performs aerial photography automatically or in response to a user's operation during autonomous flight (autonomous movement). For example, three-dimensional display can be realized using the plurality of captured images acquired by the imaging unit 130. Such a plurality of captured images are used, for example, to create a three-dimensional map. In this embodiment, as an example, the imaging unit 130 is provided in the moving body 10, but the present disclosure is not limited thereto.
 情報処理装置20は、移動体10により取得された移動局観測データおよび基準局3により取得された基準局観測データに基づいて、2地点(観測点と基準点)の地点間の相対的な位置関係を求める相対測位により、観測点の位置(緯度経度)を算出する。相対測位は単独測位より高精度である。例えば、上述した撮像部130により取得される複数の撮像画像には、撮像時刻と、撮像地点の位置情報(ジオタグとも称される)が付加されるが、撮影時点では単独測位により算出された位置情報が付加され、後から上記相対測位の結果に基づいて、事後的に、より高精度の座標(位置情報)に更新され得る。 The information processing device 20 calculates the relative positional relationship between two points (observation point and reference point) based on the mobile station observation data acquired by the mobile object 10 and the reference station observation data acquired by the reference station 3. The position (latitude and longitude) of the observation point is calculated by the relative positioning obtained. Relative positioning is more accurate than independent positioning. For example, a plurality of captured images acquired by the above-mentioned imaging unit 130 are added with the imaging time and location information (also referred to as a geotag) of the imaging point, but at the time of imaging, the position calculated by independent positioning is Information is added and can be subsequently updated to more accurate coordinates (location information) based on the results of the relative positioning.
 相対測位には、複数の受信機で単独測位を行ってそれぞれの位置情報から相対位置を求めるDGPS(Differential GPS)と、複数の受信機と衛星との距離の差(行路差)を搬送波の位相により求め、受信機間の相対位置を決定する干渉測位があり、一般的にDGPSより干渉測位の方が高精度である。本実施形態では、後処理において干渉測位を用いる。より具体的には、干渉測位の一例であるPPK測位法を用いて、移動体10で記録したデータを、基準局3から取得したデータで補正し、より精度の高い測位を実現する。 Relative positioning includes DGPS (Differential GPS), which performs positioning independently with multiple receivers and calculates the relative position from the position information of each, and DGPS (Differential GPS), which calculates the relative position from the position information of each receiver. There is interferometric positioning that determines the relative position between receivers, and generally has higher accuracy than DGPS. In this embodiment, interferometric positioning is used in post-processing. More specifically, the PPK positioning method, which is an example of interferometric positioning, is used to correct the data recorded by the mobile object 10 with the data acquired from the reference station 3, thereby achieving more accurate positioning.
 (課題の整理)
 ここで、後処理(PPK等の事後的な測位処理)に使用する移動局観測データに不安定なデータが含まれている場合、測位処理の精度に影響が生じ得る。上記特許文献1では、観測時に衛星の仰角を予測し、所定の角度閾値を超える複数の衛星から信号を受信することが開示されているが、RTK測位法における精度向上方法であり、後処理における精度向上については考慮されていない。
(Organizing issues)
Here, if the mobile station observation data used for post-processing (subsequent positioning processing such as PPK) includes unstable data, the accuracy of the positioning processing may be affected. The above-mentioned Patent Document 1 discloses predicting the elevation angle of a satellite during observation and receiving signals from a plurality of satellites exceeding a predetermined angle threshold. No consideration is given to improving accuracy.
 そこで、本実施形態では、観測データから不安定なデータを除き、適切な範囲の(安定した)観測データを後処理に使用することで、測位処理の精度を向上する。不安定なデータの判断基準はいくつか挙げられる。本実施形態では、さらに、各判断基準に基づいて複数の適切な範囲の観測データ(すなわち、複数組の使用開始時刻および使用終了時刻による各使用観測データ)を用意して各々解を求め、複数の解から最終的な測位データを生成することで、さらなる精度向上を実現し得る。 Therefore, in this embodiment, the accuracy of positioning processing is improved by removing unstable data from observation data and using (stable) observation data in an appropriate range for post-processing. There are several criteria for determining unstable data. In this embodiment, furthermore, a plurality of appropriate ranges of observation data (i.e., each usage observation data based on multiple sets of usage start times and usage end times) are prepared based on each judgment criterion, and a solution is obtained for each, and multiple Further accuracy improvement can be achieved by generating final positioning data from the solution.
 以上、本開示の一実施形態による位置測位システムの概要について説明した。続いて、本実施形態による位置測位システムに含まれる移動体10および情報処理装置20の具体的な構成について図面を参照して説明する。 The outline of the positioning system according to an embodiment of the present disclosure has been described above. Next, specific configurations of the mobile object 10 and the information processing device 20 included in the positioning system according to the present embodiment will be described with reference to the drawings.
 <<2.構成例>>
 <2-1.移動体10の構成>
 図2は、本実施形態による移動体10の構成の一例を示すブロック図である。図2に示すように、移動体10は、制御部110、位置センサ120、撮像部130、高度センサ140、記憶部150、通信部160、および飛行機構170を有する。
<<2. Configuration example >>
<2-1. Configuration of mobile body 10>
FIG. 2 is a block diagram showing an example of the configuration of the mobile object 10 according to this embodiment. As shown in FIG. 2, the mobile object 10 includes a control section 110, a position sensor 120, an imaging section 130, an altitude sensor 140, a storage section 150, a communication section 160, and a flight mechanism 170.
 (制御部110)
 制御部110は、演算処理装置および制御装置として機能し、各種プログラムに従って移動体10内の動作全般を制御する。制御部110は、例えばCPU(Central Processing Unit)、マイクロプロセッサ等の電子回路によって実現される。また、制御部110は、使用するプログラムや演算パラメータ等を記憶するROM(Read Only Memory)、及び適宜変化するパラメータ等を一時記憶するRAM(Random Access Memory)を含んでいてもよい。
(Control unit 110)
The control unit 110 functions as an arithmetic processing device and a control device, and controls overall operations within the mobile body 10 according to various programs. The control unit 110 is realized by, for example, an electronic circuit such as a CPU (Central Processing Unit) or a microprocessor. Further, the control unit 110 may include a ROM (Read Only Memory) that stores programs to be used, calculation parameters, etc., and a RAM (Random Access Memory) that temporarily stores parameters that change as appropriate.
 制御部110は、自己位置推定部111、飛行制御部112、および観測データ記憶制御部113としても機能する。自己位置推定部111は、位置センサ120で取得したデータに基づいて、自己位置を推定する。例えば、自己位置推定部111は、GNSS(Global Navigation Satellite System/全球測位衛星システム)を用いて、自己位置として緯度経度のデータを算出する。より具体的には、自己位置推定部111は、4基以上の航法衛星2(GNSS衛星)から受信した信号に基づいて位置を算出する単独測位により自己位置を推定してもよい。 The control unit 110 also functions as a self-position estimation unit 111, a flight control unit 112, and an observation data storage control unit 113. The self-position estimating unit 111 estimates the self-position based on the data acquired by the position sensor 120. For example, the self-position estimation unit 111 uses GNSS (Global Navigation Satellite System) to calculate latitude and longitude data as the self-position. More specifically, the self-position estimation unit 111 may estimate the self-position by independent positioning that calculates the position based on signals received from four or more navigation satellites 2 (GNSS satellites).
 飛行制御部112は、飛行機構170を制御して自律飛行を実現する。具体的には、飛行制御部112は、移動体10の位置や姿勢の状態に基づいて、移動体10が目標の状態(位置、姿勢)になるよう飛行機構170を制御する。例えば、飛行制御部112は、制御部110により推定された自己位置から所定の移動目標位置に至る移動経路に沿って移動するよう制御する。移動経路は、改め設定され、記憶部150に記憶された飛行経路であってもよい。なお、飛行制御部112は、飛行経路に沿った自律飛行に限らず、通信部160を介して受信したユーザ指示に従った飛行制御も行い得る。また、移動体10の姿勢(YAW角)は、例えば移動体10に搭載されるジャイロセンサや電子コンパス等の姿勢センサ(不図示)により得られる。 The flight control unit 112 controls the flight mechanism 170 to achieve autonomous flight. Specifically, the flight control unit 112 controls the flight mechanism 170 based on the position and attitude of the moving body 10 so that the moving body 10 is in a target state (position, attitude). For example, the flight control unit 112 controls the vehicle to move along a movement route from its own position estimated by the control unit 110 to a predetermined movement target position. The travel route may be a flight route that is newly set and stored in the storage unit 150. Note that the flight control unit 112 is not limited to autonomous flight along a flight route, but can also perform flight control according to user instructions received via the communication unit 160. Further, the attitude (YAW angle) of the moving body 10 is obtained, for example, by an attitude sensor (not shown) such as a gyro sensor or an electronic compass mounted on the moving body 10.
 観測データ記憶制御部113は、位置センサ120により航法衛星2から受信した信号を含む観測データを、記憶部150に記憶する制御を行う。本実施形態では、航法衛星2から信号を受信することを観測と称する。また、信号を受信した地点を観測点と称する。移動体10は、飛行経路に沿って飛行(移動)しながら、連続的に観測し得る。観測データには、信号受信時刻も含まれる。また、観測データには、観測時における移動体10の高度情報も含まれる。 The observation data storage control unit 113 controls the storage of observation data including the signal received from the navigation satellite 2 by the position sensor 120 in the storage unit 150. In this embodiment, receiving a signal from the navigation satellite 2 is referred to as observation. Further, the point where the signal is received is called an observation point. The moving object 10 can be continuously observed while flying (moving) along a flight path. Observation data also includes signal reception time. The observation data also includes altitude information of the mobile object 10 at the time of observation.
 また、制御部110は、観測データの他、飛行や撮像に関する制御Logや、撮像部130で得られた撮像画像も記憶部150に記憶する制御を行う。撮像画像には、撮像時刻およびジオタグ(自己位置推定部111により算出された位置情報)といった、いわゆるExif情報が付加される。 In addition, the control unit 110 performs control to store control logs related to flight and imaging, and captured images obtained by the imaging unit 130 in the storage unit 150 in addition to observation data. So-called Exif information such as the imaging time and a geotag (location information calculated by the self-position estimating unit 111) is added to the captured image.
 (位置センサ120)
 位置センサ120は、位置を算出するために用いられるデータを受信する受信機である。一例として、GPS、準天頂衛星、GLONASS、Galileo、BeiDou等の航法衛星2を受信対象とするGNSS受信機により実現される。位置センサ120により航法衛星2から受信した信号は、観測データとして、記憶部150に記憶される。また、かかる信号は、自己位置推定部111による自己位置推定にも用いられる。
(Position sensor 120)
Position sensor 120 is a receiver that receives data used to calculate position. As an example, this is realized by a GNSS receiver that receives navigation satellites 2 such as GPS, quasi-zenith satellites, GLONASS, Galileo, and BeiDou. The signal received from the navigation satellite 2 by the position sensor 120 is stored in the storage unit 150 as observation data. Further, such a signal is also used for self-position estimation by the self-position estimating section 111.
 (撮像部130)
 撮像部130は、1以上のレンズ(光学系)と、CCDやCMOS等からなる撮像素子とを有し、飛行中に自動的にまたはユーザ操作に応じて空撮を行なう。
(Imaging unit 130)
The imaging unit 130 includes one or more lenses (optical system) and an imaging device such as a CCD or CMOS, and performs aerial photography automatically or in response to a user's operation during flight.
 (高度センサ140)
 高度センサは、移動体10の高度を算出し、制御部110に出力する。高度センサ140は、例えば気圧センサにより実現される。高度センサ140は、気圧の変化を計測し、移動体10の(地上からの)高さを算出し得る。
(altitude sensor 140)
The altitude sensor calculates the altitude of the mobile object 10 and outputs it to the control unit 110. The altitude sensor 140 is realized by, for example, an atmospheric pressure sensor. The altitude sensor 140 can measure changes in atmospheric pressure and calculate the height of the mobile object 10 (from the ground).
 (記憶部150)
 記憶部150は、制御部110の処理に用いられるプログラムや演算パラメータ等を記憶するROM(Read Only Memory)、および適宜変化するパラメータ等を一時記憶するRAM(Random Access Memory)により実現される。本実施形態による記憶部250は、飛行経路、観測データ、撮像画像等を格納し得る。
(Storage unit 150)
The storage unit 150 is realized by a ROM (Read Only Memory) that stores programs, calculation parameters, etc. used in the processing of the control unit 110, and a RAM (Random Access Memory) that temporarily stores parameters that change as appropriate. The storage unit 250 according to this embodiment can store flight routes, observation data, captured images, and the like.
 (通信部160)
 通信部160は、外部装置と通信接続してデータの送受信を行う。通信部160は、例えば、有線/無線LAN(Local Area Network)、またはWi-Fi(登録商標)、Bluetooth(登録商標)、携帯通信網(LTE(Long Term Evolution)、4G(第4世代の移動体通信方式)、5G(第5世代の移動体通信方式))等により通信する。例えば、通信部160は、情報処理装置20から飛行経路の情報やユーザ操作を受信し、また、観測データや撮像画像を情報処理装置20に送信する。
(Communication Department 160)
The communication unit 160 communicates with an external device to transmit and receive data. The communication unit 160 uses, for example, a wired/wireless LAN (Local Area Network), Wi-Fi (registered trademark), Bluetooth (registered trademark), a mobile communication network (LTE (Long Term Evolution), 4G (fourth generation mobile 5G (5th generation mobile communication system)), etc. For example, the communication unit 160 receives flight route information and user operations from the information processing device 20, and also transmits observation data and captured images to the information processing device 20.
 (飛行機構170)
 飛行機構170は、移動体10を飛行させるための機構である。飛行機構170は、例えば、移動体10に搭載されたバッテリ(不図示)から供給されるエネルギーによって駆動する1以上モータや、1以上のプロペラ(例えば4枚のロータ)を含む。飛行機構170は、飛行制御部112による制御に従って駆動し、移動体10の飛行を実現する。
(Flight mechanism 170)
The flight mechanism 170 is a mechanism for making the mobile body 10 fly. The flight mechanism 170 includes, for example, one or more motors driven by energy supplied from a battery (not shown) mounted on the moving object 10 and one or more propellers (for example, four rotors). The flight mechanism 170 is driven under the control of the flight control unit 112 and allows the mobile object 10 to fly.
 以上、移動体10の構成について具体的に説明した。なお、本実施形態による移動体10の構成は図2に示す例に限定されない。例えば、移動体10には、加速度センサ、磁気センサ(方位センサの一例)、および障害物を検知する障害物検知センサ(例えば光センサ)が設けられていてもよい。移動体10は、障害物検知センサにより障害物を回避して飛行することができる。また、観測中における移動体10の周囲の環境情報の一つとして、障害物検知センサのセンシング結果が、観測データに含まれて記憶部150に記憶されてもよい。 The configuration of the mobile body 10 has been specifically described above. Note that the configuration of the mobile body 10 according to this embodiment is not limited to the example shown in FIG. 2. For example, the moving body 10 may be provided with an acceleration sensor, a magnetic sensor (an example of a direction sensor), and an obstacle detection sensor (for example, an optical sensor) that detects obstacles. The moving body 10 can fly while avoiding obstacles using an obstacle detection sensor. Further, as one piece of environmental information around the mobile object 10 during observation, the sensing result of the obstacle detection sensor may be included in the observation data and stored in the storage unit 150.
 また、移動体10は、撮像部130を有しない構成であってもよい。また、移動体10は、内蔵される記憶部150の他、取り出し可能な記憶媒体を有し、観測データや撮像画像を、記憶媒体に書き込んでもよい。また、制御部110の各機能は、各々別のプロセッサにより実現されてもよい。 Additionally, the moving body 10 may have a configuration that does not include the imaging unit 130. In addition to the built-in storage unit 150, the moving object 10 may have a removable storage medium, and observation data and captured images may be written in the storage medium. Further, each function of the control unit 110 may be realized by a separate processor.
 <2-2.情報処理装置20の構成>
 図3は、本実施形態による情報処理装置20の構成の一例を示すブロック図である。図3に示すように、情報処理装置20は、通信部210、制御部220、操作入力部230、表示部240、および記憶部250を有する。
<2-2. Configuration of information processing device 20>
FIG. 3 is a block diagram showing an example of the configuration of the information processing device 20 according to this embodiment. As shown in FIG. 3, the information processing device 20 includes a communication section 210, a control section 220, an operation input section 230, a display section 240, and a storage section 250.
 (通信部210)
 通信部210は、外部装置と通信接続し、データの送受信を行う。また、通信部210は、例えば、有線/無線LAN(Local Area Network)、またはWi-Fi(登録商標)、Bluetooth(登録商標)、携帯通信網(LTE(Long Term Evolution)、4G(第4世代の移動体通信方式)、5G(第5世代の移動体通信方式))等によりネットワークと通信接続することが可能である。例えば通信部210は、無線通信により移動体10から観測データを受信する。また、通信部210は、無線通信によりユーザ操作の情報を移動体10に送信する。また、通信部210は、インターネットを介して、基準局3から観測データを受信する。
(Communication Department 210)
The communication unit 210 communicates with an external device and sends and receives data. Further, the communication unit 210 is configured to use, for example, a wired/wireless LAN (Local Area Network), Wi-Fi (registered trademark), Bluetooth (registered trademark), mobile communication network (LTE (Long Term Evolution), 4G (fourth generation It is possible to connect to a network using 5G (5th generation mobile communication system), etc. For example, the communication unit 210 receives observation data from the mobile object 10 via wireless communication. Furthermore, the communication unit 210 transmits user operation information to the mobile body 10 by wireless communication. The communication unit 210 also receives observation data from the reference station 3 via the Internet.
 (制御部220)
 制御部220は、演算処理装置および制御装置として機能し、各種プログラムに従って情報処理装置20内の動作全般を制御する。制御部220は、例えばCPU(Central Processing Unit)、マイクロプロセッサ等の電子回路によって実現される。また、制御部220は、使用するプログラムや演算パラメータ等を記憶するROM(Read Only Memory)、及び適宜変化するパラメータ等を一時記憶するRAM(Random Access Memory)を含んでいてもよい。
(Control unit 220)
The control unit 220 functions as an arithmetic processing device and a control device, and controls overall operations within the information processing device 20 according to various programs. The control unit 220 is realized by, for example, an electronic circuit such as a CPU (Central Processing Unit) or a microprocessor. Further, the control unit 220 may include a ROM (Read Only Memory) that stores programs to be used, calculation parameters, etc., and a RAM (Random Access Memory) that temporarily stores parameters that change as appropriate.
 本実施形態による制御部220は、移動局観測データ取得部221、基準局観測データ取得部222、使用時刻決定部223、測位処理部224、高精度化部225、および表示制御部226としても機能する。 The control unit 220 according to the present embodiment also functions as a mobile station observation data acquisition unit 221, a reference station observation data acquisition unit 222, a usage time determination unit 223, a positioning processing unit 224, a precision improvement unit 225, and a display control unit 226. .
 移動局観測データ取得部221は、移動体10により得られた移動局観測データを取得する。例えば、移動局観測データ取得部221は、通信部210を介して、無線通信により移動体10から移動局観測データを受信してもよい。また、移動局観測データ取得部221は、移動体10から取り出され、情報処理装置20に挿入されたSD(Secure Digital)メモリーカード等の記憶媒体から、移動局観測データを読み取ってもよい。 The mobile station observation data acquisition unit 221 acquires mobile station observation data obtained by the mobile object 10. For example, the mobile station observation data acquisition unit 221 may receive mobile station observation data from the mobile body 10 via wireless communication via the communication unit 210. Furthermore, the mobile station observation data acquisition unit 221 may read the mobile station observation data from a storage medium such as an SD (Secure Digital) memory card that is taken out from the mobile object 10 and inserted into the information processing device 20.
 基準局観測データ取得部222は、基準局3により得られた基準局観測データを取得する。例えば、基準局観測データ取得部222は、通信部210を介してインターネットに接続し、基準局3により得られた基準局観測データが格納されるサーバから、移動局観測データをダウンロードしてもよい。なお、本実施形態では、基準局3の一例として地上に設置される基地局を想定しているが、これに限らず、電子基準点や仮想基準点など、基地局相当のLogが取得できるものであってもよい。どの基準局3から、いつの移動局観測データを取得するかは、ユーザにより指定される。ユーザは、移動体10を飛行させた場所の近くにある基準局3により得られた、飛行させた日時に対応する移動局観測データを、取得するよう操作する。 The reference station observation data acquisition unit 222 acquires the reference station observation data obtained by the reference station 3. For example, the reference station observation data acquisition unit 222 may connect to the Internet via the communication unit 210 and download the mobile station observation data from a server in which the reference station observation data obtained by the reference station 3 is stored. In addition, in this embodiment, a base station installed on the ground is assumed as an example of the reference station 3, but the base station is not limited to this, and it is possible to obtain a log equivalent to a base station, such as an electronic reference point or a virtual reference point. There may be. The user specifies from which reference station 3 and when the mobile station observation data is to be acquired. The user operates to obtain mobile station observation data corresponding to the date and time of flight, which is obtained by the reference station 3 located near the location where the mobile object 10 was flown.
 使用時刻決定部223は、移動局観測データに対して、後述する測位処理に使用する観測データの使用開始時刻および使用終了時刻を複数組決定する機能を有する。使用時刻決定部223により使用開始時刻および使用終了時刻を決定することで、観測データから不安定なデータを除外し、後述する測位処理において安定した適切なデータが得られる。本実施形態では、不安定なデータの判断基準をいくつか設定し、各判断基準に基づいて複数の適切な範囲の観測データ(すなわち、複数組の使用開始時刻および使用終了時刻による各使用観測データ)を用意して測位処理部224において各々解を求めることで、後述する高精度化部225において、測位処理部224により得られた複数の解から、より精度の高い測位データを最終的に生成することができる。 The usage time determining unit 223 has a function of determining multiple sets of usage start times and usage end times of observation data used for positioning processing, which will be described later, for mobile station observation data. By determining the usage start time and usage end time by the usage time determination unit 223, unstable data can be excluded from the observation data, and stable and appropriate data can be obtained in the positioning process described later. In this embodiment, several criteria for determining unstable data are set, and based on each criterion, observation data in a plurality of appropriate ranges (i.e., each usage observation data with multiple sets of usage start time and usage end time) is set. ), and the positioning processing unit 224 obtains each solution, so that the later-described high-precision unit 225 finally generates more accurate positioning data from the multiple solutions obtained by the positioning processing unit 224. can do.
 以下、使用時刻決定部223において使用開始時刻および使用終了時刻を決定する際の判断基準について、いくつかの例を説明する。使用時刻決定部223は、下記に説明する判断基準を複数用いて、複数組の使用開始時刻および使用終了時刻を決定し得る。 Hereinafter, some examples will be explained regarding the criteria for determining the usage start time and usage end time in the usage time determination unit 223. The usage time determining unit 223 can determine multiple sets of usage start times and usage end times using multiple criteria described below.
 ・移動開始終了時刻
 使用時刻決定部223は、使用開始時刻および使用終了時刻を、移動体10(移動局)の移動開始終了時刻に基づいて決定してもよい。移動開始終了時刻とは、例えば、移動体10の離着陸時刻である。使用時刻決定部223は、移動体10の離陸時刻(移動開始時刻)を、観測データの使用開始時刻、着陸時刻(移動終了時刻)を、観測データの使用終了時刻に決定する。
- Movement start and end time The use time determining unit 223 may determine the use start time and use end time based on the movement start and end time of the mobile body 10 (mobile station). The movement start and end times are, for example, the takeoff and landing times of the mobile body 10. The use time determining unit 223 determines the takeoff time (movement start time) of the mobile object 10 as the use start time of the observation data, and the landing time (movement end time) as the use end time of the observation data.
 ここで、離陸前および着陸後の観測データを不安定なデータとして除いた観測データ(使用観測データと称する。)を用いた際の測位処理の精度向上について説明する。まず、移動体10により得られた全ての(測位開始から終了までの)測位データを用いて測位処理を行った場合について、図4を参照して説明する。図4は、不安定なデータを除かなかった場合における測位処理の解データ(測位データ)の一例を示す図である。離着陸前後は、ユーザが移動体10を持って動かしたりするが、この間も、人等の障害物が移動体10の近くにある状態で移動体10による観測(航法衛星2からの信号の受信)が行われ、不安定なデータが取得され得る。 Here, we will explain how to improve the accuracy of positioning processing when using observation data (referred to as used observation data) that excludes observation data before takeoff and after landing as unstable data. First, a case where positioning processing is performed using all the positioning data (from the start to the end of positioning) obtained by the mobile object 10 will be described with reference to FIG. 4. FIG. 4 is a diagram showing an example of solution data (positioning data) of positioning processing when unstable data is not removed. Before and after takeoff and landing, the user holds and moves the mobile object 10, and during this time, the mobile object 10 performs observation (reception of signals from the navigation satellite 2) with obstacles such as people in the vicinity of the mobile object 10. is performed, and unstable data may be obtained.
 図4では、測位処理の解データとして、移動体10が観測した各観測点(飛行経路上の各観測点を含む)の緯度経度を示すデータが示されている。測位処理部224において、測位処理としてPPK測位法を用いた場合、各観測点の位置情報(緯度経度を示すデータ)について、Float解またはFix解が得られる。Fix解は、Float解よりも精度が高い(誤差が少ない)解であり、Fix率(全ての解に対するFix解の割合)の高さが、測位精度の良さの目安となる。精度が高い解(Fix解)がより多く得られることが望ましい。本実施形態では、一例として、測位精度の高さを、Fix率を用いて説明する。 In FIG. 4, data indicating the latitude and longitude of each observation point (including each observation point on the flight route) observed by the mobile object 10 is shown as solution data of the positioning process. When the positioning processing unit 224 uses the PPK positioning method for positioning processing, a Float solution or a Fixed solution is obtained for the position information (data indicating latitude and longitude) of each observation point. The Fix solution is a solution with higher accuracy (fewer errors) than the Float solution, and the height of the Fix rate (ratio of Fix solutions to all solutions) is a measure of the positioning accuracy. It is desirable to obtain as many highly accurate solutions (Fix solutions) as possible. In this embodiment, the height of positioning accuracy will be explained using a fix rate as an example.
 さらに詳細に説明すると、PPK測位法では、L(搬送波位相)の数を算出する過程で整数値バイアス(N)を求める箇所が存在する。整数値バイアスは、真のアンビギュイティ(観測を始めた時の衛星と受信機の距離)であり、搬送波波長の整数倍(整数。つまり小点以下はない)のはずだが、最初から決定することが出来ないため、近似解を求める算出法(例えば、LAMBDA法;The least-squares ambiguity decorrelation adjustment)が用いられる。PPK測位法において、整数値バイアスが整数値で得られなかった場合(少数値を含む近似解の場合)の解(測位データ;緯度経度を示すデータ)がFloat解と称され、整数値バイアスが整数値で得られた場合の解がFix解と称される。また、整数値バイアスを求める際に一般的に用いられる計算方法は逐次近似法のため、搬送波が連続で観測できている期間においては整数値バイアスが固定となる(すなわち一度求まった解を次の計算に使用する)。このため、間違った解が以降の計算に悪影響を与え、誤った解に陥る(精度が低下する)恐れがある。 To explain in more detail, in the PPK positioning method, there is a part where an integer value bias (N) is calculated in the process of calculating the number of L (carrier phase). The integer bias is the true ambiguity (the distance between the satellite and the receiver at the beginning of the observation), and should be an integer multiple of the carrier wavelength (an integer, that is, there is no part below the decimal point), but it must be determined from the beginning. Therefore, a calculation method for obtaining an approximate solution (for example, the LAMBDA method; the least-squares ambiguity decorrelation adjustment) is used. In the PPK positioning method, when the integer value bias cannot be obtained as an integer value (in the case of an approximate solution including decimal values), the solution (positioning data; data indicating latitude and longitude) is called a Float solution, and the integer value bias is A solution obtained using integer values is called a Fix solution. In addition, the calculation method generally used to find the integer bias is a successive approximation method, so the integer bias is fixed during the period when the carrier wave can be observed continuously (i.e., the solution once found is used in calculations). Therefore, an incorrect solution may adversely affect subsequent calculations, leading to an incorrect solution (decreased accuracy).
 図4では、離着陸前後の不安定なデータ(図4の拡大箇所)が計算に含まれるため、以降の(各観測点)の計算(測位処理)に悪影響を与え、Fix率が低くなっている。そこで、本実施形態では、測位処理に用いる観測データに関し、離着陸前後の不安定なデータを除くことで、測位処理で得られる解データ(測位データ)のFix率を高めることを可能とする。 In Figure 4, unstable data before and after takeoff and landing (enlarged area in Figure 4) is included in the calculation, which has a negative impact on subsequent calculations (positioning processing) at each observation point, resulting in a low fix rate. . Therefore, in this embodiment, regarding the observation data used in the positioning process, by removing unstable data before and after takeoff and landing, it is possible to increase the fix rate of the solution data (positioning data) obtained in the positioning process.
 図5は、本実施形態による離着陸時刻に基づいて不安定なデータを除いた場合における測位処理の解データ(測位データ)の一例を示す図である。図5の拡大箇所に示すように、離着陸前後の不安定な観測データを除く、すなわち、例えば離陸時刻を使用開始時刻、着陸時刻を使用終了時刻として切り出した使用観測データを、測位処理に用いることで、不安定なデータによる計算への悪影響を低減し、Fix率を高めることが可能となる。図5に示すFix率98.7%という計算結果は一例であるが、少なくとも全ての観測データを用いる場合に比べてFix率が高まる実験結果が得られた。 FIG. 5 is a diagram showing an example of solution data (positioning data) of the positioning process when unstable data is removed based on takeoff and landing times according to the present embodiment. As shown in the enlarged part of Fig. 5, unstable observation data before and after take-off and landing is removed, that is, used observation data that is extracted using the take-off time as the start time of use and the landing time as the end time of use, for example, is used for positioning processing. This makes it possible to reduce the negative influence of unstable data on calculations and increase the fix rate. Although the calculation result of a fix rate of 98.7% shown in FIG. 5 is an example, an experimental result was obtained in which the fix rate is higher than at least when all observation data is used.
 なお、使用時刻決定部223は、データの安定性を高めるため、離着陸時刻からさらに所定の時間を引いて使用開始時刻および使用終了時刻を決定してもよい。すなわち、使用時刻決定部223は、離陸時刻から所定時間後を使用開始時刻、着陸時刻の所定時間前を使用終了時刻としてもよい。 In addition, in order to improve the stability of the data, the use time determination unit 223 may determine the use start time and use end time by further subtracting a predetermined time from the takeoff and landing time. That is, the use time determination unit 223 may set a predetermined time after takeoff time as the use start time, and a predetermined time before landing time as the use end time.
 また、離着陸時刻は、移動体10から取得される制御Logから判断され得る。情報処理装置20は、移動体10の制御Logも、移動局観測データと共に取得し得る。制御Logには、飛行制御に関するデータが含まれ、離着陸時刻が取得できる。また、使用時刻決定部223は、移動体10の高度情報に基づいて離着陸時刻を判断することも可能である。移動体10の高度情報は、例えば移動局観測データに含まれる。 Furthermore, the takeoff and landing times can be determined from the control log acquired from the mobile object 10. The information processing device 20 can also acquire the control log of the mobile object 10 together with the mobile station observation data. The control log includes data related to flight control, and allows acquisition of takeoff and landing times. Further, the use time determining unit 223 can also determine the takeoff and landing times based on the altitude information of the mobile object 10. The altitude information of the mobile object 10 is included in, for example, mobile station observation data.
 また、使用時刻決定部223は、移動体10の高度が所定値を越えた時刻を使用開始時刻、移動体10の高度が所定値を下回った時刻を使用終了時刻としてもよい。これにより、高度不足による不安定なデータを除外することができる。 Further, the use time determining unit 223 may set the time when the altitude of the mobile body 10 exceeds a predetermined value as the use start time, and the time when the altitude of the mobile body 10 falls below the predetermined value as the use end time. This makes it possible to exclude unstable data due to insufficient altitude.
 ・撮影開始終了時刻
 使用時刻決定部223は、使用開始時刻および使用終了時刻を、移動体10(移動局)の撮影開始終了時刻に基づいて決定してもよい。使用時刻決定部223は、移動体10の撮影開始時刻を、観測データの使用開始時刻、撮影終了時刻を、観測データの使用終了時刻に決定する。撮影開始終了時刻は、移動体10から取得される制御Logから得てもよいし、撮像画像に付加されるExif情報から得てもよい。撮影は移動体10の高度が十分な高さに達した場合や、飛行が安定した場合等、目標地点や良好な状態で行われることが想定され、撮影が行われている間の観測データを用いることで、撮影開始前や撮影終了後の不安定な観測データによる測位処理への悪影響を低減することが期待できる。
- Shooting start and end time The use time determining unit 223 may determine the use start time and use end time based on the shooting start and end time of the mobile object 10 (mobile station). The usage time determining unit 223 determines the imaging start time of the mobile object 10 as the observation data usage start time, and the imaging end time as the observation data usage end time. The shooting start and end times may be obtained from the control log obtained from the moving object 10 or from Exif information added to the captured image. It is assumed that photography will be carried out at a target point or in good conditions, such as when the altitude of the mobile object 10 has reached a sufficient height or when the flight is stable, and the observation data while photography is being performed. By using this method, it is expected that the negative impact on positioning processing due to unstable observation data before the start of shooting or after the end of shooting can be reduced.
 図6は、本実施形態による撮影開始終了時刻で使用開始時刻および使用終了時刻を決定した場合の測位データの精度向上について説明する図である。図6左には、時刻指定なし、すなわち全ての観測データを用いた場合の測位処理の結果(測位データ)を示す。この場合、測位精度の高さを示すFix率は48.2%となった。一方、図6右に示すように、撮影開始終了時刻でトリミングした使用観測データを測位処理に用いた場合、Fix率は98.3%となり、測位精度が向上した。 FIG. 6 is a diagram illustrating the improvement in accuracy of positioning data when the use start time and use end time are determined based on the shooting start and end times according to the present embodiment. The left side of FIG. 6 shows the results of positioning processing (positioning data) without time designation, that is, when all observation data are used. In this case, the fix rate, which indicates high positioning accuracy, was 48.2%. On the other hand, as shown on the right side of FIG. 6, when the used observation data trimmed at the shooting start and end time is used for positioning processing, the fix rate is 98.3%, and the positioning accuracy is improved.
 また、使用時刻決定部223は、撮影開始終了時刻に所定の余裕時間(例えば数秒~数十秒)を追加して使用開始時刻および使用終了時刻を決定してもよい。すなわち、使用時刻決定部223は、撮影開始時刻から所定時間前を使用開始時刻、撮影終了時刻の所定時間後を使用終了時刻としてもよい。 Further, the use time determining unit 223 may determine the use start time and use end time by adding a predetermined margin time (for example, several seconds to several tens of seconds) to the shooting start and end time. In other words, the use time determining unit 223 may set a predetermined time before the shooting start time as the use start time, and may set a predetermined time after the shooting end time as the use end time.
 図7は、本実施形態による撮影開始終了時刻に所定の余裕時間を追加して使用開始時刻および使用終了時刻を決定した場合の測位データの精度向上について説明する図である。図7左には、時刻指定なし、すなわち全ての観測データを用いた場合の測位処理の結果(測位データ)を示す。この場合、測位精度の高さを示すFix率は48.2%となった。一方、図7右に示すように、撮影開始終了時刻に余裕を持たせてトリミングした使用観測データを測位処理に用いた場合、Fix率は99.2%となり、測位精度が向上した。 FIG. 7 is a diagram illustrating an improvement in accuracy of positioning data when the use start time and use end time are determined by adding a predetermined margin time to the shooting start and end time according to the present embodiment. The left side of FIG. 7 shows the results of positioning processing (positioning data) without time designation, that is, when all observation data are used. In this case, the fix rate, which indicates high positioning accuracy, was 48.2%. On the other hand, as shown on the right side of FIG. 7, when used observation data that has been trimmed with a margin in the shooting start and end time is used for positioning processing, the fix rate is 99.2%, and the positioning accuracy is improved.
 図6および図7に示すFix率は一つの実験結果であるが、いずれにせよ、撮影開始終了時刻に基づいてトリミングした使用観測データを測位処理に用いることで、少なくとも全ての観測データを用いる場合に比べてFix率が高まることが明確である。なお、ここでは移動体10で撮影を行っているため、撮影開始終了時刻を用いたが、これに限定されず、撮影以外の何らかの情報取得(各種センシング)が飛行の目的の場合に、その情報取得開始終了時刻を用いてもよい。 The fix rates shown in Figures 6 and 7 are just experimental results, but in any case, by using the observation data that is trimmed based on the shooting start and end time for positioning processing, at least when all observation data is used. It is clear that the fix rate increases compared to Note that here, since the photographing is performed by the moving object 10, the photographing start and end time is used, but this is not limited to this, and if the purpose of the flight is to acquire some information other than photographing (various sensing), that information may be used. The acquisition start and end time may also be used.
 ・観測衛星数の確保開始終了時刻
 使用時刻決定部223は、使用開始時刻および使用終了時刻を、移動体10(移動局)による所定の観測衛星数の確保開始終了時刻に基づいて決定してもよい。観測できている衛星数が少ない程、不安定なデータとなる可能性が高いためである。使用時刻決定部223は、移動体10による所定の観測衛星数の確保開始時刻を、観測データの使用開始時刻、所定の観測衛星数の確保終了時刻を、観測データの使用終了時刻に決定する。移動体10(移動局)による所定の観測衛星数の確保開始終了時刻は、移動体10から取得される観測データから得られる。
・Start and finish time for securing the number of observation satellites The use time determining unit 223 determines the start time and end time for use based on the start and end time for securing a predetermined number of observation satellites by the mobile object 10 (mobile station). good. This is because the fewer the number of satellites that can be observed, the more likely the data will be unstable. The use time determining unit 223 determines the start time for securing the predetermined number of observation satellites by the mobile object 10 as the start time for using the observation data, and the end time for securing the predetermined number of observation satellites as the end time for using the observation data. The start and end time of securing a predetermined number of observation satellites by the mobile body 10 (mobile station) is obtained from the observation data acquired from the mobile body 10.
 図8は、本実施形態による移動体10で観測した衛星数の一例を示す図である。観測データには、図8に示すように、移動体10で観測した衛星数のデータも含まれる。ここで、「観測した」とは、信号を受信できたことを意味する。すなわち、移動体10で観測した衛星数とは、移動体10が信号を受信できた航法衛星2の数である。 FIG. 8 is a diagram showing an example of the number of satellites observed by the mobile object 10 according to the present embodiment. The observation data also includes data on the number of satellites observed by the mobile object 10, as shown in FIG. Here, "observed" means that a signal could be received. That is, the number of satellites observed by the mobile body 10 is the number of navigation satellites 2 whose signals could be received by the mobile body 10.
 所定の観測衛星数は、移動体10に設けられる位置センサ120の最大アンテナ数としてもよい。位置センサ120は、例えばGNSS受信機であって、その最大アンテナ数(受信可能な衛星数)を所定の観測衛星数としてもよい。図8に示す例では、例えば最大アンテナ数が24基の場合を想定し、使用時刻決定部223は、24基観測できた5時19分2秒を使用開始時刻、24基観測できなくなった5時23分16秒を使用終了時刻に決定する。なお、一時的に観測衛星数が減った時間(ごく短い時間)は無視するようにしてもよい。 The predetermined number of observation satellites may be the maximum number of antennas of the position sensor 120 provided on the mobile object 10. The position sensor 120 is, for example, a GNSS receiver, and its maximum number of antennas (the number of satellites that can be received) may be set as the predetermined number of observation satellites. In the example shown in FIG. 8, it is assumed that the maximum number of antennas is 24, and the use time determining unit 223 determines that the use start time is 5:19:02 when 24 antennas can be observed, and 5:19:02 when 24 antennas can no longer be observed. 23 minutes and 16 seconds is determined as the end time of use. Note that the time when the number of observation satellites temporarily decreases (very short time) may be ignored.
 図9は、本実施形態による所定の観測衛星数の確保開始終了時刻で使用開始時刻および使用終了時刻を決定した場合の測位データの精度向上について説明する図である。図9左には、時刻指定なし、すなわち全ての観測データを用いた場合の測位処理の結果(測位データ)を示す。この場合、測位精度の高さを示すFix率は48.2%となった。一方、図9右に示すように、所定の観測衛星数の確保開始終了時刻でトリミングした使用観測データを測位処理に用いた場合、Fix率は99.1%となり、測位精度が向上した。 FIG. 9 is a diagram illustrating the improvement in accuracy of positioning data when the use start time and use end time are determined based on the start and end time of securing a predetermined number of observation satellites according to the present embodiment. The left side of FIG. 9 shows the results of positioning processing (positioning data) without time specification, that is, when all observation data are used. In this case, the fix rate, which indicates high positioning accuracy, was 48.2%. On the other hand, as shown on the right side of FIG. 9, when the used observation data trimmed at the start and end times of securing a predetermined number of observation satellites is used for positioning processing, the fix rate is 99.1%, and the positioning accuracy is improved.
 また、使用時刻決定部223は、移動体10により観測できている衛星数として、基準局でも同じ衛星が観測出来ている場合をカウントするようにしてもよい。後述する測位処理では、対応する時刻の基準局観測データも用いるため、基準局3の観測データの安定性も求められる。使用時刻決定部223は、基準局観測データを考慮し、移動体10と基準局3で同じ航法衛星2を観測できている場合、「観測衛星数:1」とカウントする。これにより、より安定した観測データを用いることが可能となる。 Further, the usage time determination unit 223 may count the number of satellites that can be observed by the mobile object 10 when the same satellite can be observed by the reference station. In the positioning process described later, the reference station observation data at the corresponding time is also used, so the stability of the observation data of the reference station 3 is also required. The use time determining unit 223 considers the reference station observation data and counts the number of observed satellites as 1 if the same navigation satellite 2 can be observed by the mobile object 10 and the reference station 3. This makes it possible to use more stable observation data.
 また、使用時刻決定部223は、所定の観測衛星数の確保開始時刻から確保終了時刻の間で、観測衛星数が一時的に少なくなった部分を除外するよう、観測データを分割した使用観測データを切り出してもよい。例えば、使用時刻決定部223は、所定の観測衛星数の確保開始から一時的に観測衛星数が少なくなった第1の途中時刻:Aまでの第1の使用観測データと、観測衛星数が復活した第2の途中時刻:Bから確保終了時刻までの第2の使用観測データとを、移動局観測データから切り出してもよい。この場合、使用時刻決定部223は、第1の使用観測データと、第2の使用観測データと、途中を除外していない第3の使用観測データ(所定の観測衛星数の確保開始時刻から確保終了時刻までの観測データ)と、を、測位処理部224に出力する。測位処理部224では、第1の使用観測データを用いた測位処理と、第2の使用観測データを用いた測位処理と、第3の使用観測データを用いた測位処理と、を行なう。第1の途中時刻:Aから第2の途中時刻:Bまでの観測データは不安定なデータであるが、第1の使用観測データと第2の使用観測データに分けてそれぞれ測位処理を行うことで、当該不安定なデータによる影響が低減される。そして、測位処理部224は、第1の使用観測データを用いた測位処理の結果と、第2の使用観測データを用いた測位処理の結果と、第3の使用観測データを用いた測位処理の結果から第1の途中時刻:Aから第2の途中時刻:Bまでの結果を取り出した結果と、を繋げることで、不安定なデータによる影響を出来るだけ低減させた測位データを得ることが可能となる。 In addition, the use time determination unit 223 uses observation data obtained by dividing the observation data so as to exclude a portion where the number of observation satellites temporarily decreases between the start time of securing a predetermined number of observation satellites and the end time of securing a predetermined number of observation satellites. You can also cut it out. For example, the usage time determining unit 223 stores the first usage observation data from the start of securing a predetermined number of observation satellites to a first intermediate time when the number of observation satellites temporarily decreases: A, and the number of observation satellites restored. The second used observation data from the second intermediate time: B to the end time of reservation may be extracted from the mobile station observation data. In this case, the usage time determination unit 223 selects the first usage observation data, the second usage observation data, and the third usage observation data (secured from the start time of securing the predetermined number of observation satellites) without excluding any part of the usage data. observation data up to the end time) are output to the positioning processing unit 224. The positioning processing unit 224 performs a positioning process using the first used observation data, a positioning process using the second used observation data, and a positioning process using the third used observation data. Although the observation data from the first intermediate time: A to the second intermediate time: B is unstable data, positioning processing should be performed separately for the first used observation data and the second used observation data. Therefore, the influence of the unstable data is reduced. The positioning processing unit 224 then uses the results of the positioning process using the first observation data to be used, the results of the positioning process using the second observation data to be used, and the results of the positioning process using the third observation data to be used. By connecting the results with the results obtained from the first intermediate time: A to the second intermediate time: B, it is possible to obtain positioning data that reduces the influence of unstable data as much as possible. becomes.
 ・信号強度に基づく時刻
 使用時刻決定部223は、使用開始時刻および使用終了時刻を、移動体10(移動局)による観測時の信号強度(航法衛星2から受信した信号の強度)に基づいて決定してもよい。使用時刻決定部223は、信号強度が所定値を越えた時刻を観測データの使用開始時刻、信号強度が所定値を下回った時刻を観測データの使用終了時刻に決定する。信号強度の情報は、移動体10から取得される観測データから得られる。なお、一時的に信号強度が所定値を下回った時間(ごく短い時間)は無視するようにしてもよい。また、使用時刻決定部223は、途中、信号強度が所定値を下回った一定時間を除いて分割した使用観測データを切り出してもよい。この場合、測位処理部224において、部分的ではあるが精度の高い測位データが得られる。
- Time based on signal strength The usage time determination unit 223 determines the usage start time and usage end time based on the signal strength (strength of the signal received from the navigation satellite 2) at the time of observation by the mobile object 10 (mobile station). You may. The usage time determination unit 223 determines the time when the signal strength exceeds a predetermined value as the observation data usage start time, and the time when the signal strength falls below the predetermined value as the observation data usage end time. Information on signal strength is obtained from observation data obtained from the mobile object 10. Note that the time (very short time) during which the signal strength temporarily falls below a predetermined value may be ignored. Further, the usage time determining unit 223 may cut out the usage observation data divided by excluding a certain period of time during which the signal strength was lower than a predetermined value. In this case, the positioning processing unit 224 obtains partial but highly accurate positioning data.
 信号強度が高い程、より安定した観測データが取得できていると言えるため、測位データの精度向上が期待できる。 It can be said that the higher the signal strength, the more stable observation data has been acquired, so it can be expected that the accuracy of positioning data will improve.
 ・環境に基づく時刻
 使用時刻決定部223は、使用開始時刻および使用終了時刻を、移動体10(移動局)による観測時の環境に基づいて決定してもよい。マルチパスの少なさや、付近に物体(障害物)がない等、良好な環境での観測データを、使用観測データとすることが考え得る。使用時刻決定部223は、移動体10による環境が所定条件を満たした時刻を観測データの使用開始時刻、環境が所定条件を満たさなくなった時刻を観測データの使用終了時刻に決定する。所定条件とは、例えば、マルチパスが少ないことや、障害物が無いことである。環境の情報は、移動体10から取得される観測データや、制御Log、また、別途ユーザが観測時に記録したLogから得られる。なお、一時的に環境が所定条件を満たさない時間(ごく短い時間)は無視するようにしてもよい。また、使用時刻決定部223は、途中、環境が所定条件を満たさない一定時間を除いて分割した使用観測データを切り出してもよい。この場合、測位処理部224において、部分的ではあるが精度の高い測位データが得られる。
- Time based on the environment The usage time determining unit 223 may determine the usage start time and usage end time based on the environment at the time of observation by the mobile object 10 (mobile station). It is conceivable that the observation data to be used may be observation data in a favorable environment, such as less multipath and no nearby objects (obstacles). The use time determining unit 223 determines the time when the environment of the mobile object 10 satisfies a predetermined condition as the observation data use start time, and the time when the environment no longer satisfies the predetermined condition as the observation data use end time. The predetermined conditions include, for example, that there are few multipaths and that there are no obstacles. The environment information is obtained from observation data acquired from the mobile object 10, a control log, and a log separately recorded by the user during observation. Note that a time (very short time) during which the environment temporarily does not satisfy the predetermined conditions may be ignored. Further, the use time determination unit 223 may cut out the usage observation data divided by excluding a certain period during which the environment does not satisfy a predetermined condition. In this case, the positioning processing unit 224 obtains partial but highly accurate positioning data.
 環境が良好な場合、より安定した観測データが取得できていると言えるため、測位データの精度向上が期待できる。 If the environment is favorable, it can be said that more stable observation data can be obtained, so an improvement in the accuracy of positioning data can be expected.
 以上、使用時刻決定部223による使用開始時刻および使用終了時刻を決定する際の判断基準の一例について説明した。使用時刻決定部223は、上記判断基準を複数用いて、複数組の使用開始時刻および使用終了時刻を決定し、複数の使用観測データを測位処理部224に出力する。例えば、使用時刻決定部223は、撮影開始終了時刻でトリミングした使用観測データと、観測衛星数の確保開始終了時刻でトリミングした使用観測データとを、測位処理部224に出力する。 An example of the criteria for determining the usage start time and usage end time by the usage time determining unit 223 has been described above. The use time determining unit 223 uses a plurality of the above criteria to determine a plurality of sets of use start times and use end times, and outputs a plurality of use observation data to the positioning processing unit 224. For example, the usage time determining unit 223 outputs the usage observation data trimmed at the shooting start and end time and the usage observation data trimmed at the securing start and end time of the number of observation satellites to the positioning processing unit 224.
 続いて、図3に戻り、測位処理部224について説明する。測位処理部224は、使用時刻決定部223により決定された複数組の使用開始時刻および使用終了時刻による複数の使用観測データと、基準局3の観測データと、に基づいて、測位処理を行って複数の測位データを算出する。本実施形態による測位処理は、上述したように、一例としてPPK測位法を用いる。算出される測位データは、各観測点の緯度経度を示すデータである。 Next, returning to FIG. 3, the positioning processing unit 224 will be explained. The positioning processing unit 224 performs positioning processing based on the plurality of usage observation data based on the plurality of sets of usage start time and usage end time determined by the usage time determination unit 223 and the observation data of the reference station 3. Calculate positioning data. As described above, the positioning process according to this embodiment uses the PPK positioning method as an example. The calculated positioning data is data indicating the latitude and longitude of each observation point.
 また、測位処理部224は、さらなる精度向上のため、ノイズ閾値など、様々なパラメータを振り分けたフィルタ(パラメータセットとも称される)を用いて、1つの使用観測データに対して複数回の測位処理(異なるフィルタを用いた測位処理)を実行してもよい。これにより、さらに多くの測位データ(使用観測データ数×フィルタ数)が出力される。PPK測位法による測位処理で用いるフィルタは、例えば、信号ノイズ比の閾値(SNR(Signal-to-Noise Ratio)マスク)、衛星の仰角閾値(Elevation Mask)、観測衛星の種類でのマスク(Glonassは除く等)といった様々なマスクの組み合わせが考え得る。ここで記載したマスクは一例であって、本実施形態はこれに限定されない。 In addition, in order to further improve accuracy, the positioning processing unit 224 performs positioning processing multiple times on one observation data using a filter (also referred to as a parameter set) that distributes various parameters such as a noise threshold. (positioning processing using different filters) may be executed. As a result, even more positioning data (number of observation data used x number of filters) is output. Filters used in positioning processing using the PPK positioning method include, for example, a signal-to-noise ratio threshold (SNR (Signal-to-Noise Ratio) mask), a satellite elevation angle threshold (Elevation Mask), and a mask based on the type of observation satellite (Glonass is Various combinations of masks are possible, such as (excluding, etc.). The mask described here is an example, and the present embodiment is not limited thereto.
 高精度化部225は、測位処理部224から出力された複数の測位データに基づいて、最終的な測位データを生成する。本実施形態では、複数の測位データに基づいて1つの高精度な測位データを生成することで、さらなる精度向上を実現し得る。 The precision improvement unit 225 generates final positioning data based on the plurality of positioning data output from the positioning processing unit 224. In this embodiment, further accuracy improvement can be achieved by generating one piece of highly accurate positioning data based on a plurality of pieces of positioning data.
 例えば、高精度化部225は、複数の測位データのうち、最もFix率が高い(すなわち、最も精度が高い)測位データを、最終的な測位データとする。また、高精度化部225は、最もFix率が高い測位データが複数ある場合や、最も高いFix率に近いFix率の測位データがある場合には、より強いフィルタを用いて算出(測位処理)した方を優先して、最終的な測位データとしてもよい。すなわち、高精度化部225は、複数の測位データから、測位データの精度の高さと、測位処理で用いたフィルタの強さに応じて、最終的な測位データを選択してもよい。 For example, the precision improvement unit 225 sets the positioning data with the highest fix rate (that is, the highest accuracy) among the plurality of positioning data as the final positioning data. In addition, when there is a plurality of positioning data with the highest fix rate, or when there is positioning data with a fix rate close to the highest fix rate, the precision improvement unit 225 calculates using a stronger filter (positioning process). It is also possible to give priority to the one that has been set and use it as the final positioning data. That is, the precision improvement unit 225 may select the final positioning data from a plurality of positioning data according to the precision of the positioning data and the strength of the filter used in the positioning process.
 図10は、実施形態による複数の測位データのFix率の一例を示す図である。図10に示すように、本実施形態による複数の測位データは、複数の使用観測データとフィルタの組み合わせで算出され得る。例えば、撮影開始終了時刻でトリミングした使用観測データに対して、強いフィルタ(例えばElevation Mask 25°(仰角が25°以下の衛星の信号を除外する意味))を用いた場合、測位データd1のFix率が100%となった。また、撮影開始終了時刻に10秒の余裕時間を持たせてトリミングした使用観測データに対して、同じ強いフィルタ(EL mask 25°)を用いた場合、測位データd2のFix率は53.9%となった。また、所定の観測衛星数の確保開始終了時刻でトリミングした使用観測データに対して、同じ強いフィルタ(EL mask 25°)を用いた場合、測位データd3のFix率は66%となった。 FIG. 10 is a diagram illustrating an example of the fix rate of a plurality of positioning data according to the embodiment. As shown in FIG. 10, a plurality of positioning data according to the present embodiment can be calculated by a combination of a plurality of used observation data and filters. For example, if a strong filter (e.g., Elevation Mask 25° (meaning that signals from satellites with an elevation angle of 25° or less are excluded)) is used for the observation data used that is trimmed at the shooting start and end time, the Fix of positioning data d1 The rate became 100%. In addition, when using the same strong filter (EL mask 25°) for the observation data used that was trimmed with a margin of 10 seconds at the shooting start and end time, the fix rate of the positioning data d2 was 53.9%. It became. Furthermore, when the same strong filter (EL mask 25°) was used for the used observation data that was trimmed at the start and end time of securing a predetermined number of observation satellites, the fix rate of the positioning data d3 was 66%.
 一方、撮影開始終了時刻でトリミングした使用観測データに対して、弱いフィルタ(例えばEL mask 15°)を用いた場合、図10に示すように、測位データd4のFix率は100%となった。また、撮影開始終了時刻に10秒の余裕時間を持たせてトリミングした使用観測データに対して、同じ弱いフィルタ(EL mask 15°)を用いた場合、測位データd5のFix率が84.6%となった。また、所定の観測衛星数の確保開始終了時刻でトリミングした使用観測データに対して、同じ弱いフィルタ(EL mask 15°)を用いた場合、測位データd6のFix率が100%となった。 On the other hand, when a weak filter (for example, EL mask 15°) was used for the used observation data that was trimmed at the shooting start and end time, the fix rate of the positioning data d4 was 100%, as shown in FIG. 10. Furthermore, when using the same weak filter (EL mask 15°) for the observation data used that was trimmed with a margin of 10 seconds at the shooting start and end time, the fix rate of positioning data d5 was 84.6%. It became. Furthermore, when the same weak filter (EL mask 15°) was used for the used observation data that was trimmed at the start and end time of securing a predetermined number of observation satellites, the fix rate of the positioning data d6 was 100%.
 このような場合、高精度化部225は、Fix率が100%となった測位データd1、d4、d6のいずれかを、最終的な測位データとして採用する。この際、高精度化部225は、最も強いフィルタを用いて算出された測位データd1を、最終的な測位データとして採用してもよい。最も強いフィルタの使用により、ノイズが少なく、より正確な観測データが測位処理に用いられていると考えられるためである。 In such a case, the precision improvement unit 225 adopts any of the positioning data d1, d4, and d6 with a fix rate of 100% as the final positioning data. At this time, the precision improvement unit 225 may employ the positioning data d1 calculated using the strongest filter as the final positioning data. This is because it is thought that by using the strongest filter, more accurate observation data with less noise is used for positioning processing.
 なお、高精度化部225は、処理時間削減のため、より強いフィルタを用いた測位処理から行い、一定のFix率(例えば95%以上)(すなわち、一定の精度)の測位データが得られた段階で測位処理を終了してもよい。また、高精度化部225は、改め設定された回数分の測位処理を行うようにしてもよい。この場合、高精度化部225は、最もFix率が高い測位データを採用してもよいし、一定のFix率(例えば95%以上)の測位データを採用してもよい。一定のFix率の測位データが得られなかった場合、高精度化部225は、得られるまで引き続き測位処理を行ってもよい。なお、図10に示す各測位データのFix率は、一つの実験結果であって、本実施形態はこれに限定されない。 In addition, in order to reduce processing time, the precision improvement unit 225 performs positioning processing using a stronger filter, and obtains positioning data with a certain fix rate (for example, 95% or more) (i.e., a certain accuracy). The positioning process may be completed in stages. Further, the precision improvement unit 225 may perform positioning processing a re-set number of times. In this case, the precision improvement unit 225 may employ positioning data with the highest fix rate, or may employ positioning data with a fixed fix rate (for example, 95% or more). If positioning data with a constant fix rate is not obtained, the precision improvement unit 225 may continue to perform positioning processing until it is obtained. Note that the fix rate of each positioning data shown in FIG. 10 is one experimental result, and the present embodiment is not limited to this.
 図11は、本実施形態による使用観測データの切り出し(トリミング)を行った場合と行わなかった場合の測位データのFix率を比較する表である。図11に示す例では、さらに各使用観測データを用いて測位処理を行う際に各種maskのセットを含むフィルタが用いられた場合の測位データのFix率が示される。フィルタには、例えばグロナス衛星マスク(グロナス衛星の使用有無)、SNR mask、およびEL maskが用いられる。かかる実権結果によれば、トリミング無しでの各種フィルタを用いた最高Fix率は41.9%で、トリミング有りでの各種フィルタを用いた最高Fix率は100%であり、全体として41.9%から100%に測位精度が向上している。 FIG. 11 is a table that compares the fix rate of positioning data when the observation data used according to the present embodiment is trimmed and when it is not trimmed. The example shown in FIG. 11 further shows the fix rate of positioning data when a filter including a set of various masks is used when positioning processing is performed using each observation data used. For example, a GLONASS satellite mask (whether GLONASS satellites are used), an SNR mask, and an EL mask are used as the filter. According to the actual results, the highest fix rate using various filters without trimming is 41.9%, and the highest fix rate using various filters with trimming is 100%, making the overall fix rate 41.9%. Positioning accuracy has improved from 100% to 100%.
 また、高精度化部225は、複数の測位データのうち、Fix解(精度が高い部分)を組み合わせて、最終的な測位データを生成してもよい。例えば、高精度化部225は、Fix解を部分的に繋ぎ合わせて1つの測位データを生成してもよい。図12は、本実施形態によるFix解の繋ぎ合わせによる最終的な測位データの生成について説明する図である。図12に示す例では、測位データを形成する破線がFloat解、実線がFix解である。高精度化部225は、図12上段に示すような、一部にFix解を含む複数の測位データから、互いに(Float解の部分を)補い合うようFix解の部分を合成し、図12下段に示すような全てFix解の測位データを生成することが可能である。Fix解の抽出は、一定のFix率を有する測位データや、一定の強さのフィルタを用いた測位データから行うようにしてもよい。 Furthermore, the precision improvement unit 225 may generate final positioning data by combining Fix solutions (parts with high accuracy) among the plurality of positioning data. For example, the precision improvement unit 225 may partially connect the Fix solutions to generate one piece of positioning data. FIG. 12 is a diagram illustrating generation of final positioning data by connecting Fix solutions according to this embodiment. In the example shown in FIG. 12, the broken line forming the positioning data is the Float solution, and the solid line is the Fix solution. The precision improvement unit 225 synthesizes fixed solution parts from a plurality of positioning data partially including fixed solutions as shown in the upper part of FIG. 12 so as to complement each other (the float solution parts), and It is possible to generate all fixed solution positioning data as shown. The fix solution may be extracted from positioning data having a constant fix rate or positioning data using a filter with a constant strength.
 また、高精度化部225は、Fix率が高い測位データを用いる際に、各測位データを比較し、他のFix解と明らかに異なるFix解を含む測位データを排除するようにしてもよい。図13は、本実施形態による複数の観測データにおけるFix解の比較結果を示す図である。図13では、一例として、Z座標の比較を行う。ここで用いるZ座標の値は全てFix解であるが、データ5のみ、データ1~データ4と明らかに異なることが分かる。これにより、データ5は誤ったFix解である可能性が高く、データ5を除外することで、測位精度をより向上させることができる。また、高精度化部225は、Fix解に限らず、Float解とも比較を行ってもよい。誤ったFix解は、Float解よりも大きな誤差が生じることがあるため、Float解も参考にし得る。 Furthermore, when using positioning data with a high fix rate, the precision improvement unit 225 may compare each piece of positioning data and exclude positioning data that includes a fix solution that is clearly different from other fix solutions. FIG. 13 is a diagram showing a comparison result of Fix solutions in a plurality of observation data according to this embodiment. In FIG. 13, as an example, Z coordinates are compared. All the Z coordinate values used here are fixed solutions, but it can be seen that only data 5 is clearly different from data 1 to data 4. Thereby, there is a high possibility that data 5 is an incorrect Fix solution, and by excluding data 5, positioning accuracy can be further improved. Furthermore, the precision improvement unit 225 may compare not only the Fix solution but also the Float solution. Since an incorrect Fix solution may have a larger error than a Float solution, the Float solution may also be used as a reference.
 以上、高精度化部225による最終的な測位データの生成について説明した。これにより、測位データの精度を、さらに向上させること(高精度化)ができる。高精度化した測位データは、記憶部250に格納され得る。 The generation of final positioning data by the precision improvement unit 225 has been described above. Thereby, the accuracy of positioning data can be further improved (higher accuracy). The highly accurate positioning data may be stored in the storage unit 250.
 次いで、図3に戻り、表示制御部226について説明する。表示制御部226は、高精度化部225により高精度化された測位データを、表示部240に表示する制御を行う。なお、本実施形態では、高精度化した測位データの出力の一例として表示するが、高精度化した測位データの出力は、表示に限定されない。例えば、高精度化した測位データは、通信部210から外部装置に送信されてもよい。 Next, returning to FIG. 3, the display control section 226 will be explained. The display control unit 226 performs control to display the positioning data whose accuracy has been improved by the accuracy improvement unit 225 on the display unit 240. Note that in this embodiment, the output of highly accurate positioning data is displayed as an example of output, but the output of highly accurate positioning data is not limited to display. For example, highly accurate positioning data may be transmitted from the communication unit 210 to an external device.
 (操作入力部230)
 操作入力部230は、ユーザからの操作を付け付け、入力情報を制御部220に出力する。操作入力部230は、例えばタッチパネル、ボタン、スイッチ、キーボード等の各種入力デバイスにより実現される。
(Operation input section 230)
The operation input unit 230 attaches an operation from the user and outputs input information to the control unit 220. The operation input unit 230 is realized by various input devices such as a touch panel, a button, a switch, a keyboard, etc., for example.
 (表示部240)
 表示部240は、操作画面や、高精度化された最終的な測位データを含む画面等の各種画面を表示する機能を有する。表示部240は、例えば液晶ディスプレイ(LCD:Liquid Crystal Display)装置、OLED(Organic Light Emitting Diode)装置等により実現され得る。
(Display section 240)
The display unit 240 has a function of displaying various screens such as an operation screen and a screen containing highly accurate final positioning data. The display unit 240 may be realized by, for example, a liquid crystal display (LCD) device, an organic light emitting diode (OLED) device, or the like.
 (記憶部250)
 記憶部250は、制御部220の処理に用いられるプログラムや演算パラメータ等を記憶するROM(Read Only Memory)、および適宜変化するパラメータ等を一時記憶するRAM(Random Access Memory)により実現される。
(Storage unit 250)
The storage unit 250 is realized by a ROM (Read Only Memory) that stores programs, calculation parameters, etc. used in the processing of the control unit 220, and a RAM (Random Access Memory) that temporarily stores parameters that change as appropriate.
 以上、情報処理装置20の構成について具体的に説明した。なお、本実施形態による情報処理装置20の構成は図3に示す例に限定されない。例えば、情報処理装置20は、複数の装置により実現されてもよい。例えば、移動体観測データ取得部121、基準局観測データ取得部122、使用時刻決定部123、および測位処理部124の機能と、高精度化125の機能とが、別の装置で実現されてもよい。また、情報処理装置20の少なくともいずれかの構成を外部装置に設けてもよい。また、情報処理装置20は、図3に示す構成を全て有しなくともよい。 The configuration of the information processing device 20 has been specifically described above. Note that the configuration of the information processing device 20 according to this embodiment is not limited to the example shown in FIG. 3. For example, the information processing device 20 may be realized by a plurality of devices. For example, the functions of the mobile observation data acquisition section 121, the reference station observation data acquisition section 122, the usage time determination section 123, and the positioning processing section 124, and the function of the precision improvement 125 may be realized by different devices. . Further, at least one configuration of the information processing device 20 may be provided in an external device. Further, the information processing device 20 does not need to have all the configurations shown in FIG. 3.
 <<3.動作処理>>
 次に、本実施形態に係る測位処理システムの動作処理について図面を用いて具体的に説明する。図14は、本実施形態による入力波形データの生成処理の流れの一例を示すフローチャートである。
<<3. Operation processing >>
Next, operation processing of the positioning processing system according to the present embodiment will be specifically explained using the drawings. FIG. 14 is a flowchart illustrating an example of the flow of input waveform data generation processing according to this embodiment.
 図14に示すように、まず、情報処理装置20は、移動体10の観測データ(移動局観測データ)を取得する(ステップS103)。続いて、情報処理装置20は、取得した移動体10の観測データ(移動局観測データ)に対して、測位処理に使用する使用観測データの使用開始時刻および使用終了時刻を複数組決定する(ステップS106)。 As shown in FIG. 14, the information processing device 20 first obtains observation data (mobile station observation data) of the mobile object 10 (step S103). Subsequently, the information processing device 20 determines a plurality of sets of usage start times and usage end times of usage observation data used for positioning processing for the acquired observation data (mobile station observation data) of the mobile object 10 (step S106).
 その後、情報処理装置20は、複数の使用観測データと、基準局の観測データを用いて、複数の測位データを算出(測位処理)する(ステップS109)。次いで、情報処理装置20は、複数の測位データに基づいて、測位データの高精度化を行なう(ステップS112)。 After that, the information processing device 20 calculates a plurality of positioning data (positioning process) using the plurality of used observation data and the observation data of the reference station (step S109). Next, the information processing device 20 improves the accuracy of the positioning data based on the plurality of positioning data (step S112).
 次に、情報処理装置20は、高精度化した測位データを出力(表示)する(ステップS115)。そして、本動作は終了する。 Next, the information processing device 20 outputs (displays) highly accurate positioning data (step S115). Then, this operation ends.
 以上、本実施形態による測位処理の流れの一例について説明した。なお、図14に示す測位処理は一例であって、本開示はこれに限定されない。 An example of the flow of the positioning process according to this embodiment has been described above. Note that the positioning process shown in FIG. 14 is an example, and the present disclosure is not limited thereto.
 <<5.効果>>
 本実施形態では、測位処理に用いる観測データの使用開始時刻および使用終了時刻を複数組決定し、複数の使用観測データから測位処理により複数の測位データを算出して、当該複数の測位データから最終的な測位データを生成することで、さらなる測位精度向上を実現する。
<<5. Effect >>
In this embodiment, multiple sets of usage start time and usage end time of observation data used for positioning processing are determined, multiple positioning data are calculated by positioning processing from the multiple usage observation data, and a final By generating accurate positioning data, we can further improve positioning accuracy.
 また、測位処理において、各使用観測データに対してフィルタが異なる測位処理を複数回行うことで、さらに複数の測位データを算出し、最終的な測位データの測位精度を向上させることができる。 Furthermore, in the positioning process, by performing the positioning process multiple times with different filters for each observation data used, it is possible to further calculate a plurality of positioning data and improve the positioning accuracy of the final positioning data.
 また、観測データからトリミングした使用観測データを用いることは、測位処理に用いるデータの削減に繋がり、処理時間を短くする効果も奏する。例えば撮影開始終了時刻に基づいて使用観測データをトリミングした場合、全観測データに対してデータが半分の長さになる場合もある。 Furthermore, using the observation data that has been trimmed from the observation data leads to a reduction in the amount of data used in the positioning process, which also has the effect of shortening the processing time. For example, when the observation data to be used is trimmed based on the shooting start and end time, the length of the data may become half of the total observation data.
 <<6.補足>>
 以上、添付図面を参照しながら本開示の好適な実施形態について詳細に説明したが、本技術はかかる例に限定されない。本開示の技術分野における通常の知識を有する者であれば、請求の範囲に記載された技術的思想の範疇内において、各種の変更例または修正例に想到し得ることは明らかであり、これらについても、当然に本開示の技術的範囲に属するものと了解される。
<<6. Supplement >>
Although preferred embodiments of the present disclosure have been described above in detail with reference to the accompanying drawings, the present technology is not limited to such examples. It is clear that a person with ordinary knowledge in the technical field of the present disclosure can come up with various changes or modifications within the scope of the technical idea described in the claims, and It is understood that these also naturally fall within the technical scope of the present disclosure.
 また、上述した移動体10、または情報処理装置20に内蔵されるCPU、ROM、およびRAM等のハードウェアに、移動体10、または情報処理装置20の機能を発揮させるための1以上のコンピュータプログラムも作成可能である。また、当該1以上のコンピュータプログラムを記憶させたコンピュータ読み取り可能な記憶媒体も提供される。 In addition, one or more computer programs for causing hardware such as a CPU, ROM, and RAM built in the mobile body 10 or the information processing device 20 described above to exhibit the functions of the mobile body 10 or the information processing device 20. can also be created. Also provided is a computer readable storage medium storing the one or more computer programs.
 また、本明細書に記載された効果は、あくまで説明的または例示的なものであって限定的ではない。つまり、本開示に係る技術は、上記の効果とともに、または上記の効果に代えて、本明細書の記載から当業者には明らかな他の効果を奏しうる。 Furthermore, the effects described in this specification are merely explanatory or illustrative, and are not limiting. In other words, the technology according to the present disclosure can have other effects that are obvious to those skilled in the art from the description of this specification, in addition to or in place of the above effects.
 なお、本技術は以下のような構成も取ることができる。
(1)
 移動局により取得された、航行衛星から受信した信号を含む観測データに対して、測位処理に使用するデータの使用開始時刻および使用終了時刻を複数組決定し、
 前記複数組による各使用観測データと、基準局の観測データと、に基づいて、測位処理により複数の測位データを算出し、
 前記複数の測位データに基づいて、最終的な測位データを生成する、
制御部を備える、情報処理装置。
(2)
 前記制御部は、前記測位処理において複数のフィルタを用い、各使用観測データに対して各々複数の測位データを算出する、前記(1)に記載の情報処理装置。
(3)
 前記制御部は、前記使用開始時刻および前記使用終了時刻を、前記移動局の移動開始終了時刻、前記移動局による撮影開始終了時刻、および前記移動局による所定の観測衛星数の確保開始終了時刻の少なくともいずれかに基づいて決定する、前記(1)または(2)に記載の情報処理装置。
(4)
 前記制御部は、前記使用開始時刻および前記使用終了時刻を、前記移動局による撮影開始終了時刻に所定の余裕時間を追加して決定する、前記(3)に記載の情報処理装置。
(5)
 前記制御部は、前記使用開始時刻および前記使用終了時刻を、前記移動局による観測時の環境に基づいて決定する、前記(1)~(4)のいずれか1項に記載の情報処理装置。
(6)
 前記制御部は、前記使用開始時刻および前記使用終了時刻を、前記移動局による観測時の信号強度に基づいて決定する、前記(1)~(5)のいずれか1項に記載の情報処理装置。
(7)
 前記移動局は、自律飛行により空間内を移動する移動体である、前記(1)~(6)のいずれか1項に記載の情報処理装置。
(8)
 前記制御部は、前記使用開始時刻および前記使用終了時刻を、前記移動体の離着陸時刻に基づいて決定する、前記(7)に記載の情報処理装置。
(9)
 前記制御部は、前記使用開始時刻および前記使用終了時刻を、前記移動体の高度情報に基づいて決定する、前記(7)に記載の情報処理装置。
(10)
 前記観測データは、前記移動局により移動中に継続的に取得された前記信号の受信時刻を含む、前記(1)~(9)のいずれか1項に記載の情報処理装置。
(11)
 前記制御部は、前記複数の測位データのうち、最も精度が高い測位データを、最終的な測位データとする、前記(1)~(10)のいずれか1項に記載の情報処理装置。
(12)
 前記制御部は、前記複数の測位データのうち、精度の高さと、測位処理で用いたフィルタの強さに応じて、最終的な測位データを選択する、前記(1)~(11)のいずれか1項に記載の情報処理装置。
(13)
 前記制御部は、より強いフィルタを用いた測位処理から行い、一定の精度の測位データが得られた段階で測位処理を終了する、前記(1)~(12)のいずれか1項に記載の情報処理装置。
(14)
 前記制御部は、改め設定された回数分の測位処理を行い、最も精度が高い測位データを、最終的な測位データとする、前記(1)~(13)のいずれか1項に記載の情報処理装置。
(15)
 前記制御部は、前記複数の測位データに基づいて、精度が高い部分を組み合わせて、最終的な測位データを生成する、前記(1)~(13)のいずれか1項に記載の情報処理装置。
(16)
 前記制御部は、前記複数の測位データを比較し、明らかに異なる解を含む測位データを排除した上で、最終的な測位データを生成する、前記(11)~(15)のいずれか1項に記載の情報処理装置。
(17)
 前記測位処理として、干渉測位法が用いられる、前記(1)~(16)のいずれか1項に記載の情報処理装置。
(18)
 前記干渉測位法として、PPK(Post Processing Kinematic)測位法が用いられる、前記(17)に記載の情報処理装置。
(19)
 プロセッサが、
 移動局により取得された、航行衛星から受信した信号を含む観測データに対して、測位処理に使用するデータの使用開始時刻および使用終了時刻を複数組決定することと、
 前記複数組による各使用観測データと、基準局の観測データと、に基づいて、測位処理により複数の測位データを算出することと、
 前記複数の測位データに基づいて、最終的な測位データを生成することと、
を含む、情報処理方法。
(20)
 コンピュータを、
 移動局により取得された、航行衛星から受信した信号を含む観測データに対して、測位処理に使用するデータの使用開始時刻および使用終了時刻を複数組決定し、
 前記複数組による各使用観測データと、基準局の観測データと、に基づいて、測位処理により複数の測位データを算出し、
 前記複数の測位データに基づいて、最終的な測位データを生成する、
制御部として機能させる、プログラム。
(21)
 移動局により取得された、航行衛星から受信した信号を含む観測データに対して、測位処理に使用するデータの使用開始時刻および使用終了時刻を複数組決定し、
 前記複数組による各使用観測データと、基準局の観測データと、に基づいて、測位処理により複数の測位データを算出する、
制御部を備える、情報処理装置。
(22)
 移動局により取得された、航行衛星から受信した信号を含む観測データから、複数組の使用開始時刻および使用終了時刻により切り出された各使用観測データと、基準局の観測データと、に基づいて測位処理により算出された複数の測位データに基づいて、最終的な測位データを生成する制御部を備える、情報処理装置。
Note that the present technology can also have the following configuration.
(1)
Determining multiple sets of usage start times and usage end times of data used for positioning processing for observation data acquired by a mobile station and including signals received from navigation satellites,
Calculating a plurality of positioning data through positioning processing based on the observation data used by the plurality of sets and the observation data of the reference station,
generating final positioning data based on the plurality of positioning data;
An information processing device including a control unit.
(2)
The information processing device according to (1), wherein the control unit uses a plurality of filters in the positioning process to calculate a plurality of positioning data for each used observation data.
(3)
The control unit sets the use start time and use end time to a start and end time of movement of the mobile station, a start and end time of photographing by the mobile station, and a start and end time of securing a predetermined number of observation satellites by the mobile station. The information processing device according to (1) or (2), wherein the information processing device is determined based on at least one of the following.
(4)
The information processing device according to (3), wherein the control unit determines the use start time and the use end time by adding a predetermined margin time to the start and end time of photographing by the mobile station.
(5)
The information processing device according to any one of (1) to (4), wherein the control unit determines the use start time and the use end time based on an environment at the time of observation by the mobile station.
(6)
The information processing device according to any one of (1) to (5), wherein the control unit determines the use start time and the use end time based on signal strength at the time of observation by the mobile station. .
(7)
The information processing device according to any one of (1) to (6), wherein the mobile station is a mobile body that moves in space by autonomous flight.
(8)
The information processing device according to (7), wherein the control unit determines the use start time and the use end time based on takeoff and landing times of the mobile object.
(9)
The information processing device according to (7), wherein the control unit determines the use start time and the use end time based on altitude information of the mobile object.
(10)
The information processing device according to any one of (1) to (9), wherein the observation data includes reception times of the signals continuously acquired by the mobile station while moving.
(11)
The information processing device according to any one of (1) to (10), wherein the control unit sets the most accurate positioning data among the plurality of positioning data as the final positioning data.
(12)
The control unit selects the final positioning data from among the plurality of positioning data according to the degree of accuracy and the strength of the filter used in the positioning process. The information processing device according to item 1.
(13)
The control unit according to any one of (1) to (12) above, performs positioning processing using a stronger filter and ends the positioning processing when positioning data with a certain accuracy is obtained. Information processing device.
(14)
The information according to any one of (1) to (13) above, wherein the control unit performs positioning processing for a re-set number of times and sets the positioning data with the highest accuracy as the final positioning data. Processing equipment.
(15)
The information processing device according to any one of (1) to (13), wherein the control unit generates final positioning data by combining highly accurate parts based on the plurality of positioning data. .
(16)
Any one of (11) to (15) above, wherein the control unit compares the plurality of positioning data, eliminates positioning data that includes clearly different solutions, and then generates final positioning data. The information processing device described in .
(17)
The information processing device according to any one of (1) to (16), wherein an interferometric positioning method is used as the positioning process.
(18)
The information processing device according to (17), wherein a PPK (Post Processing Kinematic) positioning method is used as the interferometric positioning method.
(19)
The processor
determining a plurality of sets of usage start times and usage end times of data used for positioning processing for observation data acquired by a mobile station and including signals received from navigation satellites;
Calculating a plurality of positioning data by a positioning process based on each observation data used by the plurality of sets and observation data of a reference station;
Generating final positioning data based on the plurality of positioning data;
information processing methods, including
(20)
computer,
Determining multiple sets of usage start times and usage end times of data used for positioning processing for observation data acquired by a mobile station and including signals received from navigation satellites,
Calculating a plurality of positioning data through positioning processing based on the observation data used by the plurality of sets and the observation data of the reference station,
generating final positioning data based on the plurality of positioning data;
A program that functions as a control unit.
(21)
Determining multiple sets of usage start times and usage end times of data used for positioning processing for observation data acquired by a mobile station and including signals received from navigation satellites,
calculating a plurality of positioning data through positioning processing based on the observation data used by the plurality of sets and the observation data of the reference station;
An information processing device including a control unit.
(22)
Positioning processing is performed based on the observation data obtained by the mobile station, including the signals received from the navigation satellite, and the observation data of the reference station and the observation data extracted from multiple sets of use start and end times. An information processing device including a control unit that generates final positioning data based on a plurality of positioning data calculated by.
 2 航法衛星
 3 基準局
 10 移動体
 110 制御部
 111 自己位置推定部
 112 飛行制御部
 113 観測データ記憶制御部
 120 位置センサ
 130 撮像部
 140 高度センサ
 150 記憶部
 160 通信部
 170 飛行機構
 20 情報処理装置
 210 通信部
 220 制御部
 221 移動局観測データ取得部
 222 基準局観測データ取得部
 223 使用時刻決定部
 224 測位処理部
 225 高精度化部
 226 表示制御部
 230 操作入力部
 240 表示部
 250 記憶部
2 Navigation satellite 3 Reference station 10 Mobile object 110 Control unit 111 Self-position estimation unit 112 Flight control unit 113 Observation data storage control unit 120 Position sensor 130 Imaging unit 140 Altitude sensor 150 Storage unit 160 Communication unit 170 Flight mechanism 20 Information processing device 210 Communication Units 220 Control unit 221 Mobile station observation data acquisition unit 222 Reference station observation data acquisition unit 223 Use time determination unit 224 Positioning processing unit 225 High precision unit 226 Display control unit 230 Operation input unit 240 Display unit 250 Storage unit

Claims (20)

  1.  移動局により取得された、航行衛星から受信した信号を含む観測データに対して、測位処理に使用するデータの使用開始時刻および使用終了時刻を複数組決定し、
     前記複数組による各使用観測データと、基準局の観測データと、に基づいて、測位処理により複数の測位データを算出し、
     前記複数の測位データに基づいて、最終的な測位データを生成する、
    制御部を備える、情報処理装置。
    Determining multiple sets of usage start times and usage end times of data used for positioning processing for observation data acquired by a mobile station and including signals received from navigation satellites,
    Calculating a plurality of positioning data through positioning processing based on the observation data used by the plurality of sets and the observation data of the reference station,
    generating final positioning data based on the plurality of positioning data;
    An information processing device including a control unit.
  2.  前記制御部は、前記測位処理において複数のフィルタを用い、各使用観測データに対して各々複数の測位データを算出する、請求項1に記載の情報処理装置。 The information processing device according to claim 1, wherein the control unit uses a plurality of filters in the positioning process to calculate a plurality of positioning data for each used observation data.
  3.  前記制御部は、前記使用開始時刻および前記使用終了時刻を、前記移動局の移動開始終了時刻、前記移動局による撮影開始終了時刻、および前記移動局による所定の観測衛星数の確保開始終了時刻の少なくともいずれかに基づいて決定する、請求項1に記載の情報処理装置。 The control unit sets the use start time and use end time to a start and end time of movement of the mobile station, a start and end time of photographing by the mobile station, and a start and end time of securing a predetermined number of observation satellites by the mobile station. The information processing device according to claim 1, wherein the information processing device makes the determination based on at least one of the following.
  4.  前記制御部は、前記使用開始時刻および前記使用終了時刻を、前記移動局による撮影開始終了時刻に所定の余裕時間を追加して決定する、請求項3に記載の情報処理装置。 The information processing device according to claim 3, wherein the control unit determines the use start time and the use end time by adding a predetermined margin time to the start and end time of shooting by the mobile station.
  5.  前記制御部は、前記使用開始時刻および前記使用終了時刻を、前記移動局による観測時の環境に基づいて決定する、請求項1に記載の情報処理装置。 The information processing device according to claim 1, wherein the control unit determines the use start time and the use end time based on an environment at the time of observation by the mobile station.
  6.  前記制御部は、前記使用開始時刻および前記使用終了時刻を、前記移動局による観測時の信号強度に基づいて決定する、請求項1に記載の情報処理装置。 The information processing device according to claim 1, wherein the control unit determines the use start time and the use end time based on signal strength at the time of observation by the mobile station.
  7.  前記移動局は、自律飛行により空間内を移動する移動体である、請求項1に記載の情報処理装置。 The information processing device according to claim 1, wherein the mobile station is a mobile body that moves in space by autonomous flight.
  8.  前記制御部は、前記使用開始時刻および前記使用終了時刻を、前記移動体の離着陸時刻に基づいて決定する、請求項7に記載の情報処理装置。 The information processing device according to claim 7, wherein the control unit determines the use start time and the use end time based on takeoff and landing times of the mobile object.
  9.  前記制御部は、前記使用開始時刻および前記使用終了時刻を、前記移動体の高度情報に基づいて決定する、請求項7に記載の情報処理装置。 The information processing device according to claim 7, wherein the control unit determines the use start time and the use end time based on altitude information of the mobile object.
  10.  前記観測データは、前記移動局により移動中に継続的に取得された前記信号の受信時刻を含む、請求項1に記載の情報処理装置。 The information processing device according to claim 1, wherein the observation data includes reception times of the signals continuously acquired by the mobile station while moving.
  11.  前記制御部は、前記複数の測位データのうち、最も精度が高い測位データを、最終的な測位データとする、請求項1に記載の情報処理装置。 The information processing device according to claim 1, wherein the control unit sets the most accurate positioning data among the plurality of positioning data as the final positioning data.
  12.  前記制御部は、前記複数の測位データのうち、精度の高さと、測位処理で用いたフィルタの強さに応じて、最終的な測位データを選択する、請求項1に記載の情報処理装置。 The information processing device according to claim 1, wherein the control unit selects final positioning data from among the plurality of positioning data according to high accuracy and strength of a filter used in the positioning process.
  13.  前記制御部は、より強いフィルタを用いた測位処理から行い、一定の精度の測位データが得られた段階で測位処理を終了する、請求項1に記載の情報処理装置。 The information processing device according to claim 1, wherein the control unit performs positioning processing using a stronger filter, and ends the positioning processing when positioning data with a certain accuracy is obtained.
  14.  前記制御部は、改め設定された回数分の測位処理を行い、最も精度が高い測位データを、最終的な測位データとする、請求項1に記載の情報処理装置。 The information processing device according to claim 1, wherein the control unit performs positioning processing a re-set number of times and sets positioning data with the highest accuracy as final positioning data.
  15.  前記制御部は、前記複数の測位データに基づいて、精度が高い部分を組み合わせて、最終的な測位データを生成する、請求項1に記載の情報処理装置。 The information processing device according to claim 1, wherein the control unit generates final positioning data by combining highly accurate parts based on the plurality of positioning data.
  16.  前記制御部は、前記複数の測位データを比較し、明らかに異なる解を含む測位データを排除した上で、最終的な測位データを生成する、請求項11に記載の情報処理装置。 The information processing device according to claim 11, wherein the control unit compares the plurality of positioning data, eliminates positioning data that includes clearly different solutions, and then generates final positioning data.
  17.  前記測位処理として、干渉測位法が用いられる、請求項1に記載の情報処理装置。 The information processing device according to claim 1, wherein an interferometric positioning method is used as the positioning process.
  18.  前記干渉測位法として、PPK(Post Processing Kinematic)測位法が用いられる、請求項17に記載の情報処理装置。 The information processing device according to claim 17, wherein a PPK (Post Processing Kinematic) positioning method is used as the interferometric positioning method.
  19.  プロセッサが、
     移動局により取得された、航行衛星から受信した信号を含む観測データに対して、測位処理に使用するデータの使用開始時刻および使用終了時刻を複数組決定することと、
     前記複数組による各使用観測データと、基準局の観測データと、に基づいて、測位処理により複数の測位データを算出することと、
     前記複数の測位データに基づいて、最終的な測位データを生成することと、
    を含む、情報処理方法。
    The processor
    determining a plurality of sets of usage start times and usage end times of data used for positioning processing for observation data acquired by a mobile station and including signals received from navigation satellites;
    Calculating a plurality of positioning data by a positioning process based on each observation data used by the plurality of sets and observation data of a reference station;
    Generating final positioning data based on the plurality of positioning data;
    information processing methods, including
  20.  コンピュータを、
     移動局により取得された、航行衛星から受信した信号を含む観測データに対して、測位処理に使用するデータの使用開始時刻および使用終了時刻を複数組決定し、
     前記複数組による各使用観測データと、基準局の観測データと、に基づいて、測位処理により複数の測位データを算出し、
     前記複数の測位データに基づいて、最終的な測位データを生成する、
    制御部として機能させる、プログラム。
    computer,
    Determining multiple sets of usage start times and usage end times of data used for positioning processing for observation data acquired by a mobile station and including signals received from navigation satellites,
    Calculating a plurality of positioning data through positioning processing based on the observation data used by the plurality of sets and the observation data of the reference station,
    generating final positioning data based on the plurality of positioning data;
    A program that functions as a control unit.
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Citations (6)

* Cited by examiner, † Cited by third party
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JP2010078382A (en) * 2008-09-25 2010-04-08 Hitachi Zosen Corp Position measuring device and position measuring method by gps
JP2013083480A (en) * 2011-10-06 2013-05-09 Electronic Navigation Research Institute Method and apparatus for selecting satellite used for rtk positioning computation
JP2018119818A (en) * 2017-01-23 2018-08-02 紘生 因 Setting method for parameter and parallel computer used for kinematic positioning
CN110749909A (en) * 2019-07-25 2020-02-04 中国民用航空中南地区空中交通管理局 Aircraft position high-precision positioning method based on multi-constellation network post difference
JP2021001736A (en) * 2019-06-19 2021-01-07 清水建設株式会社 Method for determining setting parameter of positioning algorithm
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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2010078382A (en) * 2008-09-25 2010-04-08 Hitachi Zosen Corp Position measuring device and position measuring method by gps
JP2013083480A (en) * 2011-10-06 2013-05-09 Electronic Navigation Research Institute Method and apparatus for selecting satellite used for rtk positioning computation
JP2018119818A (en) * 2017-01-23 2018-08-02 紘生 因 Setting method for parameter and parallel computer used for kinematic positioning
JP2021001736A (en) * 2019-06-19 2021-01-07 清水建設株式会社 Method for determining setting parameter of positioning algorithm
CN110749909A (en) * 2019-07-25 2020-02-04 中国民用航空中南地区空中交通管理局 Aircraft position high-precision positioning method based on multi-constellation network post difference
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