CN109084765A - Walking positioning method, device and storage medium in a kind of pedestrian room - Google Patents
Walking positioning method, device and storage medium in a kind of pedestrian room Download PDFInfo
- Publication number
- CN109084765A CN109084765A CN201810965290.1A CN201810965290A CN109084765A CN 109084765 A CN109084765 A CN 109084765A CN 201810965290 A CN201810965290 A CN 201810965290A CN 109084765 A CN109084765 A CN 109084765A
- Authority
- CN
- China
- Prior art keywords
- pedestrian
- walking
- data
- parameters
- geomagnetic
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 42
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 49
- 239000002245 particle Substances 0.000 claims abstract description 32
- 238000012806 monitoring device Methods 0.000 claims abstract description 4
- 230000001133 acceleration Effects 0.000 claims description 25
- 238000012544 monitoring process Methods 0.000 claims description 15
- 238000004590 computer program Methods 0.000 claims description 9
- 238000012937 correction Methods 0.000 claims description 9
- 238000012545 processing Methods 0.000 claims description 9
- 238000001914 filtration Methods 0.000 claims description 8
- 238000001514 detection method Methods 0.000 claims description 6
- 238000005259 measurement Methods 0.000 claims description 6
- 230000005389 magnetism Effects 0.000 abstract 4
- 230000000694 effects Effects 0.000 description 6
- 238000012952 Resampling Methods 0.000 description 4
- 238000010586 diagram Methods 0.000 description 4
- 239000011159 matrix material Substances 0.000 description 3
- 230000005484 gravity Effects 0.000 description 2
- 238000005070 sampling Methods 0.000 description 2
- 238000012360 testing method Methods 0.000 description 2
- 241000282414 Homo sapiens Species 0.000 description 1
- 238000000342 Monte Carlo simulation Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000006073 displacement reaction Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 230000004927 fusion Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000036544 posture Effects 0.000 description 1
- 230000007704 transition Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
- G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
- G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
- G01C21/18—Stabilised platforms, e.g. by gyroscope
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/005—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 with correlation of navigation data from several sources, e.g. map or contour matching
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/04—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by terrestrial means
- G01C21/08—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by terrestrial means involving use of the magnetic field of the earth
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
- G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
- G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
- G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/20—Instruments for performing navigational calculations
- G01C21/206—Instruments for performing navigational calculations specially adapted for indoor navigation
Landscapes
- Engineering & Computer Science (AREA)
- Remote Sensing (AREA)
- Radar, Positioning & Navigation (AREA)
- Automation & Control Theory (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Environmental & Geological Engineering (AREA)
- General Life Sciences & Earth Sciences (AREA)
- Geology (AREA)
- Navigation (AREA)
- Position Fixing By Use Of Radio Waves (AREA)
- Traffic Control Systems (AREA)
Abstract
The present invention provides walking positioning method, device and storage medium in a kind of pedestrian room, and method includes: that the initial data of target pedestrian walking is obtained by the way that the monitoring device of target pedestrian's foot is arranged in, and initial data includes state parameter and earth magnetism characteristic quantity；State parameter is resolved, obtains walking parameter, and eliminate the error of walking parameter, position estimation is carried out according to the walking parameter through eliminating error, obtains the position estimation data of target pedestrian current location；Earth magnetism characteristic quantity is matched with the earth magnetism characteristic quantity in the earth magnetism fingerprint base, to obtain target pedestrian's current geographic position data；Position estimated data and current geographic position data are calculated according to particle filter algorithm, to obtain target pedestrian current location, improve the precision of positioning.
Description
Technical Field
The invention mainly relates to the technical field of positioning, in particular to a pedestrian indoor walking positioning method, a pedestrian indoor walking positioning device and a storage medium.
Background
Along with the development of human beings and the progress of society, people have more and more social activities, and people have more and more travel and can not leave the demand for position information. In the current society, most of activities of people are performed indoors, signals of a satellite positioning system are influenced when the satellite positioning system is indoors, the effect of obtaining position information of people through the satellite positioning system when the satellite positioning system is indoors is not ideal, indoor positioning of pedestrians is achieved through Wi-Fi/Bluetooth equipment and a GPS/Beidou system at present, but the pedestrian cannot be used when the pedestrian is not located indoors, meanwhile, the situation that the Wi-Fi/Bluetooth equipment is greatly put into use exists, the equipment needs to be maintained regularly, and the cost is high.
Disclosure of Invention
The invention aims to solve the technical problem of the prior art and provides a pedestrian indoor walking positioning method, a pedestrian indoor walking positioning device and a storage medium.
The technical scheme for solving the technical problems is as follows: a pedestrian indoor walking positioning method comprises the following steps:
acquiring original data of walking of a target pedestrian through monitoring equipment arranged on the foot of the target pedestrian, wherein the original data comprises state parameters of the current position of the target pedestrian and geomagnetic characteristic quantity;
resolving the state parameters to obtain walking parameters, eliminating errors of the walking parameters, and performing position estimation according to the walking parameters with the errors eliminated to obtain position estimation data of the current position of the target pedestrian;
establishing a geomagnetic fingerprint database, collecting a plurality of indoor geomagnetic characteristic quantities, and respectively associating and storing the geomagnetic characteristic quantities with corresponding geographic position data;
matching the geomagnetic characteristic quantity of the current position of the target pedestrian with the geomagnetic characteristic quantity in the geomagnetic fingerprint database, and obtaining current geographic position data of the target pedestrian according to the matched geomagnetic characteristic quantity;
and calculating the position estimation data and the current geographical position data according to a particle filter algorithm so as to obtain the current position of the target pedestrian.
Another technical solution of the present invention for solving the above technical problems is as follows: a pedestrian indoor walking positioning device, comprising:
the system comprises a measuring module, a processing module and a processing module, wherein the measuring module is used for acquiring original walking data of a target pedestrian through monitoring equipment arranged on the foot of the target pedestrian, and the original walking data comprises state parameters and geomagnetic characteristic quantities;
the main control module is used for resolving the state parameters to obtain walking parameters, eliminating errors of the walking parameters, and performing position estimation according to the walking parameters with the errors eliminated to obtain position estimation data of the current position of the target pedestrian;
the geomagnetic fingerprint database creating module is used for acquiring a plurality of indoor geomagnetic characteristic quantities, and respectively associating and storing the geomagnetic characteristic quantities with corresponding geographic position data;
the geomagnetic matching module is used for matching the geomagnetic characteristic quantity of the current position of the target pedestrian with the geomagnetic characteristic quantity in the geomagnetic fingerprint database and obtaining current geographic position data of the target pedestrian according to the matched geomagnetic characteristic quantity;
and the main control module is also used for calculating the position estimation data and the current geographic position data according to a particle filter algorithm so as to obtain the current position of the target pedestrian.
Another technical solution of the present invention for solving the above technical problems is as follows: a pedestrian indoor walking location method comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the method when executing the computer program.
Another technical solution of the present invention for solving the above technical problems is as follows: a computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method as described.
The invention has the beneficial effects that: the method comprises the steps of measuring original data of a target pedestrian when the target pedestrian walks through monitoring equipment of feet of the target pedestrian, resolving the original data to obtain walking parameters, estimating the walking parameters through a position estimation algorithm to obtain position estimation data, matching a geomagnetic intensity value corresponding to the position of the target pedestrian according to a created geomagnetic fingerprint database, and combining the position estimation data and the geomagnetic intensity value according to a particle filtering algorithm to obtain the current position of the target pedestrian and improve positioning accuracy.
Drawings
Fig. 1 is a flowchart of a method for positioning indoor walking of a pedestrian according to an embodiment of the present invention;
fig. 2 is a flowchart of a method for positioning indoor walking of a pedestrian according to another embodiment of the present invention;
FIG. 3 is a diagram illustrating the zero-speed detection effect of a pedestrian according to an embodiment of the present invention;
fig. 4 is a diagram of an indoor geomagnetic fingerprint database according to an embodiment of the present invention;
fig. 5 is a block diagram of a positioning device for indoor walking of pedestrians according to an embodiment of the present invention;
FIG. 6 is a graph of experimental results provided by the present invention.
Detailed Description
The principles and features of this invention are described below in conjunction with the following drawings, which are set forth by way of illustration only and are not intended to limit the scope of the invention.
Fig. 1 is a flowchart of a method for positioning indoor walking of a pedestrian according to an embodiment of the present invention;
as shown in fig. 1, a pedestrian indoor walking positioning method includes the following steps:
acquiring original data of walking of a target pedestrian through monitoring equipment arranged on the foot of the target pedestrian, wherein the original data comprises state parameters of the current position of the target pedestrian and geomagnetic characteristic quantity;
resolving the state parameters and the geomagnetic characteristic quantity to obtain walking parameters, eliminating errors of the walking parameters, and performing position estimation according to the walking parameters with the errors eliminated to obtain position estimation data of the current position of the target pedestrian;
establishing a geomagnetic fingerprint database, collecting a plurality of indoor geomagnetic characteristic quantities, and respectively associating and storing the geomagnetic characteristic quantities with corresponding geographic position data;
matching the geomagnetic characteristic quantity with the geomagnetic characteristic quantity in the geomagnetic fingerprint database, and obtaining current geographic position data of the target pedestrian according to the matched geomagnetic characteristic quantity;
and calculating the position estimation data and the current geographical position data according to a particle filter algorithm so as to obtain the current position of the target pedestrian.
Alternatively, as an embodiment of the present invention, as shown in fig. 2,
the obtaining of the position estimation data of the current position of the target pedestrian includes:
obtaining position estimation data of the current position of the target pedestrian according to a pedestrian navigation algorithm, wherein the pedestrian navigation algorithm comprises the following steps:
converting the state parameters under a carrier coordinate system into three-axis data of a geographic coordinate system according to a direction calculation algorithm, constructing a quaternion rigid body equation according to the three-axis data, and calculating the quaternion rigid body equation to obtain walking parameters;
eliminating parameter errors generated by the jitter of the monitoring equipment in the walking parameters according to an extended Kalman algorithm;
establishing four judgment conditions under the zero-speed state of the pedestrian according to a zero-speed correction algorithm, determining a zero-speed state parameter corresponding to the zero-speed state of the pedestrian in the walking parameters with parameter errors eliminated according to the four judgment conditions, and eliminating accumulated errors of the walking parameters according to the zero-speed state parameter;
and carrying out position estimation on the walking parameters without the accumulated errors according to a position estimation algorithm to obtain position estimation data of the current position of the target pedestrian.
The embodiment has the advantages that the speed, the attitude and the position parameters of the target pedestrian can be accurately obtained by using the direction calculation algorithm, the extended Kalman algorithm and the zero-speed correction algorithm.
Specifically, the direction calculation algorithm is as follows:
first using hx、hy、hzRespectively representing three-axis data for converting geomagnetic data in a carrier coordinate system to a geographic coordinate system through a direction cosine matrix, as shown in formulas (1) and (2), wherein:
bxrepresenting a component in the X-axis direction, byRepresenting a component in the Y-axis direction, bzDenotes the component in the Z-axis direction, m denotes the data measured by the magnetometer in the carrier coordinate system, and Q ═ Q0,q1,q2,q3]TIs a quaternion, q0Is the real part of a quaternion, q1、q2、q3Is the imaginary part of the quaternion;
the quaternion rigid equations are shown in formulas (3) and (4):
roll angle (roll), pitch angle (pitch), and heading angle (yaw) are expressed by the following equation (5):
in the formula,for quaternion multiplier operation, Q ═ Q0,q1,q2,q3]TIs a quaternion, q0Is the real part of a quaternion, q1、q2、q3Is the imaginary part of the quaternion, ω ═ ωx,ωy,ωz]Representing values of a three-axis gyroscope;
in the above example, the method further comprises modifying the quaternion:
converting the gravity vector and the geomagnetic vector under the geographic coordinate system into a carrier coordinate system, as shown in formulas (6) and (7):
wherein, bxRepresenting a component in the X-axis direction, byRepresenting a component in the Y-axis direction, bzAnd representing the component in the Z-axis direction, and comparing the vector obtained by calculation of the formula with actually measured data to obtain an error vector so as to further correct the quaternion.
Specifically, the extended kalman algorithm is as follows:
because the inertial sensor has zero drift and temperature drift, and is influenced by the shaking of the carrier, and the magnetometer is interfered by external hard and soft magnets, the obtained data is not accurate enough, so the data needs to be processed; the extended Kalman filtering can be applied to a nonlinear system and is widely applied to an inertial navigation system; the invention adopts the extended Kalman filter to realize the processing and fusion of data.
The state equation and the measurement equation of the extended kalman filter are expressed by equations (8,9), respectively:
Qk+1＝AQk+wk(8)
wherein a is exp (0.5 Ω (ω T)s) Is a state transition matrix, wkRepresenting noise;representing an attitude rotation matrix, g representing a normalized gravity vector, and h representing a normalized magnetic field strength vector;andrepresenting the measurement noise of the accelerometer and magnetometer, respectively.
Specifically, the monitoring device comprises an accelerometer, a gyroscope and a magnetometer, the state parameters are obtained through the accelerometer, the gyroscope and the magnetometer, and the geomagnetic characteristic quantity is obtained through the magnetometer;
the key of the zero speed correction is to accurately detect the moment when the pedestrian is at the zero speed. According to the periodicity of data output by an accelerometer and a gyroscope when a pedestrian walks, the following four conditions for detecting zero speed are constructed:
1) judging whether the modulus of the total acceleration output by the accelerometer in the state parameters is smaller than a preset acceleration parameter:
therein, thamin、thamaxRespectively, a lower limit and an upper limit of the set threshold.
2) Judging whether the variance of the acceleration output value output by the accelerometer in the state parameters is smaller than a preset acceleration variance parameter by setting a sliding window:
whereinAverage of accelerometer measurements in a sliding window:
wherein s is1Is the length of the sliding window of the acceleration output value.
3) Judging whether the modulus of the triaxial output value output by the gyroscope in the state parameters is smaller than a preset gyroscope output parameter:
therein, thωmaxIs a set threshold.
4) Judging whether the sum of the output rate of the accelerometer and the output rate of the gyroscope is smaller than a preset output rate parameter or not by setting a sliding window:
wherein,Nωis the variance of the gyroscope noise, NaIs the variance of the accelerometer noise, thgmTo set the decision threshold, s2The sliding window length for acceleration and gyroscope output values.
When the four conditions are simultaneously met, the pedestrian is considered to be in a zero-speed state, otherwise, the pedestrian is considered to be in a non-zero-speed state;
the pedestrian zero-speed detection effect graph is shown in fig. 3, and the reasonable zero-speed correction algorithm can effectively reduce the accumulated error of the inertia measurement unit and improve the navigation positioning precision. The zero-speed correction of the system is realized by adopting a direct zero setting method. That is, when the system detects that the pedestrian is in a zero speed state, the speed of the pedestrian is set to zero.
Corresponding experimental tests are carried out according to the proposed distinguishing conditions, and test results show that the zero-speed state of the pedestrian can be accurately detected under the conditions of different walking speeds and walking postures of different pedestrians.
Table 1 shows the results of the detection of the number of steps taken by the target pedestrian:
table 1 units: (N)
The zero-speed detection method provided by the invention has higher accuracy and higher application value.
Based on the above embodiments, the position estimation algorithm is described in detail below:
the speed of the pedestrian may be expressed in a geographic coordinate system as:
in the formula, vnWhich is indicative of the speed of the pedestrian,the acceleration of the coriolis acceleration is expressed,denotes centripetal acceleration, gnRepresenting a local gravitational acceleration value;
when the displacement of the pedestrian is calculated, error compensation needs to be carried out on the acceleration, so that the system error is reduced;
when calculating the speed of the pedestrian, the coriolis acceleration and the centripetal acceleration are negligible, so the obtainable speed update expression is:
in the formula, Δ t is a sampling period.
The position of the pedestrian is obtained by integrating the speed, and the formula can be expressed as:
further available location update formulas are:
the position estimation data of the current position of the target pedestrian can be obtained from the above equation.
Optionally, as an embodiment of the present invention, the obtaining current position information of the target pedestrian includes:
the particle filtering algorithm comprises:
establishing a state equation by using the position coordinates of the pedestrians and the target pedestrian course in the position estimation data
s＝(x，y，θ) (19)
Wherein x and y represent the position coordinates of the pedestrian, and theta represents the heading of the target pedestrian;
in the particle filtering process, each particle represents an assumption of a current state, and each particle has a weight w, and the larger the weight of the particle is, the closer the particle is to an actual state is.
Performing particle filtering according to the state equation to obtain corresponding particles of the target pedestrian in each walking state;
setting w as the weight of the particles, establishing the following measurement equation according to the characteristic that each particle obeys Gaussian distribution in the walking state to calculate the current position of the target pedestrian,
wherein σ is standard deviation, μnRepresenting the geomagnetic intensity value measured at the nth step,and representing the geomagnetic intensity value corresponding to the current position of the target pedestrian, which is obtained by matching the geomagnetic matching fingerprint database in the Nth step, of the ith particle.
The particle filtering algorithm further comprises the step of resampling: the resampling mainly aims to solve the particle shortage phenomenon in the classic Monte Carlo method, and the main idea is to resample the particles and the probability density function represented by the corresponding weight value, and realize the resampling by increasing the particles with larger weight value and reducing the particles with smaller weight value, and when the number of effective particles is smaller than a set threshold value, the resampling is carried out.
Optionally, as an embodiment of the present invention, the acquiring a plurality of indoor geomagnetic characteristic quantities includes:
the indoor space is divided into a plurality of positioning areas, and geomagnetic characteristic quantities corresponding to the positioning areas are collected through geomagnetic detection equipment.
Specifically, fig. 4 is a graph of an indoor geomagnetic fingerprint database after kriging interpolation, and as shown in fig. 4, in order to better construct the geomagnetic fingerprint database, the present invention employs a kriging interpolation method for construction. The kriging interpolation method is an optimal, linear and unbiased estimation method, is one of the most widely applied spatial interpolation methods, can utilize given information to the greatest extent, and has high interpolation precision.
Fig. 5 is a block diagram of a positioning device for indoor walking of pedestrians according to an embodiment of the present invention;
optionally, as an embodiment of the present invention, as shown in fig. 5, a pedestrian indoor walking positioning device includes:
the system comprises a measuring module, a processing module and a processing module, wherein the measuring module is used for acquiring original walking data of a target pedestrian through monitoring equipment arranged on the foot of the target pedestrian, and the original walking data comprises state parameters and geomagnetic characteristic quantities;
the main control module is used for resolving the state parameters and the geomagnetic characteristic quantity to obtain walking parameters, eliminating errors of the walking parameters, and performing position estimation according to the walking parameters with the errors eliminated to obtain position estimation data of the current position of the target pedestrian;
the geomagnetic fingerprint database creating module is used for acquiring a plurality of indoor geomagnetic characteristic quantities, and respectively associating and storing the geomagnetic characteristic quantities with corresponding geographic position data;
the geomagnetic matching module is used for matching the geomagnetic characteristic quantity with the geomagnetic characteristic quantity in the geomagnetic fingerprint database and obtaining current geographic position data of the target pedestrian according to the matched geomagnetic characteristic quantity;
and the main control module is also used for calculating the position estimation data and the current geographic position data according to a particle filter algorithm so as to obtain the current position of the target pedestrian.
Optionally, as an embodiment of the present invention, the main control module is specifically configured to:
obtaining position estimation data of the current position of the target pedestrian according to a pedestrian navigation algorithm, wherein the pedestrian navigation algorithm comprises the following steps:
converting the state parameters under the carrier coordinate system into three-axis data of a geographic coordinate system according to the direction calculation algorithm, constructing a quaternion rigid body equation according to the three-axis data, and calculating the quaternion rigid body equation to obtain walking parameters;
eliminating parameter errors generated by the jitter of the monitoring equipment in the walking parameters according to the extended Kalman algorithm;
establishing four judgment conditions under the zero-speed state of the pedestrian according to a zero-speed correction algorithm, determining a zero-speed state parameter corresponding to the zero-speed state of the pedestrian in the walking parameters with parameter errors eliminated according to the four judgment conditions, and eliminating accumulated errors of the walking parameters according to the zero-speed state parameter;
and carrying out position estimation on the walking parameters without the accumulated errors according to a position estimation algorithm to obtain position estimation data of the current position of the target pedestrian.
Optionally, as an embodiment of the present invention, the monitoring device includes an accelerometer, a gyroscope, and a magnetometer, the state parameters are obtained through the accelerometer, the gyroscope, and the magnetometer, and the geomagnetic characteristic quantity is obtained through the magnetometer;
the four judgment conditions in the main control module are as follows:
1) judging whether the modulus of the total acceleration output by the accelerometer in the state parameters is smaller than a preset acceleration parameter or not;
2) judging whether the variance of the acceleration output value output by the accelerometer in the state parameters is smaller than a preset acceleration variance parameter or not;
3) judging whether the modulus of the triaxial output value output by the gyroscope in the state parameters is smaller than a preset gyroscope output parameter or not;
4) and judging whether the sum of the output rate of the accelerometer and the output rate of the gyroscope is less than a preset output rate parameter.
Optionally, as another embodiment of the present invention, a pedestrian indoor walking positioning apparatus includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the method when executing the computer program.
Alternatively, as another embodiment of the present invention, a computer-readable storage medium stores a computer program which, when executed by a processor, implements the steps of the method as described.
Experimental results and analysis:
in order to verify the positioning effect of the algorithm provided by the invention, the place is selected to be tested in a gymnasium of a certain university.
The ADIS16405 inertial sensor is integrated in the monitoring equipment adopted by the invention, the sampling rate is 50HZ, a tester fixes the monitoring equipment on the foot, walks for a circle according to a specified route from a calibrated starting point, and then introduces the measured data into the MATLAB processor for processing, and the experimental result is shown in figure 6:
by analyzing the positioning method based on PDR (i.e. positioning method a) and the positioning method proposed by the present invention (i.e. positioning method B), the obtained positioning errors are shown in table 2:
table 2 pedestrian walking error analysis unit: (m)
Compared with the PDR positioning method, the average error of the positioning method provided by the invention is reduced by 77.5%, and the positioning precision is effectively improved.
According to the invention, the original data of the target pedestrian during walking is measured by the monitoring equipment of the foot of the target pedestrian, the walking parameters are obtained by resolving the original data through a direction resolving algorithm, an extended Kalman algorithm and a zero-speed correction algorithm, the walking parameters are estimated by utilizing a position estimation algorithm to obtain position estimation data, meanwhile, the geomagnetic intensity value corresponding to the position of the target pedestrian is matched according to a created geomagnetic fingerprint database, and the position estimation data and the geomagnetic intensity value are combined according to a particle filter algorithm, so that the current position of the target pedestrian is obtained, and the positioning precision is improved.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of a unit is merely a logical division, and an actual implementation may have another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed.
Units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment of the present invention.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention essentially or partially contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
While the invention has been described with reference to specific embodiments, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A pedestrian indoor walking positioning method is characterized by comprising the following steps:
acquiring original data of walking of a target pedestrian through monitoring equipment arranged on the foot of the target pedestrian, wherein the original data comprises state parameters of the current position of the target pedestrian and geomagnetic characteristic quantity;
resolving the state parameters to obtain walking parameters, eliminating errors of the walking parameters, and performing position estimation according to the walking parameters with the errors eliminated to obtain position estimation data of the current position of the target pedestrian;
establishing a geomagnetic fingerprint database, collecting a plurality of indoor geomagnetic characteristic quantities, and respectively associating and storing the geomagnetic characteristic quantities with corresponding geographic position data;
matching the geomagnetic characteristic quantity of the current position of the target pedestrian with the geomagnetic characteristic quantity in the geomagnetic fingerprint database, and obtaining current geographic position data of the target pedestrian according to the matched geomagnetic characteristic quantity;
and calculating the position estimation data and the current geographical position data according to a particle filter algorithm so as to obtain the current position of the target pedestrian.
2. The indoor pedestrian walking positioning method according to claim 1, wherein the obtaining of the position estimation data of the current position of the target pedestrian comprises:
obtaining position estimation data of the current position of the target pedestrian according to a pedestrian navigation algorithm, wherein the pedestrian navigation algorithm comprises the following steps:
converting the state parameters under a carrier coordinate system into three-axis data of a geographic coordinate system according to a direction calculation algorithm, constructing a quaternion rigid body equation according to the three-axis data, and calculating the quaternion rigid body equation to obtain walking parameters;
eliminating parameter errors generated by the jitter of the monitoring equipment in the walking parameters according to an extended Kalman algorithm;
establishing four judgment conditions under the zero-speed state of the pedestrian according to a zero-speed correction algorithm, determining a zero-speed state parameter corresponding to the zero-speed state of the pedestrian in the walking parameters with parameter errors eliminated according to the four judgment conditions, and eliminating accumulated errors of the walking parameters according to the zero-speed state parameter;
and carrying out position estimation on the walking parameters without the accumulated errors according to a position estimation algorithm to obtain position estimation data of the current position of the target pedestrian.
3. The indoor pedestrian walking positioning method according to claim 2, wherein the monitoring device comprises an accelerometer, a gyroscope and a magnetometer, and the state parameters are obtained through the accelerometer, the gyroscope and the magnetometer;
the four judgment conditions are as follows:
1) judging whether the modulus of the total acceleration output by the accelerometer in the state parameters is smaller than a preset acceleration parameter or not;
2) judging whether the variance of the acceleration output value output by the accelerometer in the state parameters is smaller than a preset acceleration variance parameter or not;
3) judging whether the modulus of the triaxial output value output by the gyroscope in the state parameters is smaller than a preset gyroscope output parameter or not;
4) and judging whether the sum of the output rate of the accelerometer and the output rate of the gyroscope is less than a preset output rate parameter.
4. The indoor walking positioning method for pedestrians according to claim 1, wherein the collecting indoor multiple geomagnetic characteristic quantities comprises:
the indoor space is divided into a plurality of positioning areas, and geomagnetic characteristic quantities corresponding to the positioning areas are collected through geomagnetic detection equipment.
5. The indoor pedestrian walking positioning method according to any one of claims 1 to 4, wherein the obtaining of the current position information of the target pedestrian comprises:
the particle filtering algorithm comprises:
establishing a state equation s (x, y, theta) between the pedestrian position coordinates in the position estimation data and the target pedestrian course, wherein x and y represent the pedestrian position coordinates, and theta represents the target pedestrian course;
performing particle filtering according to the state equation to obtain corresponding particles of the target pedestrian in each walking state;
setting w as the weight of the particles, establishing the following measurement equation according to the characteristic that each particle obeys Gaussian distribution in the walking state to calculate the current position of the target pedestrian,
wherein σ is standard deviation, μnRepresenting the geomagnetism characteristic quantity measured at the nth step,and representing the geomagnetic characteristic quantity corresponding to the current geographic position data of the target pedestrian, which is obtained by matching the ith particle in the Nth step through the geomagnetic matching fingerprint database.
6. The utility model provides an indoor walking positioner of pedestrian, its characterized in that includes:
the system comprises a measuring module, a processing module and a processing module, wherein the measuring module is used for acquiring original walking data of a target pedestrian through monitoring equipment arranged on the foot of the target pedestrian, and the original walking data comprises state parameters and geomagnetic characteristic quantities;
the main control module is used for resolving the state parameters to obtain walking parameters, eliminating errors of the walking parameters, and performing position estimation according to the walking parameters with the errors eliminated to obtain position estimation data of the current position of the target pedestrian;
the geomagnetic fingerprint database creating module is used for acquiring a plurality of indoor geomagnetic characteristic quantities, and respectively associating and storing the geomagnetic characteristic quantities with corresponding geographic position data;
the geomagnetic matching module is used for matching the geomagnetic characteristic quantity of the current position of the target pedestrian with the geomagnetic characteristic quantity in the geomagnetic fingerprint database and obtaining current geographic position data of the target pedestrian according to the matched geomagnetic characteristic quantity;
and the main control module is also used for calculating the position estimation data and the current geographic position data according to a particle filter algorithm so as to obtain the current position of the target pedestrian.
7. The indoor pedestrian walking positioning device of claim 6, wherein the main control module is specifically configured to:
obtaining position estimation data of the current position of the target pedestrian according to a pedestrian navigation algorithm, wherein the pedestrian navigation algorithm comprises the following steps:
converting the state parameters under a carrier coordinate system into three-axis data of a geographic coordinate system according to a direction calculation algorithm, constructing a quaternion rigid body equation according to the three-axis data, and calculating the quaternion rigid body equation to obtain walking parameters;
eliminating parameter errors generated by the jitter of the monitoring equipment in the walking parameters according to an extended Kalman algorithm;
establishing four judgment conditions under the zero-speed state of the pedestrian according to a zero-speed correction algorithm, determining a zero-speed state parameter corresponding to the zero-speed state of the pedestrian in the walking parameters with parameter errors eliminated according to the four judgment conditions, and eliminating accumulated errors of the walking parameters according to the zero-speed state parameter;
and carrying out position estimation on the walking parameters without the accumulated errors according to a position estimation algorithm to obtain position estimation data of the current position of the target pedestrian.
8. The pedestrian indoor walking positioning device of claim 7, wherein the monitoring equipment comprises an accelerometer, a gyroscope and a magnetometer, and the state parameters are obtained through the accelerometer, the gyroscope and the magnetometer;
the four judgment conditions in the main control module are as follows:
1) judging whether the modulus of the total acceleration output by the accelerometer in the state parameters is smaller than a preset acceleration parameter or not;
2) judging whether the variance of the acceleration output value output by the accelerometer in the state parameters is smaller than a preset acceleration variance parameter or not;
3) judging whether the modulus of the triaxial output value output by the gyroscope in the state parameters is smaller than a preset gyroscope output parameter or not;
4) and judging whether the sum of the output rate of the accelerometer and the output rate of the gyroscope is less than a preset output rate parameter.
9. A pedestrian indoor walking positioning device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any one of claims 1 to 5 when executing the computer program.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810965290.1A CN109084765B (en) | 2018-08-23 | 2018-08-23 | Indoor walking positioning method and device for pedestrian and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810965290.1A CN109084765B (en) | 2018-08-23 | 2018-08-23 | Indoor walking positioning method and device for pedestrian and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109084765A true CN109084765A (en) | 2018-12-25 |
| CN109084765B CN109084765B (en) | 2021-09-07 |
Family
ID=64794215
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810965290.1A Expired - Fee Related CN109084765B (en) | 2018-08-23 | 2018-08-23 | Indoor walking positioning method and device for pedestrian and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109084765B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110260855A (en) * | 2019-06-24 | 2019-09-20 | 北京壹氢科技有限公司 | A kind of indoor pedestrian navigation localization method merging pedestrian's dead reckoning, Geomagnetism Information and indoor map information |
| GB2616940A (en) * | 2022-03-22 | 2023-09-27 | Univ China Mining | Passive combined indoor positioning system and method based on intelligent terminal sensor |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110313716A1 (en) * | 2010-02-19 | 2011-12-22 | Itrack, Llc | Intertial tracking system with provision for position correction |
| CN103175529A (en) * | 2013-03-01 | 2013-06-26 | 上海美迪索科电子科技有限公司 | Pedestrian inertial positioning system based on indoor magnetic field feature assistance |
| CN104197938A (en) * | 2014-09-03 | 2014-12-10 | 厦门大学 | Indoor localization method based on foot inertia sensor |
| CN106225786A (en) * | 2016-08-15 | 2016-12-14 | 北京理工大学 | A kind of adaptive pedestrian navigation system zero-speed section detecting method |
| CN107218938A (en) * | 2017-05-22 | 2017-09-29 | 南京航空航天大学 | The Wearable pedestrian navigation localization method and equipment aided in based on modelling of human body motion |
-
2018
- 2018-08-23 CN CN201810965290.1A patent/CN109084765B/en not_active Expired - Fee Related
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110313716A1 (en) * | 2010-02-19 | 2011-12-22 | Itrack, Llc | Intertial tracking system with provision for position correction |
| CN103175529A (en) * | 2013-03-01 | 2013-06-26 | 上海美迪索科电子科技有限公司 | Pedestrian inertial positioning system based on indoor magnetic field feature assistance |
| CN104197938A (en) * | 2014-09-03 | 2014-12-10 | 厦门大学 | Indoor localization method based on foot inertia sensor |
| CN106225786A (en) * | 2016-08-15 | 2016-12-14 | 北京理工大学 | A kind of adaptive pedestrian navigation system zero-speed section detecting method |
| CN107218938A (en) * | 2017-05-22 | 2017-09-29 | 南京航空航天大学 | The Wearable pedestrian navigation localization method and equipment aided in based on modelling of human body motion |
Non-Patent Citations (2)
| Title |
|---|
| 李思民等: "基于地磁指纹和PDR融合的手机室内定位系统", 《传感技术学报》 * |
| 王亚娜等: "基于粒子滤波的多信息融合室内定位算法研究", 《电子技术应用》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110260855A (en) * | 2019-06-24 | 2019-09-20 | 北京壹氢科技有限公司 | A kind of indoor pedestrian navigation localization method merging pedestrian's dead reckoning, Geomagnetism Information and indoor map information |
| GB2616940A (en) * | 2022-03-22 | 2023-09-27 | Univ China Mining | Passive combined indoor positioning system and method based on intelligent terminal sensor |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109084765B (en) | 2021-09-07 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104061934B (en) | Pedestrian indoor position tracking method based on inertial sensor | |
| Bai et al. | A high-precision and low-cost IMU-based indoor pedestrian positioning technique | |
| Zhou et al. | Use it free: Instantly knowing your phone attitude | |
| CN109579853B (en) | Inertial navigation indoor positioning method based on BP neural network | |
| CN104296750B (en) | Zero speed detecting method, zero speed detecting device, and pedestrian navigation method as well as pedestrian navigation system | |
| EP2850392B1 (en) | Method for step detection and gait direction estimation | |
| Sabatini | Quaternion-based extended Kalman filter for determining orientation by inertial and magnetic sensing | |
| CN104969030B (en) | Inertial device, methods and procedures | |
| CN107076554B (en) | Method and system for the determining and automatic jump detection of normal trajectories | |
| CN107255474B (en) | PDR course angle determination method integrating electronic compass and gyroscope | |
| CN106705959A (en) | Method and device for detecting course of mobile terminal | |
| CN108458714B (en) | Euler angle solving method without gravity acceleration in attitude detection system | |
| CN108426573A (en) | A kind of the pedestrian's gait detection method and terminal device of terminal device | |
| CN104964685A (en) | Judgment method for moving state of mobile phone | |
| CN111024126B (en) | Self-adaptive zero-speed correction method in pedestrian navigation positioning | |
| CN106370178B (en) | Attitude measurement method and device of mobile terminal equipment | |
| Shockley | Ground vehicle navigation using magnetic field variation | |
| CN110672095A (en) | Pedestrian indoor autonomous positioning algorithm based on micro inertial navigation | |
| CN104266648A (en) | Indoor location system based on Android platform MARG sensor | |
| CN103644910A (en) | Personal autonomous navigation system positioning method based on segment RTS smoothing algorithm | |
| CN109084765B (en) | Indoor walking positioning method and device for pedestrian and storage medium | |
| CN106153069A (en) | Attitude rectification apparatus and method in autonomous navigation system | |
| EP3227634B1 (en) | Method and system for estimating relative angle between headings | |
| CN111435083A (en) | Pedestrian track calculation method, navigation method and device, handheld terminal and medium | |
| CN111197974B (en) | Barometer height measuring and calculating method based on Android inertial platform |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20210907 |