CN108180923A - A kind of inertial navigation localization method based on human body odometer - Google Patents
A kind of inertial navigation localization method based on human body odometer Download PDFInfo
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- CN108180923A CN108180923A CN201711291646.XA CN201711291646A CN108180923A CN 108180923 A CN108180923 A CN 108180923A CN 201711291646 A CN201711291646 A CN 201711291646A CN 108180923 A CN108180923 A CN 108180923A
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- inertial navigation
- human body
- navigation system
- odometer
- body odometer
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C22/00—Measuring distance traversed on the ground by vehicles, persons, animals or other moving solid bodies, e.g. using odometers, using pedometers
- G01C22/006—Pedometers
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- 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
Abstract
The present invention provides a kind of inertial navigation localization methods based on human body odometer, can realize the precision navigation under pedestrian's full motion state.The present invention selects human body odometer to carry out aided inertial navigation system, wherein, human body odometer is with reference to land by the use of vehicle-mounted odometer using the stroke representated by each pulse as the method for calibration factor, using single step step-length as calibration factor, calibration factor includes modifying factor, obtained calibration factor is more accurate, so as to obtain the travel track of accurate human body.Modifying factor is increased to the state vector of inertial navigation system simultaneously, the arbitrariness and uncertainty of human motion can be directed to, the characteristics of making full use of inertial navigation system positioning accuracy is high in short-term, aided inertial navigation system completes the precision navigation under indoor pedestrian's full motion state.
Description
Technical field
The invention belongs to pedestrian navigation technical fields, and in particular to a kind of inertial navigation positioning side based on human body odometer
Method.
Background technology
The it is proposed and development of " smart city " propose higher requirement to the location navigation of indoor occupant, are passed based on inertia
Pedestrian's dead reckoning system (PDR) of sensor has sufficient independence and flexibility, is increasingly paid attention to by people.Needle at present
It is based primarily upon zero-velocity curve (ZUPT) principle to PDR systematic researches, is corrected by searching for the point of zero velocity in people's walking process
Inertial navigation system is also studied and carries out building feature information, people's walking experience step information etc. and inertial navigation system
The mode of fusion, aided inertial navigation system complete the navigation under indoor pedestrian's full motion state.
But ZUPT methods, which need to have point of zero velocity, accurately judges identification, thus be only applicable to level land walk, stair activity etc.
Simple gait；And building feature is complicated, is different, people's traveling step-length is influenced again by surrounding enviroment, mood etc., so using
The inertial navigation positioning accuracy that these information are merged with inertial navigation system is all not ideal enough, and positioning accuracy is not high.
Invention content
In view of this, the present invention provides a kind of inertial navigation localization method based on human body odometer, row can be realized
Precision navigation under people's full motion state.
The present invention is achieved through the following technical solutions：
Include the following steps：
Step 1, the cadence of human motion and acceleration and angular speed information are acquired, and to collected human motion
Acceleration and angular speed information carries out inertial navigation resolving, obtains inertial navigation and resolves displacement increment；
Step 2, calibration factor with the cadence of the collected human motion of step 1 is multiplied, obtains the output of human body odometer
Displacement increment；
Wherein described calibration factor S is：
S=(1+ δ K) [h (afstep+b)+c]
Wherein, [h (afstep+ b)+c] for reference step, fstepFor cadence, h is the height of people, and a, b and c are and step
The relevant reference step coefficient of state is known quantity；δ K are modifying factor, for correcting reference step error；
Step 3, modifying factor is increased in the state vector of inertial navigation system, is established using inertial navigation principle used
The state equation of property navigation system；
By the human body odometer output displacement increment that the inertial navigation that step 1 obtains resolves displacement increment and step 2 obtains
Difference as observed quantity, establish the observational equation of inertial navigation system；
Step 4, the state equation and observational equation established based on step 3 are obtained inertia using kalman filter method and led
The state vector estimated value of boat system；
Step 5, gained state vector estimated value is filtered to human body odometer calibration factor and inertial navigation using step 4
The zero bias of system are modified, and complete the positioning under pedestrian's full motion state.
Wherein, the observational equation of inertial navigation system is established with displacement integration matching process.
Wherein, gyroscope and the accelerometer acquisition cadence of human motion and acceleration and angular speed information are utilized；It is used
The state vector of property navigation system is：
Wherein, ψNFor attitude error；δVNFor velocity error；ζNFor longitude and latitude error；δ h are vertical error；ε is three axis
To gyroscope constant value zero bias；Accelerometer constant value zero bias for three axial directions.
Wherein, the observational equation of the inertial navigation system is：δ Z (k)=δ Δs RINS(tk)-δΔSN(tk), wherein δ Z
(k) it is observed quantity differential, δ Δs RINS(tk) it is that inertial navigation system resolves displacement increment differential, δ Δs SN(tk) it is human body odometer
Output displacement incremental differential.
Wherein, human body acceleration and angular speed information under different motion gait is acquired using micro-inertia sensor.
Wherein, the micro-inertia sensor is configured at human foot, waist or shin bone.
Advantageous effect：
The present invention selects human body odometer to carry out aided inertial navigation system, wherein, human body odometer is with reference to land in vehicle-mounted
Journey meter is using the stroke representated by each pulse as the method for calibration factor, using single step step-length as calibration factor, calibration factor
Comprising modifying factor, obtained calibration factor is more accurate, so as to obtain the travel track of accurate human body.Simultaneously by modifying factor
Son increases to the state vector of inertial navigation system, can be directed to the arbitrariness and uncertainty of human motion, make full use of used
Property navigation system the characteristics of positioning accuracy is high in short-term, aided inertial navigation system is completed accurate under indoor pedestrian's full motion state
Navigation.
Description of the drawings
Fig. 1 is the inertial navigation localization method flow chart based on human body odometer.
Specific embodiment
The present invention will now be described in detail with reference to the accompanying drawings and examples.
In order to realize the arbitrariness and not to the precision navigation under indoor pedestrian's full motion state, needed for human motion
Certainty finds new external auxiliary source information, and the characteristics of making full use of inertial navigation system positioning accuracy is high in short-term, auxiliary is used
Property navigation system complete precision navigation under indoor pedestrian's full motion state.
The present invention selects human body odometer to carry out aided inertial navigation system, wherein, human body odometer is with reference to land in vehicle-mounted
Journey meter is using the stroke representated by each pulse as the method for calibration factor, using single step step-length as calibration factor, calibration factor
Comprising modifying factor, obtained calibration factor is more accurate, so as to obtain the travel track of accurate human body.Simultaneously by modifying factor
Son increases to the state vector of inertial navigation system, can be directed to the arbitrariness and uncertainty of human motion, make full use of used
Property navigation system the characteristics of positioning accuracy is high in short-term, using kalman filter method, by two or more subsystems using effective
Information fusion method merged, and then realize pedestrian's full motion state under precision navigation.
The present invention provides a kind of inertial navigation localization methods based on human body odometer, and it is for the national games can to complete indoor pedestrian
High accuracy positioning under dynamic state.
The inertial navigation localization method flow chart of human body odometer is as shown in Figure 1, described method includes following steps：
Step 1, the cadence of human motion and acceleration and angular speed information are acquired, and to collected human motion
Acceleration and angular speed information carries out inertial navigation resolving, obtains inertial navigation and resolves displacement increment；
Wherein, human body acceleration and angular speed information under different motion gait is acquired using micro-inertia sensor, at present
Micro-inertia sensor often uses gyroscope and accelerometer.Micro-inertia sensor is configured at human foot, waist or shin bone.
Wherein, in k-th of sampling period Δ T=tk-tk-1Interior, inertial navigation system resolves displacement increment and is：
Wherein, VNFor the speed that inertial navigation system resolves, k=1,2,3 ... .M, M are total for the sampling period, t0For
Sample initial time, t1At the time of for first sampling period end, t2At the time of for second sampling period end, and so on, tk
At the time of for k-th of sampling period end.
Step 2, calibration factor is multiplied to obtain the increasing of human body odometer output displacement with the cadence of collected human motion
Amount；
Wherein described calibration factor S is：
S=(1+ δ K) [h (afstep+b)+c]
Wherein, fstepFor cadence；H is the height of people；δ K are modifying factor；A, b and c is the reference step under different gaits
Coefficient, [h (afstep+ b)+c] it is reference step.Wherein, reference step is obtained by gait division result early period, different
The reference step of gait is different；Modifying factor is represented by the arbitrariness of human motion and random for correcting reference step error
Property caused by step change, pass through on-line identification and ART network and obtain.
Calibration factor is the single step step-length of human body odometer, using the cadence of collected human motion as human body mileage
Meter output umber of pulse, output umber of pulse are multiplied the human body odometer output displacement increment that can be calculated with calibration factor.
Human body odometer output displacement increment is：
Wherein,For the human body odometer coordinate system that inertial navigation system resolves to the transformation of navigational coordinate system
Matrix；ΔSVMSThe single step step-length S as obtained by human body odometer.
In addition, human motion is not necessarily in a certain specific dimension, if human motion is divided into front-rear direction and right and left
To two dimensions, it is considered as in each dimension there are one individual human body odometer, human body mileage is calculated as two-dimension human body mileage at this time
Meter, as shown in Figure 1；
Step 3, the state equation and observational equation of inertial navigation system are established：
The modifying factor that step 2 obtains is increased in the state vector of inertial navigation, established using inertial navigation principle
The state equation of inertial navigation system；
Wherein, inertial navigation system model is existing well known model, and for the modifying factor of human body odometer, have：
In the present embodiment, on the basis of inertial navigation system and human body odometer model is established, modifying factor is increased
It is added in state vector, obtaining state vector is：
Wherein, ψNFor attitude error；δVNFor velocity error；ζNFor longitude and latitude error；δ h are vertical error；ε is three axis
To gyroscope constant value zero bias；Accelerometer constant value zero bias for three axial directions.
The state equation for obtaining inertial navigation system is：
Wherein, F (tk) represent system transfer matrix, it is obtained by the dynamic error model of inertial navigation system and human body odometer
It arrives；W(tk) it is system noise.
By the human body odometer output displacement increment that the inertial navigation that step 1 obtains resolves displacement increment and step 2 obtains
Difference as observed quantity, the observational equation of inertial navigation system is established with displacement integration matching process；
Wherein observed quantity is Z (k)：
Z (k)=Δ RINS(tk)-ΔSN(tk)
Differential is carried out to Z (k) both members, the observational equation for obtaining inertial navigation system is：
δ Z (k)=δ Δs RINS(tk)-δΔSN(tk)
The present embodiment selects displacement integration matching process to establish observational equation, is established using displacement integration matching process used
The observational equation of property navigation system, relative to traditional using speed as the odometer auxiliary navigation method of observed quantity, avoid because
The quantization error for calculating human body odometer speed and introducing, effectively reduces measurement noise level, improves navigation system performance.
Observational equation, which is further arranged, to be obtained：
It can thus be concluded that observing matrix H (k) is：
Step 4, the state equation and observational equation for the inertial navigation system established based on step 3, utilize Kalman filtering
Fundamental equation the information of human body odometer and inertial navigation system is merged, realize human body odometer and inertial navigation system
Mutual correction and optimum fusion between system, obtain state vector estimated value；
Step 5, using filtering gained state vector estimated value to human body odometer calibration factor and inertial navigation system
Zero bias be modified, complete pedestrian's full motion state under positioning.
When step 1 utilizes gyroscope and the accelerometer acquisition cadence of human motion and acceleration and angular speed information
When, the zero bias of inertial navigation system refer to the zero bias of gyroscope and accelerometer in step 5.
In conclusion the foregoing is merely a prefered embodiment of the invention, it is not intended to limit the scope of the present invention.
All within the spirits and principles of the present invention, any modification, equivalent replacement, improvement and so on should be included in the present invention's
Within protection domain.
Claims (6)
1. a kind of inertial navigation localization method based on human body odometer, which is characterized in that include the following steps：
Step 1, the cadence of human motion and acceleration and angular speed information are acquired, and to the acceleration of collected human motion
Degree and angular velocity information carry out inertial navigation resolving, obtain inertial navigation and resolve displacement increment；
Step 2, calibration factor with the cadence of the collected human motion of step 1 is multiplied, obtains human body odometer output displacement
Increment；
Wherein described calibration factor S is：
S=(1+ δ K) [h (afstep+b)+c]
Wherein, [h (afstep+ b)+c] for reference step, fstepFor cadence, h is the height of people, and a, b and c are and gait phase
The reference step coefficient of pass is known quantity；δ K are modifying factor, for correcting reference step error；
Step 3, modifying factor is increased in the state vector of inertial navigation system, establishes inertia using inertial navigation principle and lead
The state equation of boat system；
By the difference of human body odometer output displacement increment that the inertial navigation that step 1 obtains resolves displacement increment and step 2 obtains
As observed quantity, the observational equation of inertial navigation system is established；
Step 4, the state equation and observational equation established based on step 3 obtain inertial navigation system using kalman filter method
The state vector estimated value of system；
Step 5, gained state vector estimated value is filtered to human body odometer calibration factor and inertial navigation system using step 4
Zero bias be modified, complete pedestrian's full motion state under positioning.
2. a kind of inertial navigation localization method based on human body odometer as described in claim 1, which is characterized in that with position
Allochthonous deposit divides the observational equation that matching process establishes inertial navigation system.
3. a kind of inertial navigation localization method based on human body odometer as described in claim 1, which is characterized in that utilize top
Spiral shell instrument and the accelerometer acquisition cadence of human motion and acceleration and angular speed information；The state vector of inertial navigation system
For：
X=] (ψN)T (δVN)T (ζN)T δh (ε)T (▽)T δK]T
Wherein, ψNFor attitude error；δVNFor velocity error；ζNFor longitude and latitude error；δ h are vertical error；ε is three axial directions
Gyroscope constant value zero bias；▽ is the accelerometer constant value zero bias of three axial directions.
4. a kind of inertial navigation localization method based on human body odometer as described in claim 1, which is characterized in that described used
The observational equation of property navigation system is：δ Z (k)=δ Δs RINS(tk)-δΔSN(tk), wherein δ Z (k) be observed quantity differential, δ Δs
RINS(tk) it is that inertial navigation system resolves displacement increment differential, δ Δs SN(tk) it is human body odometer output displacement incremental differential.
5. a kind of inertial navigation localization method based on human body odometer as described in claim 1, which is characterized in that utilize micro-
Inertial sensor acquires human body acceleration and angular speed information under different motion gait.
6. a kind of inertial navigation localization method based on human body odometer as claimed in claim 5, which is characterized in that described micro-
Inertial sensor is configured at human foot, waist or shin bone.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109297486A (en) * | 2018-09-30 | 2019-02-01 | 北京自行者科技有限公司 | The body movement condition judgement method and system of inertia and more odometer information auxiliary |
| CN109769206A (en) * | 2019-02-25 | 2019-05-17 | 广州市香港科大霍英东研究院 | A kind of indoor positioning fusion method, device, storage medium and terminal device |
| CN111157984A (en) * | 2020-01-08 | 2020-05-15 | 电子科技大学 | Pedestrian autonomous navigation method based on millimeter wave radar and inertial measurement unit |
| CN111307148A (en) * | 2020-04-03 | 2020-06-19 | 北京航空航天大学 | Pedestrian positioning method based on inertial network |
| CN111380516A (en) * | 2020-02-27 | 2020-07-07 | 上海交通大学 | Inertial navigation/odometer vehicle combined navigation method and system based on odometer measurement information |
| CN111811500A (en) * | 2020-05-06 | 2020-10-23 | 北京嘀嘀无限科技发展有限公司 | Target object pose estimation method and device, storage medium and electronic equipment |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103983273A (en) * | 2014-04-29 | 2014-08-13 | 华南理工大学 | Real-time step length estimation method based on acceleration sensor |
| CN104819716A (en) * | 2015-04-21 | 2015-08-05 | 北京工业大学 | Indoor and outdoor personal navigation algorithm based on INS/GPS (inertial navigation system/global position system) integration of MEMS (micro-electromechanical system) |
| CN105628027A (en) * | 2016-02-19 | 2016-06-01 | 中国矿业大学 | Indoor environment precise real-time positioning method based on MEMS inertial device |
| US20160169703A1 (en) * | 2014-12-12 | 2016-06-16 | Invensense Inc. | Method and System for Characterization Of On Foot Motion With Multiple Sensor Assemblies |
-
2017
- 2017-12-08 CN CN201711291646.XA patent/CN108180923B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103983273A (en) * | 2014-04-29 | 2014-08-13 | 华南理工大学 | Real-time step length estimation method based on acceleration sensor |
| US20160169703A1 (en) * | 2014-12-12 | 2016-06-16 | Invensense Inc. | Method and System for Characterization Of On Foot Motion With Multiple Sensor Assemblies |
| CN104819716A (en) * | 2015-04-21 | 2015-08-05 | 北京工业大学 | Indoor and outdoor personal navigation algorithm based on INS/GPS (inertial navigation system/global position system) integration of MEMS (micro-electromechanical system) |
| CN105628027A (en) * | 2016-02-19 | 2016-06-01 | 中国矿业大学 | Indoor environment precise real-time positioning method based on MEMS inertial device |
Non-Patent Citations (2)
| Title |
|---|
| JUAN BRAVO: "Comparison of step length and heading estimation methods for indoor environments", 《IEEE》 * |
| 楼喜中等: "MEMS传感器的计步算法研究", 《中国计量大学学报》 * |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109297486A (en) * | 2018-09-30 | 2019-02-01 | 北京自行者科技有限公司 | The body movement condition judgement method and system of inertia and more odometer information auxiliary |
| CN109297486B (en) * | 2018-09-30 | 2020-11-13 | 重庆自行者科技有限公司 | Inertia and multi-odometer information-assisted vehicle motion state determination method and system |
| CN109769206A (en) * | 2019-02-25 | 2019-05-17 | 广州市香港科大霍英东研究院 | A kind of indoor positioning fusion method, device, storage medium and terminal device |
| CN111157984A (en) * | 2020-01-08 | 2020-05-15 | 电子科技大学 | Pedestrian autonomous navigation method based on millimeter wave radar and inertial measurement unit |
| CN111380516A (en) * | 2020-02-27 | 2020-07-07 | 上海交通大学 | Inertial navigation/odometer vehicle combined navigation method and system based on odometer measurement information |
| CN111380516B (en) * | 2020-02-27 | 2022-04-08 | 上海交通大学 | Inertial navigation/odometer vehicle combined navigation method and system based on odometer measurement information |
| CN111307148A (en) * | 2020-04-03 | 2020-06-19 | 北京航空航天大学 | Pedestrian positioning method based on inertial network |
| CN111811500A (en) * | 2020-05-06 | 2020-10-23 | 北京嘀嘀无限科技发展有限公司 | Target object pose estimation method and device, storage medium and electronic equipment |
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