CN105241454A - System and method for pedestrian navigation based on multiple sensors - Google Patents

System and method for pedestrian navigation based on multiple sensors Download PDF

Info

Publication number
CN105241454A
CN105241454A CN201510695799.5A CN201510695799A CN105241454A CN 105241454 A CN105241454 A CN 105241454A CN 201510695799 A CN201510695799 A CN 201510695799A CN 105241454 A CN105241454 A CN 105241454A
Authority
CN
China
Prior art keywords
pedestrian
data
course
moment
navigation
Prior art date
Application number
CN201510695799.5A
Other languages
Chinese (zh)
Inventor
高玉霞
黄艳辉
Original Assignee
中国兵器工业集团第二一四研究所苏州研发中心
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 中国兵器工业集团第二一四研究所苏州研发中心 filed Critical 中国兵器工业集团第二一四研究所苏州研发中心
Priority to CN201510695799.5A priority Critical patent/CN105241454A/en
Publication of CN105241454A publication Critical patent/CN105241454A/en

Links

Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01CMEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/10Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
    • G01C21/12Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
    • G01C21/16Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
    • G01C21/165Navigation; 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
    • 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
    • G01S19/48Determining position by combining or switching between position solutions derived from the satellite radio beacon positioning system and position solutions derived from a further system
    • G01S19/49Determining position by combining or switching between position solutions derived from the satellite radio beacon positioning system and position solutions derived from a further system whereby the further system is an inertial position system, e.g. loosely-coupled

Abstract

The invention discloses a system and method for pedestrian navigation based on multiple sensors. A sensor module comprises a GPS, an MEMS accelerometer, an MEMS gyroscope, a magnetic compass and a barometer. When the GPS is free of signal blockage, the GPS is adopted to perform navigation positioning. When GPS signal failure occurs, the MEMS accelerometer is utilized to collect and detect pedestrian's walking step number, the pedestrian walking course is calculated through data combination of the MEMS gyroscope and the magnetic compass, and a pedestrian's motion track in the plane is calculated according to the step number and navigation. A motion track of a pedestrian in the height direction is obtained by utilizing data obtained by the MEMS accelerometer and the barometer, and the positioning of a motion track of the pedestrian in a three-dimensional space is achieved. According to the system and method for pedestrian navigation based on the multiple sensors, the shortcoming that single GPS signals are lowered in performance when being indoors or being blocked out, and normal navigation and positioning cannot be performed is overcome, the requirements for small size and low cost of a personal navigating instrument are met, and the system and method for pedestrian navigation are more suitable for navigation of walking pedestrians.

Description

A kind of pedestrian navigation system based on multisensor and air navigation aid

Technical field

The invention belongs to field of navigation technology, particularly based on the pedestrian navigation network system realization of multisensor.

Background technology

Many activities of the mankind as ground observation, other places go on business, Scene Tourist etc. is not complete in fixing place, when we are in, just to seem particularly to the demand of position & navigation information in foreign environment urgent.Pedestrian navigation system can measure the action message of pedestrian by hand-held or Wearable sensor combinations module, resolve, finally determine real time position and the speed of pedestrian via navigational computer.

The pedestrian navigation system major part of current development is equipped with the GPS device for navigating, but the motion feature of pedestrian is complicated, motion path has unpredictability, when being in the lane, street in city, indoor, underground installation and dense woods region, the navigation performance of GPS will reduce significantly, cannot normal position & navigation.Just need to adopt integrated positioning and airmanship to be assisted to realize independent navigation, minimizing external interference etc.

Pedestrian navigation system is based on newton law of inertia, with MEMS inertial sensor for core devices, the multiple-sensor integration system be made up of mems accelerometer, MEMS gyro instrument, three axle magnetic compasses, barometer, temperature sensor etc., for realizing light, reliable position & navigation function.Complete independent positioning and navigation are carried out to personnel motion trail, be applicable to complete position & navigation task when gps signal is blocked by buildings or dense vegetation, until gps signal recovers normal, reach the object that assistant GPS completes location and navigation, be specially adapted to individual-soldier system, also can be applicable in the equipment configurations of People's Armed Police, fire fighters.

Summary of the invention

In order to solve the technical matters existed in prior art, the invention provides a kind of pedestrian navigation system organically blended by the multi-sensor informations such as GPS, MEMS gyro instrument, mems accelerometer, magnetic compass, barometer and thermometer of design, there is light, reliable position & navigation function.Also the task of personnel motion trail being carried out to complete independent positioning and navigation can be completed when gps signal is blocked by buildings or dense vegetation.While ensureing degree of accuracy, greatly reduce the complexity that algorithm calculates, pedestrian navigation positioning function can be realized accurately in real time in actual environment.

In order to realize above-mentioned technical purpose, technical scheme of the present invention is:

Pedestrian navigation system, primarily of sensor assembly, signal processing module, navigation computer module and output display terminal four part composition, should be fixed on the ankle position of pedestrian based on the pedestrian navigation system of multisensor.Sensor assembly is made up of GPS, three single shaft mems accelerometers, three single shaft MEMS gyro instrument, three axle magnetic compasses, barometric altimeter and temperature sensors etc.In the outdoor of spaciousness, no signal is blocked, and now pedestrian navigation system adopts GPS device to carry out navigator fix; When being in the particular surroundingss such as indoor, gps signal lost efficacy, then merge the technical method of multisensor, carry out dead reckoning, calculate pedestrian at three-dimensional movement locus.The algorithm of the present invention involved by indoor navigation has: paces detect, course calculates and altitude location, the Data Detection of MEMS accelerograph collection is utilized to go out the paces number of pedestrian in indoor walking, MEMS gyro instrument and magnetic compass simple combination calculate the course of pedestrian's walking, can be realized the pedestrian movement's trajectory calculation in plane by meter step number and course, mems accelerometer and barometer combine and obtain the movement locus of pedestrian in short transverse.

1, calculate pedestrian movement's track in plane mainly to solve paces and to detect and course calculates two parts problem, the last effective position location information of the lower GPS of pedestrian navigation system accounting record, and as plane motion track t 0initial value (the X in moment 0, Y 0).By the distance S that measurement row people walks 0and azimuth angle theta 0, subsequent time t can be extrapolated 1position, S 0and θ 0represent that pedestrian is from t respectively 0moment position (X 0, Y 0) walk t 1moment position (X 1, Y 1) displacement and absolute course.So pedestrian is at moment t kmovement locus can be expressed as: , , wherein, X krepresent the position of k moment X-direction, X k-1represent the position of k-1 moment X-direction, Y krepresent the position of k moment Y-direction, Y k-1represent the position of k-1 moment Y-direction, S krepresent the displacement between the k-1 moment to k moment.S k=n k-1p k-1, n k-1represent the paces number of walking between the k-1 moment to k moment, P k-1represent step-length, θ kfor course angle.

(1) paces detection can by carrying out a series of digital filtering, peakvalue's checking, dynamic threshold, dynamic accuracy to the acceleration evaluation gathered, and paces count, get rid of invalid paces counting etc. arranges and obtains Steps.

1. in order to make the signal waveform of accelerometer more level and smooth, " data smoothing algorithm " can be applied and carry out digital filtering.It is in the one-dimension array of 100 that first step continuous acquisition 100 data points leave capacity in; Second step is shifted to array from high to low successively, removes No. 0 element of data, by the most significant digit of the deposit data of up-to-date collection in array; 3rd step is averaged to this 100 number, is filtered data.Follow-up often collection second and third step of Data duplication can realize digital filtering.

2. determine dynamic threshold, pedestrian navigation system often samples the data of No. 100 accelerometers by the maximal value of renewal 3 axle acceleration and minimum value, and its mean value is called " dynamic threshold ".

3. dynamic accuracy precision [i] is determined, first the peak-to-peak value Vpp [i] of 3 axes accelerometers in these 100 times samplings is calculated, then dynamic accuracy is obtained by peak-to-peak value, wherein i=0,1,2, expression is the acceleration of 3 axis, wherein Y1 ~ Y3, X1 ~ X4 are experience exercise values, and Y1>Y2>Y3>, X1>X2>X3>X4, needs the worth situation of change by gathering repeatedly accelerometer to determine.

If Vpp [i] >=Y1, so precision [i]=X1;

If Y2≤Vpp [i] < is Y1, so precision [i]=X2;

If Y3≤Vpp [i] < is Y2, so precision [i]=X3;

Otherwise precision [i]=X4.

4. paces counting, mainly be divided into three steps: linear displacement eliminates high frequency noise, define two new array old_fixed [3] and new_fixed [3], value when new sampled data arrives in new_fixed [i] unconditionally moves in old_fixed [i], if corresponding axial acceleration information change is more than or equal to predefine precision precision [i] simultaneously, to be moved in new_fixed [i], otherwise the value in new_fixed [i] will remain unchanged; The peakvalue's checking of 3 axes accelerometers, judges x, and y, z tri-axle that acceleration change is maximum in axle is as current effective meter step axle; Dynamic threshold is adjudicated, and accelerating curve strides across dynamic threshold dc [i], and the slope of accelerating curve is negative value, and the paces number Steps of meter step register is by increase by step.

5. invalid paces counting is got rid of, real rhythmical paces must be found to get rid of invalid vibration, the velocity that usual people are the fastest is 5 steps per second, and the slowest walking speed is every 2 seconds 1 steps, and the time interval of such two effective paces is within time window [0.2s-2.0s].But have employed the sampling rate (5ms) of 200Hz in this meter step algorithm, if the data break of two paces is between 40 ~ 400, then the time between two steps of illustrating is within valid window.

Step-length is more doubt variable in pedestrian navigation system, not only varies with each individual, also because of time and different, vary in different localities, this patent adopts and estimates initial value, and the method for on-line tuning correction obtains, suppose that the moving step sizes of pedestrian is L, then in pedestrian navigation system, the relative shift of pedestrian is S k=n k-1p k-1=Steps × L.

(2) course angle θ kcalculating whether is according to motion course the course that larger change state comes choice for use gyroscope integration course or choice for use magnetic compass.Certain threshold value is set, if when the integration of gyro data is greater than this threshold value in the current short time, then can thinks that motion course is in variable condition, select gyro data integral and calculating current course value; Otherwise, if when the integration of gyro data is less than this threshold value in the current short time, then thinks that motion course is in stable or less variable condition, adopt magnetic compass data to calculate current course value.

2, height and position H kcalculating is obtained by vertical direction accelerometer and barometer simple combination, first obtains elemental height H by barometer 0, then use the increment △ H in the acceleration information computed altitude direction of vertical direction, i.e. H k=H k-1+ △ H, H in formula kfor the height in k moment, H k-1for the height in k-1 moment.

the advantage of the invention and the effect reached:

(1) this patent merges multi-sensor information and builds pedestrian navigation system, overcome rely on single gps signal indoor or have a shelter time performance reduce, cannot the inferior position of normal navigation and location.

(2) the multisensor pedestrian navigation system be made up of MEMS gyro instrument, mems accelerometer, magnetic compass and barometer, meets the requirement that personal navigation instrument volume is little, cost is low, is more suitable for the pedestrian navigation scheme of walking.

Accompanying drawing explanation

Fig. 1 pedestrian navigation System Working Principle figure;

Fig. 2 digital filter;

Fig. 3 course angle correction process flow diagram;

Fig. 4 rectilinear line test trails figure;

Fig. 5 goes upstairs test trails figure.

Embodiment

Below in conjunction with accompanying drawing, the invention will be further described.Following examples only for technical scheme of the present invention is clearly described, and can not limit the scope of the invention with this.

Pedestrian navigation system forms primarily of sensor assembly, signal processing module, navigation computer module and output display terminal four part.This patent merges multi-sensor information and builds pedestrian navigation system, overcome rely on single gps signal indoor or have a shelter time performance reduce, cannot the inferior position of normal navigation and location, its principle of work as shown in Figure 1.

When pedestrian steps into building or have buildings to block, gps signal lost efficacy and just cannot normally locate, the last effective position location information of the lower GPS of now pedestrian navigation system accounting record, and as t 0initial value (the X in moment 0, Y 0).By the distance S that measurement row people walks 0and azimuth angle theta 0, subsequent time t can be extrapolated 1position, S 0and θ 0represent that pedestrian is from t respectively 0moment position (X 0, Y 0) walk t 1moment position (X 1, Y 1) displacement and absolute course.So pedestrian is at t kmoment movement locus can be expressed as: , .But the travel distance of pedestrian is difficult to directly directly be measured by sensor, is also not easy to calculate according to the mode of integrated acceleration, therefore in pedestrian navigation system, the main product of step number and step-length that adopts obtains relative shift, that is: S k=n k-1p k-1, in formula, n k-1represent the step number of walking, P k-1represent step-length.Step number can by carrying out a series of digital filtering to the acceleration evaluation gathered, peakvalue's checking, dynamic threshold, dynamic accuracy, paces count, get rid of invalid paces counting etc. processes and obtains, step-length is more doubt variable in pedestrian navigation system, not only vary with each individual, also because of time and different, vary in different localities, often adopt and estimate initial value, the method for on-line tuning correction obtains.Course angle θ kcalculating whether is in larger change state according to motion course to come choice for use gyroscope integration course or choice for use magnetic course.Height H kpositional information is obtained by vertical direction accelerometer and barometer simple combination, first obtains initial height position information H by barometer 0, then use the increment △ H in the accekeration computed altitude direction of vertical direction.

(1) the relative displacement P of pedestrian in indoor walking is calculated k

Pedestrian navigation system involved by this patent is the ankle position being worn on pedestrian, and pedestrian in the process of walking navigational computer obtains the paces number n of walking by processing in three axes accelerometers the axis value with relatively large periodic accelerations change k-1.

(1) in order to make the signal waveform of accelerometer more level and smooth, " data smoothing algorithm " can be applied and carry out digital filtering, as shown in Figure 2.It is in the one-dimension array of 100 that first step continuous acquisition 100 data points leave capacity in; Second step is shifted to array from high to low successively, removes No. 0 element of data, by the most significant digit of the deposit data of up-to-date collection in array; 3rd step is averaged to this 100 number, is filtered data.Follow-up often collection second and third step of Data duplication can realize digital filtering.

(2) dynamic threshold is determined.Pedestrian navigation system is often sampled and is upgraded maximal value and the minimum value of 3 axle accelerations for 100 times, and the two mean value is called " dynamic threshold ", leaves in the array of dc [3].Ensuing 100 samplings utilize this threshold value to judge whether wearer steps paces, simultaneously in these 100 times samplings the maximal value of generation and the mean value of minimum value again as " dynamic threshold " next time.

dc[i]=(Max[i]+Min[i])/2;

Vpp[i]=Max[i]-Min[i]。

Wherein i=0,1,2, expression is the acceleration of 3 axis.Deposit " dynamic threshold " in dc [i], deposit the difference of the maxima and minima of 3 axial accelerations upgraded for 100 times of often sampling in Vpp [i], i.e. peak-to-peak value.

(3) dynamic accuracy precision [i] is determined.

If Vpp [i] >=Y1, so precision [i]=X1;

If Y2≤Vpp [i] < is Y1, so precision [i]=X2;

If Y3≤Vpp [i] < is Y2, so precision [i]=X3;

Otherwise precision [i]=X4.

Wherein i=0,1,2, expression is the acceleration of 3 axis.Y1 ~ Y3, X1 ~ X4 are experience exercise values, and Y1>Y2>Y3>, X1>X2>X3>X4, needs the worth situation of change by gathering repeatedly accelerometer to determine.

(4) meter step algorithm carries out paces counting.

1. eliminate high frequency noise by linear displacement, first define two new array old_fixed [3] and new_fixed [3], new sampled data leaves in array adresult [3].Value when new sampled data arrives in new_fixed [i] unconditionally moves in old_fixed [i].But whether new sampled data moves into new_fixed [i] depends on whether corresponding axial acceleration change is more than or equal to dynamic accuracy precision [i], the sampled result up-to-date if satisfied condition will be moved in new_fixed [i], otherwise the value in new_fixed [i] will remain unchanged.

old_fixed[i]=new_fixed[i];

If abs(new_fixed [i]-adresult [i]) >=precision [i], then new_fixed [i]=adresult [i].

2. the peakvalue's checking of 3 axial acceleration data, meter step algorithm will walk according to carrying out meter according to x, y, z tri-number of axle that acceleration change is maximum in axle.

Vpp [0] >=Vpp [1] & & Vpp [0] >=Vpp [2], x-axis acceleration change is maximum, will as calculating axle;

Vpp [1] >=Vpp [0] & & Vpp [1] >=Vpp [2], y-axis acceleration change is maximum, will as calculating axle;

Vpp [2] >=Vpp [0] & & Vpp [2] >=Vpp [1], z-axis acceleration change is maximum, will as calculating axle.

3. dynamic threshold judgement, calculates axle acceleration curve and stride across dynamic threshold dc [i], and the slope of accelerating curve is negative value, and meter step register Steps is by increase by step.

old_fixed[i]≥dc[i]&&new_fixed[i]<dc[i]

Wherein i is x, y, z tri-axle that acceleration change is maximum in axle.

(5) invalid paces counting is got rid of.In order to prevent the reason outside due to walking or running; acceleration is very fast or when slowly vibrating; also can think that it is a step; just must find real rhythmical paces, adopt pre_count and new_count register to record previous paces respectively and always upgrade number and current pace always upgrades number.Suppose that the velocity that people are the fastest is 5 steps per second, the slowest walking speed is every 2 seconds 1 steps, and the time interval of such two effective paces is within time window [0.2s-2.0s].But have employed the sampling rate (5ms) of 200Hz in this meter step algorithm, if be interposed between 40 ~ 400 between two paces, then the time between two steps of illustrating is within valid window.

If 40≤(new_count – new_count)≤400, then new_count=pre_count;

Otherwise new_count=pre_count, Steps=Steps-1.

Step-length is more doubt variable in pedestrian navigation system, adopts and estimates initial value, and the method for on-line tuning correction obtains, and supposes that the training pace of certain tester is L, so to sum up can obtain the paces parameter n of current time k-1=Steps, step-length P k-1=L, the relative shift S of pedestrian k=n k-1p k-1=Steps × L.

(2) the course angle θ of pedestrian's walking is calculated k

The method calculating course in this patent adopts the simple combination method being used alternatingly gyroscope and magnetic compass, whether is according to motion course the course that larger change state comes choice for use gyro data integration course or choice for use magnetic compass.Due to gyro data, integral contrast is accurate at short notice, and magnetic compass data are comparatively accurate under long-time stable state.So when motion course is in change state, then gyro data integration is obtained the course angle of course as current dead reckoning of moving; When motion course is in stable or less variable condition, then using the course angle of the motion course of magnetic compass data as current dead reckoning.Situation for the change of motion course can be judged by gyrostatic short time integration, and certain threshold value is set, if when in the current short time, the integration of gyro data is greater than this threshold value, then judge that motion course is in variable condition, otherwise, if when the integration of gyro data is less than or equal to this threshold value in the current short time, then judge that motion course is in stable or less variable condition.Concrete combined method flow process is as shown in Figure 3:

(3) planar line walk test (E, N)

Do not consider GPS last effective location data during demonstration test, initial value is set to (0.0,0.0) unit rice, i.e. X 0=0.0, Y 0=0.0, concrete computing formula is as follows. , , as shown in Figure 4, the terminal that algorithm calculates is positioning error with the distance that differs between starting point to experimental results, negligible within experiment allowed band.

(4) calculate pedestrian in room walking height and position H k

In this patent, chamber height positional information is obtained by vertical direction accelerometer and barometer simple combination, first obtains initial height position information H by barometer 0, then use the increment △ H in the accekeration computed altitude direction of vertical direction.Adopt array Accz [3] to deposit 3 continuous print accelerometer datas, wherein Accz [1] is the current data that will judge to process.Also there is effective and invalid vibration in stair climbing process simultaneously, this just needs to get rid of invalid vibration by " data window ", always upgrade total renewal number when number and current time are topped bar when once topping bar before register T and t records respectively, h_flag represents current effective marker of topping bar.

If Accz [1] >=K1 & & Accz [1]≤K2 & & Accz [1] >=Accz [0] & & Accz [1] >=Accz [2] & & M≤(t-T)≤N, then T=t, h_flag=1;

Otherwise h_flag=0.

Wherein K1, K2, M, the setting of N is different because of people and equipment, need to be obtained by many experiments, minimum acceleration when wherein K1 represents that pedestrian tops bar, peak acceleration when K2 represents that pedestrian tops bar, M represents that the slowest time that pedestrian steps to a new level, N represent the fastest time that pedestrian steps to a new level.When judging next group data, need to carry out shifting function to the data in array Accz [3], the accelerometer data of the vertical direction of up-to-date collection is deposited in i.e. Accz [0]=Accz [1], Accz [1]=Accz [2], Accz [2].The increment △ H=h_flag × h in present level direction, h represents the average height of single step.

Elemental height H when definition pedestrian begin column is walked 0, the height of subsequent time is H 1, then the height of subsequent time is H 2, analogize in proper order, the height in k moment is H k, the moving track calculation method of short transverse is H 1=H 0+ △ H, H 2=H 1+ △ H ..., H k=H k-1+ △ H, concrete test findings as shown in Figure 5.

The above is only the preferred embodiment of the present invention; it should be pointed out that for those skilled in the art, under the prerequisite not departing from the technology of the present invention principle; can also make some improvement and distortion, these improve and distortion also should be considered as protection scope of the present invention.

Claims (6)

1. based on a pedestrian navigation system for multisensor, it is characterized in that, comprise the sensor assembly being fixed on pedestrian's ankle position;
Sensor assembly comprises GPS, the mems accelerometer of three single shafts, the MEMS gyro instrument of three single shafts, the magnetic compass of three axles and barometer;
When GPS no signal is blocked, GPS is adopted to carry out navigator fix;
When gps signal lost efficacy, the paces number utilizing mems accelerometer acquisition testing pedestrian to walk, was combined with the data of magnetic compass the course calculating pedestrian's walking by MEMS gyro instrument, calculated the pedestrian movement's track in plane according to paces number and course meter; The data utilizing mems accelerometer and barometer to obtain obtain the movement locus of pedestrian in short transverse, realize the location of pedestrian at three-dimensional movement locus.
2., based on the air navigation aid of the pedestrian navigation system based on multisensor according to claim 1, it is characterized in that, comprise the following steps:
Sensor assembly is fixed on pedestrian's ankle position; Sensor assembly comprises GPS, the mems accelerometer of three single shafts, the MEMS gyro instrument of three single shafts, the magnetic compass of three axles and barometer;
When GPS no signal is blocked, GPS is adopted to carry out navigator fix;
When gps signal lost efficacy, the paces number utilizing mems accelerometer acquisition testing pedestrian to walk, was combined with the data of magnetic compass the course calculating pedestrian's walking by MEMS gyro instrument, calculated the pedestrian movement's track in plane according to paces number and course meter; The data utilizing mems accelerometer and barometer to obtain obtain the movement locus of pedestrian in short transverse, realize the location of pedestrian at three-dimensional movement locus.
3. the air navigation aid of the pedestrian navigation system based on multisensor according to claim 2, is characterized in that, the calculation procedure of plane one skilled in the art movement locus is as follows:
The last effective position location information of meter record GPS, as plane motion track t 0initial value (the X in moment 0, Y 0); The distance S walked by measurement row people and course θ, extrapolates subsequent time t 1position, S 0and θ 0represent that pedestrian is from t respectively 0moment position (X 0, Y 0) walk t 1moment position (X 1, Y 1) displacement and absolute course;
Then pedestrian is at t kmoment movement locus is expressed as: X k=X k-1+ S ksin θ k, Y k=Y k-1+ S kcos θ k, wherein, X k-1represent the position of k-1 moment X-direction, Y krepresent the position of k moment Y-direction, Y k-1represent the position of k-1 moment Y-direction, S krepresent the displacement between the k-1 moment to k moment; S k=n k-1p k-1, n k-1represent the paces number of walking between the k-1 moment to k moment, P k-1represent step-length.
4. the air navigation aid of the pedestrian navigation system based on multisensor according to claim 2, is characterized in that, the step of the paces number utilizing mems accelerometer acquisition testing pedestrian to walk is:
1. digital filtering is carried out to the data separate data smoothing algorithm of the accelerometer gathered: it is in the one-dimension array of 100 that first step continuous acquisition 100 data points leave capacity in; Second step is shifted to array from high to low successively, removes No. 0 element of data, by the most significant digit of the deposit data of up-to-date collection in array; 3rd step is averaged to this 100 number, is filtered data; Namely follow-up often collection second and third step of Data duplication realizes digital filtering;
2. determine dynamic threshold: the maximal value of the accelerometer of Data Update three single shafts of No. 100 accelerometers of often sampling and minimum value, its mean value is dynamic threshold;
3. dynamic accuracy precision [i] is determined: the peak-to-peak value Vpp first calculating the accelerometer of three single shafts in these 100 times samplings, then obtains dynamic accuracy by peak-to-peak value;
4. the counting of paces number: define two array old_fixed [3] and new_fixed [3], value when new sampled data arrives in array new_fixed [i] unconditionally moves in array old_fixed [i], if corresponding axial acceleration information change is more than or equal to predefine dynamic accuracy precision [i] simultaneously, to be moved in array new_fixed [i], otherwise the value in array new_fixed [i] remains unchanged;
The peakvalue's checking of the accelerometer of three single shafts, judges x, and y, z tri-axle that acceleration change is maximum in axle is as current effective meter step axle; Dynamic threshold is adjudicated, and accelerating curve strides across dynamic threshold dc [i], and the slope of accelerating curve is negative value, and the paces number Steps of meter step register increases by a step;
5. invalid paces counting is got rid of.
5. the air navigation aid of the pedestrian navigation system based on multisensor according to claim 2, is characterized in that, determines course and the course angle θ of pedestrian's walking kcalculation procedure be: determine that the data using gyroscope or magnetic compass calculate course angle θ according to the change state in motion course k;
Arrange a threshold value, if when in current setting-up time, the integration of gyro data is greater than this threshold value, then course of moving is in variable condition, adopts gyro data integral and calculating current course angle;
If when in current setting-up time, the integration of gyro data is less than this threshold value, then course of moving is in stable or less variable condition, adopts magnetic compass data to calculate current course angle.
6. the air navigation aid of the pedestrian navigation system based on multisensor according to claim 2, is characterized in that, height and position H kcalculate the mems accelerometer by vertical direction and barometer acquisition, first obtain initial height and position H by barometer 0, then use the increment △ H in the measurement data computed altitude direction of the mems accelerometer of vertical direction, i.e. H k=H k-1+ △ H, H in formula kfor the height in k moment, H k-1for the height in k-1 moment.
CN201510695799.5A 2015-10-23 2015-10-23 System and method for pedestrian navigation based on multiple sensors CN105241454A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201510695799.5A CN105241454A (en) 2015-10-23 2015-10-23 System and method for pedestrian navigation based on multiple sensors

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201510695799.5A CN105241454A (en) 2015-10-23 2015-10-23 System and method for pedestrian navigation based on multiple sensors

Publications (1)

Publication Number Publication Date
CN105241454A true CN105241454A (en) 2016-01-13

Family

ID=55039184

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201510695799.5A CN105241454A (en) 2015-10-23 2015-10-23 System and method for pedestrian navigation based on multiple sensors

Country Status (1)

Country Link
CN (1) CN105241454A (en)

Cited By (15)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105651304A (en) * 2016-03-22 2016-06-08 广州市中海达测绘仪器有限公司 Golf ball range-measurement system and method
CN106052672A (en) * 2016-05-09 2016-10-26 深圳市沃特沃德股份有限公司 Device, system and method for recording and presenting animal motion trail
CN106197412A (en) * 2016-06-30 2016-12-07 北京海顿中科技术有限公司 The pinpoint method of micro-inertial navigation is carried out based on accelerometer, gyroscope
CN106248079A (en) * 2016-08-26 2016-12-21 江西瑞斯科救援科技有限公司 A kind of individual soldier's 3 D positioning system and localization method thereof
CN106781271A (en) * 2016-11-21 2017-05-31 南京邮电大学 A kind of Falls in Old People salvage system and method based on acceleration transducer
CN106940190A (en) * 2017-05-15 2017-07-11 英华达(南京)科技有限公司 Navigation drawing drawing method, navigation picture draw guider and navigation system
CN106996792A (en) * 2017-04-12 2017-08-01 安徽省沃瑞网络科技有限公司 A kind of building for sale neck visitor's navigation positioning system based on Android
CN107027157A (en) * 2017-05-24 2017-08-08 北京小米移动软件有限公司 Location updating method and equipment
CN107289935A (en) * 2016-04-01 2017-10-24 中国航空工业第六八研究所 A kind of indoor navigation algorithm suitable for wearable device
CN107607976A (en) * 2017-07-28 2018-01-19 烟台持久钟表有限公司 The Big Dipper and autonomic sensor positioner and its localization method
CN108061552A (en) * 2016-11-09 2018-05-22 杭州植嘉科技有限公司 A kind of method that outdoor sports path creates and reappears
CN108318033A (en) * 2017-12-28 2018-07-24 和芯星通(上海)科技有限公司 Pedestrian navigation method and system, electronic equipment and storage medium
CN108731662A (en) * 2017-03-15 2018-11-02 酷异有限公司 3 D locating device and method
CN109074716A (en) * 2016-04-19 2018-12-21 帝人株式会社 The article for having warning system
CN109827568A (en) * 2019-01-29 2019-05-31 东北大学秦皇岛分校 Pedestrian level location estimation method in tier building based on MEMS sensor

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20080169958A1 (en) * 2006-05-18 2008-07-17 Cohen Clark E Localized jamming of navigation signals
CN101907467A (en) * 2010-08-06 2010-12-08 浙江大学 Method and device for personal location based on motion measurement information
WO2012057256A1 (en) * 2010-10-28 2012-05-03 株式会社ゼンリンデータコム Navigation terminal, navigation method, and navigation program
WO2013031355A1 (en) * 2011-08-30 2013-03-07 ソニー株式会社 Information processing device, information processing method, program, and recording medium
CN104200234A (en) * 2014-07-11 2014-12-10 杭州微纳科技有限公司 Human body action modeling and recognizing method
CN104251699A (en) * 2013-06-27 2014-12-31 珠海世纪鼎利通信科技股份有限公司 Indoor space positioning equipment and positioning method thereof
CN104977003A (en) * 2015-06-29 2015-10-14 中国人民解放军国防科学技术大学 Indoor people search method, cloud server, and system based on shared track

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20080169958A1 (en) * 2006-05-18 2008-07-17 Cohen Clark E Localized jamming of navigation signals
CN101907467A (en) * 2010-08-06 2010-12-08 浙江大学 Method and device for personal location based on motion measurement information
WO2012057256A1 (en) * 2010-10-28 2012-05-03 株式会社ゼンリンデータコム Navigation terminal, navigation method, and navigation program
WO2013031355A1 (en) * 2011-08-30 2013-03-07 ソニー株式会社 Information processing device, information processing method, program, and recording medium
CN104251699A (en) * 2013-06-27 2014-12-31 珠海世纪鼎利通信科技股份有限公司 Indoor space positioning equipment and positioning method thereof
CN104200234A (en) * 2014-07-11 2014-12-10 杭州微纳科技有限公司 Human body action modeling and recognizing method
CN104977003A (en) * 2015-06-29 2015-10-14 中国人民解放军国防科学技术大学 Indoor people search method, cloud server, and system based on shared track

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
刘程 等: "自适应计步检测算法研究", 《压电与声光》 *
曾鹏飞: "基于Wi-Fi信号强度与多传感器信息融合的室内定位系统研究", 《中国优秀硕士学位论文全文数据库 信息科技辑》 *
陈银溢: "基于CC2541和LIS3DSH的计步器设计", 《机械工程与自动化》 *

Cited By (16)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105651304A (en) * 2016-03-22 2016-06-08 广州市中海达测绘仪器有限公司 Golf ball range-measurement system and method
CN107289935A (en) * 2016-04-01 2017-10-24 中国航空工业第六八研究所 A kind of indoor navigation algorithm suitable for wearable device
CN109074716A (en) * 2016-04-19 2018-12-21 帝人株式会社 The article for having warning system
CN106052672A (en) * 2016-05-09 2016-10-26 深圳市沃特沃德股份有限公司 Device, system and method for recording and presenting animal motion trail
CN106052672B (en) * 2016-05-09 2018-01-05 深圳市沃特沃德股份有限公司 A kind of device, system and method for recording, path of animal movement being presented
CN106197412A (en) * 2016-06-30 2016-12-07 北京海顿中科技术有限公司 The pinpoint method of micro-inertial navigation is carried out based on accelerometer, gyroscope
CN106248079A (en) * 2016-08-26 2016-12-21 江西瑞斯科救援科技有限公司 A kind of individual soldier's 3 D positioning system and localization method thereof
CN108061552A (en) * 2016-11-09 2018-05-22 杭州植嘉科技有限公司 A kind of method that outdoor sports path creates and reappears
CN106781271A (en) * 2016-11-21 2017-05-31 南京邮电大学 A kind of Falls in Old People salvage system and method based on acceleration transducer
CN108731662A (en) * 2017-03-15 2018-11-02 酷异有限公司 3 D locating device and method
CN106996792A (en) * 2017-04-12 2017-08-01 安徽省沃瑞网络科技有限公司 A kind of building for sale neck visitor's navigation positioning system based on Android
CN106940190A (en) * 2017-05-15 2017-07-11 英华达(南京)科技有限公司 Navigation drawing drawing method, navigation picture draw guider and navigation system
CN107027157A (en) * 2017-05-24 2017-08-08 北京小米移动软件有限公司 Location updating method and equipment
CN107607976A (en) * 2017-07-28 2018-01-19 烟台持久钟表有限公司 The Big Dipper and autonomic sensor positioner and its localization method
CN108318033A (en) * 2017-12-28 2018-07-24 和芯星通(上海)科技有限公司 Pedestrian navigation method and system, electronic equipment and storage medium
CN109827568A (en) * 2019-01-29 2019-05-31 东北大学秦皇岛分校 Pedestrian level location estimation method in tier building based on MEMS sensor

Similar Documents

Publication Publication Date Title
US8784309B2 (en) Sensor fusion for activity identification
Qian et al. An improved indoor localization method using smartphone inertial sensors
Tian et al. Pedestrian dead reckoning for MARG navigation using a smartphone
Zhang et al. A handheld inertial pedestrian navigation system with accurate step modes and device poses recognition
CN104457751B (en) Indoor and outdoor scene recognition method and system
Zhou et al. Activity sequence-based indoor pedestrian localization using smartphones
CN105547285B (en) Navigation system in building based on virtual reality technology
Sun et al. Activity classification and dead reckoning for pedestrian navigation with wearable sensors
CN103968827B (en) A kind of autonomic positioning method of wearable body gait detection
CN105628024B (en) Single positioning navigator based on Multi-sensor Fusion and positioning navigation method
TWI457539B (en) Multi-posture step length calibration system and method for indoor positioning
Fang et al. Design of a wireless assisted pedestrian dead reckoning system-the NavMote experience
Georgy et al. Modeling the stochastic drift of a MEMS-based gyroscope in gyro/odometer/GPS integrated navigation
CN101907467B (en) Method and device for personal location based on motion measurement information
JP5295016B2 (en) Global positioning system and dead reckoning (GPS &amp; DR) integrated navigation system, and method for providing navigation information of a moving body
CN104180805B (en) Smart phone-based indoor pedestrian positioning and tracking method
EP1986170B1 (en) Traffic situation determination system
CN102944240B (en) A kind of inertial navigation system based on smart mobile phone and method
CN102419180B (en) Indoor positioning method based on inertial navigation system and WIFI (wireless fidelity)
US8224575B2 (en) Method and computer-readable storage medium with instructions for processing data in an internal navigation system
US7302359B2 (en) Mapping systems and methods
CN104819716A (en) Indoor and outdoor personal navigation algorithm based on INS/GPS (inertial navigation system/global position system) integration of MEMS (micro-electromechanical system)
Alvarez et al. Pedestrian navigation based on a waist-worn inertial sensor
CA2615214C (en) Method and device for measuring the progress of a moving person
CN106225784B (en) Based on inexpensive Multi-sensor Fusion pedestrian dead reckoning method

Legal Events

Date Code Title Description
PB01 Publication
C06 Publication
SE01 Entry into force of request for substantive examination
C10 Entry into substantive examination
RJ01 Rejection of invention patent application after publication

Application publication date: 20160113

RJ01 Rejection of invention patent application after publication