CN109061616A - A kind of Moving objects location method - Google Patents

A kind of Moving objects location method Download PDF

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CN109061616A
CN109061616A CN201811016737.7A CN201811016737A CN109061616A CN 109061616 A CN109061616 A CN 109061616A CN 201811016737 A CN201811016737 A CN 201811016737A CN 109061616 A CN109061616 A CN 109061616A
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value
strength indication
signal strength
moving objects
curve
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CN109061616B (en
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施佺
夷立华
施佳佳
孙玲
许致火
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Nantong University
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO 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
    • G01S11/00—Systems for determining distance or velocity not using reflection or reradiation
    • G01S11/02—Systems for determining distance or velocity not using reflection or reradiation using radio waves
    • G01S11/06—Systems for determining distance or velocity not using reflection or reradiation using radio waves using intensity measurements
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30—Services specially adapted for particular environments, situations or purposes
    • H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Position Fixing By Use Of Radio Waves (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

The invention proposes a kind of Moving objects location methods, active mobile tag is set on mobile node, it is acquired by being set to the wireless signal that the reader at stationary nodes issues mobile tag, the information interaction of server and each reader simultaneously carries out data preprocessing operation formation wireless signal sequential model, specifically: reader obtains corresponding signal strength indication from mobile tag by Radio Frequency Identification Technology；Signal strength indication is fitted by nonlinear least square method, curve and the wireless signal sequential model are carried out Cross Correlation Matching, obtain distance-signal strength indication relationship by the curve after obtaining removal heterodoxy value optimization；Server calculates coordinate position by weighted mass center positioning mode, is accurately positioned coordinate position further according to Unscented kalman filtering, obtains required coordinate points；Using method of the invention, moving target position can be carried out to stablize, accurately estimated.

Description

A kind of Moving objects location method
Technical field
The present invention relates to radio frequency identification location technologies more particularly to a kind of be accurately positioned using Unscented kalman filtering to move Mesh calibration method.
Background technique
Radio frequency identification location technology has important application in the scenes such as logistics management, books in libraries management.With The development of active radio frequency Identification technology identifies the increase of distance, and low speed moves target in electric bicycle and pedestrian etc. at present It is applied in positioning.In view of mobile target Portable device ability is weaker, operating range is flexibly, speed is relatively traditional is applied The characteristics such as scene is very fast, it is desirable that location technology equipment convenience with higher and cheap equipment cost.
Currently, traditional Moving objects location method mainly has indoor WIFI positioning and outdoor GPS positioning two major classes.It is indoor WIFI positioning access threshold is low, but its equipment precision is lower, and is not suitable with and relatively moves faster occasion, Wu Fashi for target When tracking position of object.Outdoor GPS positioning technology is widely used, but is existed and influenced vulnerable to shelter, and the equipment charge period is short etc. Problem.
In conclusion the position for being accurately located mobile target is urgently to solve at present how on cheap cost basis Certainly the problem of.
Summary of the invention
The main purpose of the present invention is to provide the sides using the mobile target of low speed in Unscented kalman filtering precise positioning Method can be accurately located the position of mobile target with the cost of relative moderate, in order to achieve the above objectives, specifically by following technical side Case is realized:
The Moving objects location method, active mobile tag is set on mobile node, by being set to fixation The wireless signal that reader at node issues mobile tag is acquired, the information interaction of server and each reader, Server carries out data preprocessing operation and is matched to obtain the positional relationship of mobile node by wireless signal sequential model, Specifically:
Reader obtains corresponding signal strength indication from mobile tag by Radio Frequency Identification Technology；Pass through non-linear minimum Signal strength indication is fitted by square law, the curve after obtaining removal heterodoxy value optimization, by curve and the wireless signal gradual change mould Type carries out Cross Correlation Matching, obtains distance-signal strength indication relationship；
Server calculates coordinate position by weighted mass center positioning mode, is accurately positioned further according to Unscented kalman filtering Coordinate position obtains the coordinate points of mobile target.
The Moving objects location method it is further design be, the data prediction: collection of server wireless communication Number corrects the propagation model of wireless signal, obtains signal strength indication-distance standard relationship curve and forms wireless signal gradually Varying model, and the wireless signal sequential model is stored in server；
The further design of the Moving objects location method is, includes the following steps: in data prediction
Step 1) constructs wireless signal sequential model according to formula (1):
In formula (1), p (d) indicate apart from base station linear distance be d when the signal strength indication that receives of terminal, i.e. RSSI value； p(d0) indicate apart from base station to be d0When the signal power that receives of terminal；d0For reference distance, n is the path attenuation factor；
Step 2) passes through linear naturalization Optimized model value according to formula (2):
ρi=-10lgdi, i=1,2 ..., m
In formula (2),M indicates measurement point number；diIndicate ith measurement point The distance at place, RSSIiIndicate the signal strength indication at ith measurement point；ρiIndicate the desirable signal power at ith measurement point Value；
Step 3) is stored in associated databases after being averaging the model value after optimization.
The further design of the Moving objects location method is, by nonlinear least square method by signal strength indication Fitting, the curve after obtaining removal heterodoxy value optimization specifically:
The propagation model for keeping matched curve approximation signal wireless by nonlinear system the signal strength indication collected, The model of the nonlinear system is y=f (x, θ), is met: minS (x)=fT(x) f (x)=| | f (x) | |2, wherein, f (x)= (f1(x),f2(x),...,fm(x))T, and x=(x1,x2,...,xn)T, the data of x expression fitting, S (x) expression lowest mean square mistake Difference function, θ indicate deviation value.
The further design of the Moving objects location method is, described to calculate coordinate according to weighted mass center positioning mode Position specifically:
Setting reading device position is respectively as follows: B1 (X1, Y1), B2 (X2, Y2) ..., Bn (Xn, Yn), mobile node are as follows: M (Xi, Yi), the distance of mobile node to each fixed point are respectively d1, d2 ..., dn, then calculate mobile node coordinate according to formula (3)
The further design of the Moving objects location method is that Unscented kalman filtering passes through selection Sigma point, warp It crosses nonlinear function to map to obtain Nonlinear function point set, status predication and state correction is carried out to the point set, obtained down The state variable in one stage realizes used predicted value amendment true value, specifically:
Set systematic state variable X=[x, vx,y,vy]T, wherein x indicates X axis position；vxIndicate x-axis to speed；y Indicate Y-axis position；vyIndicate y-axis to speed.
Set state-transition matrixT is the signal scanning time, and by mobile node and origin Angle is as measured value.
The further design of the Moving objects location method is that the reader of the fixed point is outside using antenna Emit electromagnetic wave, radio circuit is equipped in the active label at mobile node, radio circuit is activated to transmitting electromagnetism at reader Wave, reader obtain signal strength indication.
The further design of the Moving objects location method is, described to curve and the wireless signal sequential model Cross Correlation Matching is carried out to specifically comprise the following steps:
Step A) according to the mean square error under formula (4) calculating optimal approximation:
Wherein, the value inscribed when x (f) is database standard curve；Y (f) is practical acquired value；
Step B) relative error is normalized into according to formula (5)
Step C) setting
Convolution (5) obtains:
Wherein, ρxyFor the related coefficient of x and y, according to the Schwarz inequality of summation form it is found that 0 < ρxy< 1, if ρxy= 1, mean square error 0 indicates that this two value is completely the same；If number ρxy=0, then illustrate that two data are completely inconsistent at this time；If related Coefficient ρxyYu indicates that approximate error is smaller close to 1, and two data values are more consistent；Work as ρxyWhen being intended to threshold value, then standard is used Value replaces actual value.
Advantages of the present invention is as follows:
The advanced line number Data preprocess of Moving objects location method of the invention in advance passes mass data amendment wireless signal Model is broadcast, signal strength indication-distance standard relationship curve is obtained；Reader utilizes Radio Frequency Identification Technology from shifting at stationary nodes Active label at dynamic node obtains corresponding signal strength indication.Signal strength indication is fitted using nonlinear least square method, Curve after obtaining removal heterodoxy value optimization, carries out Cross Correlation Matching for curve and server database standard curve, obtain away from From-signal strength indication relationship；Coordinate position is calculated using weighted mass center positioning mode, it is accurately fixed further according to Unscented kalman filtering Position coordinate position, obtains required coordinate points.Using method of the invention, moving target position can be carried out to stablize, accurately estimated Meter.
Method of the invention can be applied to: 1. Vehicular intelligent positioning systems；Place's installation data acquires equipment at the parting of the ways, Electronic active label card is installed on license plate, in this way it is prevented that motor vehicle/electric vehicle robber robs, police is also convenient for and quickly solves a case Lock suspect；.2. attendance system for company；RFID chest card is worn to employee, thus can be to avoid some employees Checking card does not have the case where working but, is also convenient for management of the enterprise to emphasis production area flow of personnel.
Detailed description of the invention
Fig. 1 is Moving objects location method flow schematic diagram of the present invention.
Fig. 2 is Moving objects location specific algorithm schematic diagram of the present invention
Fig. 3 is that figure is compared in difference of the distance of the mobile node of Three-channel data before and after filtering.
Fig. 4 is that figure is compared in difference of the speed of the mobile node of Three-channel data before and after filtering.
Specific embodiment
The present invention is further described in more detail with reference to the accompanying drawings and embodiments.
Moving objects location method in the present invention, as shown in Figure 1, comprising the following steps:
Step 101: mass data is corrected wireless signal propagation model in advance by data prediction, obtains signal strength indication- In the standard relationship curve deposit database of distance；
Specifically, signal strength model meets the simplification wireless signal sequential model of base station and terminal distance, as follows:
Wherein, p (d) indicate apart from base station linear distance be d when the signal strength indication that receives of terminal, i.e. RSSI value；p (d0) indicate apart from base station to be d0When the signal power that receives of terminal；d0For reference distance, n is the path attenuation factor；
Step 2) passes through linear naturalization Optimized model value according to formula (2):
ρi=-10lgdi, i=1,2 ..., m
Wherein,M indicates measurement point number；diIt indicates at ith measurement point Distance, RSSIiIndicate the signal strength indication at ith measurement point；ρiIndicate the desirable signal power value at ith measurement point；.
It is stored in associated databases after model value after optimization is averaging.
Step 102: reader obtains phase using active label of the Radio Frequency Identification Technology from mobile node at stationary nodes The signal strength indication answered.Signal strength indication is fitted using nonlinear least square method, the song after obtaining removal heterodoxy value optimization Curve and server database standard curve are carried out Cross Correlation Matching, obtain distance-signal strength indication relationship by line；
Specifically, the reader of fixed point launches outward electromagnetic wave using antenna, in the active label at mobile node Radio circuit activates to transmitting electromagnetic wave, reader at reader and obtains performance number, that is, signal strength indication of signal.It will acquire To the signal strength indication propagation model that keeps matched curve approximation signal wireless by nonlinear system, the signal that will be collected The propagation model that intensity value keeps matched curve approximation signal wireless by nonlinear system, the model of the nonlinear system are y =f (x, θ) meets: minS (x)=fT(x) f (x)=| | f (x) | |2, wherein, f (x)=(f1(x),f2(x),...,fm(x) )T, and x=(x1,x2,...,xn)T, the data of x expression fitting, S (x) expression least mean-square error function, θ expression deviation value.
Value after above-mentioned fitting is calculated as follows with actual value:
Mean square error under optimal approximation are as follows:
Wherein, x is the value under database standard curve t moment；Y is practical acquired value.
It is normalized into relative error, then is had
As enabled
Then above formula is rewritten are as follows:
ρxy: the related coefficient of x and y, according to the Schwarz inequality of summation form it is found that 0 < ρxy<1.If correlation coefficient ρxy =1, mean square error 0 indicates that this two value is completely the same；If correlation coefficient ρxy=0, then illustrate that two data are completely different at this time It causes；If correlation coefficient ρxyYu indicates that approximate error is smaller close to 1, and two data values are more consistent.Work as ρxyWhen being intended to threshold value, Actual value can be then replaced with standard value, just have new RSSI value-distance relation at this time.
Step 103: calculating coordinate position using weighted mass center positioning mode, be accurately positioned further according to Unscented kalman filtering Coordinate position obtains required coordinate points.
Specifically, Unscented kalman filtering maps to obtain nonlinear function by nonlinear function by selection Sigma point It is worth point set, status predication and state correction is carried out to the point set, the state variable of next stage is obtained, realizes used predicted value True value is corrected, specifically:
Set systematic state variable X=[x, vx,y,vy]T, wherein x indicates X axis position；vxIndicate x-axis to speed；y Indicate Y-axis position；vyIndicate y-axis to speed.
Set state-transition matrixT is the signal scanning time, and by mobile node and origin Angle is as measured value.After the completion of this step, show the positioning that mobile target has been completed.
Such as Fig. 2, the process of the mobile target target positioning of the present embodiment is described in detail.
Firstly, carrying out data prediction.First the environmental data near a large amount of acquisition fixed antennas (i.e. signal strength indication-away from From), after then multi-group data utilizes dynamic environment model optimization, obtained value to be averaging as the RSSI value-under the environment away from From in standard curve deposit database.
Signal strength indication is fitted using nonlinear least square method secondly, asking, the song after obtaining removal heterodoxy value optimization Curve and server database standard curve are carried out Cross Correlation Matching, obtain distance-signal strength indication relationship by line.This implementation Example in, using label A as mobile node, A point reader 1, reader 2, reader 3 communication range in move, obtain phase R1, R2, the R3 answered.R1, r2 and r3 value, i.e. z value are obtained after nonlinear least square fitting, at this time and database standard Data are matched to obtain distance d1, d2 and d3 accordingly.
Finally, coordinate position is calculated using weighted mass center positioning mode, further according to Unscented kalman filtering after noise filtering It is accurately positioned coordinate position, obtains required coordinate points.In the present embodiment, the resulting position of weighted mass center isVia karr It is graceful filter out noise after obtain small noiseUnscented kalman filtering ukf is usedCorrectionAfterwards
To position (X, Y).Difference after position filtering and before is shown in Fig. 3, and the difference of speed is shown in Fig. 4, X axis speed effect after filtering processing compares as shown in Figure 4, and no filter value, which has had, to be obviously improved.Y-axis speed Value is obviously improved having after UKF is handled, and illustrates preferably inhibit the interference in external environment to make an uproar using UKF Sound is approached as much as possible to true value.To sum up, method of the invention multiplies the different value of fitting removal and without mark by carrying out non-linear two Kalman filtering inhibits noise to significantly improve positioning accuracy, it was confirmed that effectiveness of the invention.
The foregoing is only a preferred embodiment of the present invention, but scope of protection of the present invention is not limited thereto, In the technical scope disclosed by the present invention, any changes or substitutions that can be easily thought of by anyone skilled in the art, It should be covered by the protection scope of the present invention.Therefore, protection scope of the present invention should be with scope of protection of the claims Subject to.

Claims (8)

1. a kind of Moving objects location method, which is characterized in that active mobile tag is set on mobile node, by setting The wireless signal that the reader being placed at stationary nodes issues mobile tag is acquired, and is believed between server and each reader Breath interaction, server carry out data preprocessing operation and are matched to obtain the position of mobile node by wireless signal sequential model Relationship is set, specifically:
Reader obtains corresponding signal strength indication from mobile tag by Radio Frequency Identification Technology；Pass through non-linear least square Signal strength indication is fitted by method, the curve after obtaining removal heterodoxy value optimization, by curve and the wireless signal sequential model into Row Cross Correlation Matching obtains distance-signal strength indication relationship；
Server calculates coordinate position by weighted mass center positioning mode, is accurately positioned coordinate further according to Unscented kalman filtering Position obtains the coordinate points of mobile target.
2. Moving objects location method according to claim 1, which is characterized in that the data prediction: server is adopted Collect wireless signal data, correct the propagation model of wireless signal, obtains signal strength indication-distance standard relationship curve and form nothing Line signal sequential model, and the wireless signal sequential model is stored in server.
3. Moving objects location method according to claim 2, which is characterized in that include following step in data prediction It is rapid:
Step 1) constructs wireless signal sequential model according to formula (1):
In formula (1), p (d) indicate apart from base station linear distance be d when the signal strength indication that receives of terminal, i.e. RSSI value；p(d0) It indicates apart from base station to be d0When the signal power that receives of terminal；d0For reference distance；N is the path attenuation factor；
Step 2) passes through linear naturalization Optimized model value according to formula (2):
ρi=-10lgdi, i=1,2 ..., m
In formula (2),M indicates measurement point number；diIt indicates at ith measurement point Distance, RSSIiIndicate the signal strength indication at ith measurement point；ρiIndicate the desirable signal power value at ith measurement point；
Step 3) is stored in associated databases after being averaging the model value after optimization.
4. Moving objects location method according to claim 3, which is characterized in that will be believed by nonlinear least square method The fitting of number intensity value, the curve after obtaining removal heterodoxy value optimization specifically:
The propagation model for keeping matched curve approximation signal wireless by nonlinear system the signal strength indication collected, it is described The model of nonlinear system is y=f (x, θ), is met: min S (x)=fT(x) f (x)=| | f (x) | |2, wherein, f (x)=(f1 (x),f2(x),...,fm(x))T, and x=(x1,x2,...,xn)T, the data of x expression fitting, S (x) expression least mean-square error Function, θ indicate deviation value.
5. Moving objects location method according to claim 4, which is characterized in that described according to weighted mass center positioning mode meter Calculate coordinate position specifically:
Setting reading device position is respectively as follows: B1 (X1, Y1), B2 (X2, Y2) ..., Bn (Xn, Yn), mobile node are as follows: M (Xi, Yi), the distance of mobile node to each fixed point is respectively d1, d2 ..., dn, then calculates mobile node coordinate according to formula (3)
6. Moving objects location method according to claim 4, which is characterized in that Unscented kalman filtering passes through selection Sigma point maps to obtain Nonlinear function point set by nonlinear function, carries out status predication and state school to the point set Just, the state variable for obtaining next stage realizes used predicted value amendment true value, specifically:
Set systematic state variable X=[x, vx,y,vy]T, wherein x indicates X axis position；vxIndicate x-axis to speed；Y indicates Y Axial position；vyIndicate y-axis to speed；
Set state-transition matrixT is the signal scanning time, and by the angle of mobile node and origin As measured value.
7. Moving objects location method according to claim 1, which is characterized in that the reader of the fixed point utilizes Antenna launches outward electromagnetic wave, and radio circuit is equipped in the active label at mobile node, and radio circuit is activated at reader Emit electromagnetic wave, reader obtains signal strength indication.
8. Moving objects location method according to claim 2, which is characterized in that described to curve and the wireless signal Sequential model carries out Cross Correlation Matching and specifically comprises the following steps:
Step A) according to the mean square error under formula (4) calculating optimal approximation:
Wherein, the value inscribed when x (f) is database standard curve；Y (f) is practical acquired value；
Step B) relative error is normalized into according to formula (5)
Step C) setting
Convolution (5) obtains:
Wherein, ρxyFor the related coefficient of x and y, according to the Schwarz inequality of summation form it is found that 0 < ρxy< 1, if ρxy=1, Square error is 0, indicates that this two value is completely the same；If number ρxy=0, then illustrate that two data are completely inconsistent at this time；If related coefficient ρxyYu indicates that approximate error is smaller close to 1, and two data values are more consistent；Work as ρxyWhen being intended to threshold value, then standard value generation is used For actual value.
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CN109788451A (en) * 2019-04-03 2019-05-21 皖西学院 A kind of indoor orientation method of adaptive equipment conversion
CN110824423A (en) * 2019-11-26 2020-02-21 北京壹氢科技有限公司 Multi-unmanned vehicle collaborative navigation positioning method and system
CN110944293A (en) * 2019-11-26 2020-03-31 西安烽火电子科技有限责任公司 Radio search positioning method based on path attenuation and Kalman filtering fusion
CN110824423B (en) * 2019-11-26 2021-08-17 北京壹氢科技有限公司 Multi-unmanned vehicle collaborative navigation positioning method and system
CN111586605A (en) * 2020-05-20 2020-08-25 南通大学 KNN indoor target positioning method based on adjacent weighted self-adaptive k value
CN111586605B (en) * 2020-05-20 2021-11-26 南通大学 KNN indoor target positioning method based on adjacent weighted self-adaptive k value
CN112351385A (en) * 2020-10-26 2021-02-09 维沃移动通信有限公司 Positioning method and device and electronic equipment
CN113382356A (en) * 2021-06-18 2021-09-10 杭州雅观科技有限公司 Indoor positioning method based on Bluetooth signal
CN113382356B (en) * 2021-06-18 2022-07-15 杭州雅观科技有限公司 Indoor positioning method based on Bluetooth signals
CN113453148A (en) * 2021-06-25 2021-09-28 南通大学 Indoor position fingerprint positioning method combining deep learning and weighted K-neighbor algorithm
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