CN104573190B - A kind of method for tracking target based on interactive multi-model - Google Patents
A kind of method for tracking target based on interactive multi-model Download PDFInfo
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Abstract
The invention discloses a kind of method for tracking target based on interactive multi-model, including five steps：Step one, according to target dynamic condition, five groups of Singer model parameters are set, five Singer models are built；Five Singer models are interacted formula multi-model nonlinear filtering by step 2, estimate movement velocity, acceleration and the positional information of target；Step 3, using the movement velocity and acceleration of target, calculates target turning angular speed；Step 4, target turning angular speed and the threshold value of setting are compared, judges whether occur turning motion, if turning motion does not occur, regard the positional information obtained in step 2 as target following result；Step 5, in the event of turning motion, the turning angular speed for choosing three adjacent moments builds three Turn Models, interacts formula multi-model nonlinear filtering and obtain target location as target following result.The present invention has the advantages that easily realization, can improve target tracking accuracy, and guarantee is provided for the reliability and accuracy of target following.
Description
Technical field
The present invention relates to a kind of method for tracking target based on interactive multi-model, belong to target tracking domain.
Background technology
In target tracking domain, interactive multi-model (IMM) algorithm turns into a kind of widely used with its excellent performance
Target tracking algorism, it is estimated the model for covering goal behavior using several wave filters, interacted, integrated to obtain meeting and work as
The tracking result of preceding target dynamic.In interacting multiple model algorithm, the order of accuarcy of model influences very big to the result of tracking.
Turning motion is a kind of common motor-driven form of target following, and domestic and foreign scholars use Turn Models and carry out test machine
Tracking of maneuvering target algorithm.Turn Models are mainly modeled by turning angular speed, and the degree of accuracy of the turning angular speed of target motion is straight
Connect the modeling degree of accuracy of influence Turn Models.Therefore, effectively using Turn Models to target turn it is motor-driven be tracked, it is necessary to
The turning angular speed of target motion can be estimated in real time.
Singer models in existing method for tracking target are single order Markov Process Model, for target maneuver
Severe degree is modeled, therefore suitable for the tracking of various motor-driven situations.But, Singer models due to its versatility without
High-precision tracking can be realized.Realize the tracking of higher precision, it is desirable to which motion modeling is closer to real motion state.
Therefore, when the present invention occurs to turn motor-driven for target, being primarily based on five groups of Singer models, to interact formula more
Model nonlinear filtering estimation turning angular speed, and then model three-dimensional turn model to track the turning of target with turning angular speed
It is motor-driven, solve to carry out the practical sex chromosome mosaicism of maneuvering target tracking using Turn Models, improve target tracking accuracy.
The content of the invention
Goal of the invention：For problems of the prior art, the present invention provides a kind of mesh based on interactive multi-model
Tracking is marked, based on interacting multiple model filters framework, when turning motion occurs for target, by estimating the angle that target is moved
Speed, is efficiently used turning motion model and carries out target following, improve tracking accuracy.
Technical scheme：A kind of method for tracking target based on interactive multi-model, this method is filtered based on interactive multi-model
Ripple framework, first interacts formula filtering using five Singer models and obtains position, speed and acceleration information that target is moved,
Then turning angular speed is calculated, and judgement is compared with the threshold value of setting, is set if calculating obtained turning angular speed and being more than
Fixed threshold value, then judge that turning motion occurs for target, and interact with three Turn Models formula and filter and obtain tracking result；
Think that turning motion do not occur for target if the threshold value that the turning angular speed calculated is less than or equal to setting, and by five Singer
The location estimation that model interactive mode filtering is obtained is comprised the following steps that as tracking result：
Step 1) according to target dynamic condition, five groups of Singer model parameters are set, five groups of Singer models are built；
Step 2) interactive multi-model structure is based on, formula nonlinear filtering is interacted to five groups of Singer models, obtained
The estimated result of target, includes position, speed and the acceleration information of target；
Step 3) utilize step 2) obtained the tracking velocity V (k) and acceleration a (k) at k moment, calculating angle of turnAnd then calculate turning angular speed
Step 4) obtained turning angular speed and the threshold value Ω of setting will be calculated0It is compared, if Ω (k)>Ω0, then it is assumed that
Turning motion is there occurs, is gone to step 5)；If Ω (k)≤Ω0Then think that turning motion does not occur, by step 2) the obtained mesh of estimation
Cursor position information is used as tracking result；
Step 5) if it is determined that there occurs turning motion, then according to step 3) calculate continuous three moment (k, k-1, k-2)
Angular speed, build three three-dimensional turn models, estimated using interactive multi-model nonlinear filtering algorithm, tracked
As a result.
The Singer models concrete form is：
X (k+1)=diag [FS(αx),FS(αy),FS(αz)]X(k)+Wk (1)
Wherein,I=x, y, z, αiFor the time kept in reserve constant, τ in i directionsi
Inverse, αi=1/ τi, k is filtered time instant, and T is sampling time, WkFor system noise vector, system state variables be X (k)=
[Sx(k),Vx(k),Ax(k),Sy(k),Vy(k),Ay(k),Sz(k),Vz(k),Az(k)]T, Si(k) it is the position in i directions, Vi(k)
For the speed in i directions, Ai(k) it is the rate of acceleration in i directions.
The step 1) in five groups of Singer model parameters (αx, αy, αz) specific establishing method be：
11) first group of αx, αy, αzInterval be [1/50,1/100], corresponding to carrier in x, y, z yaw maneuvers
It is smaller or even without motor-driven situation；
12) second group of αx, αyInterval be [1/50,1/100], αzInterval be [1/5,1], correspond to
Carrier is motor-driven smaller on x, y directions or even without motor-driven；Motor-driven violent situation on z directions；
13) the 3rd group of αx, αyInterval be [1/5,1], αzInterval be [1/50,1/100], correspond to
Carrier is motor-driven violent on x, y directions；Smaller on z directions or even without motor-driven situation；
14) the 4th group of αx, αy, αzInterval be [1/5,1], corresponding to carrier in x, y, on z directions it is motor-driven acutely
Situation；
15) the 5th group is reinforcement group, αx, αyInterval be [1/20,1/5], αzInterval be [1/30,1/
50], carrier is motor-driven larger on x, y directions, and slow motor-driven situation is done in a z-direction.
The three-dimensional turn model concrete form is：
X (k+1)=diag [FCT(Ω),FCT(Ω),FCT(Ω)]X(k)+Wk (2)
Wherein,Ω is the turning angular speed of target, when k is filtering
Carve, T is sampling time, WkFor system noise vector, state vector is X (k)=[Sx(k),Vx(k),Ax(k),Sy(k),Vy(k),
Ay(k),Sz(k),Vz(k),Az(k)]T, Si(k) it is the position in i directions, Vi(k) it is the speed in i directions, Ai(k) adding for i directions
Speed, i=x, y, z.
The present invention uses step 3) the obtained turning angular speed of estimation as model parameter to step 5) three-dimensional turn mould
Type is modeled, and the turning that Turn Models tracking target is efficiently used is motor-driven, improves tracking accuracy.
The present invention uses above-mentioned technical proposal, has the advantages that：
(1) present invention is analyzed for the motor-driven situation of three dimensional maneuvering object, devises five groups of Singer model parameters
Scope, through interacting multiple model filters algorithm, so as to reach quick and relatively accurately track.
(2) when for target turning motion occurs for the present invention, by estimating the turning angular speed that solving target is moved, modeling
Turn Models, interact formula multiple model target tracking, so as to improve the precision of target following, strengthen and use Turn Models
Track the practicality of target.
Brief description of the drawings
Fig. 1 is algorithm flow chart of the invention；
Fig. 2 is the mathematical simulation target trajectory figure of the embodiment of the present invention；
Fig. 3 is the mathematical simulation target following error contrast schematic diagram of the embodiment of the present invention；
Fig. 4 is mathematical simulation target turning angle RATES's schematic diagram of the embodiment of the present invention；
Fig. 5 is the semi-physical simulation target trajectory figure of the embodiment of the present invention；
Fig. 6 is the semi-physical simulation target first paragraph tracking error contrast effect schematic diagram of the embodiment of the present invention；
Fig. 7 is the semi-physical simulation target second segment tracking error contrast effect schematic diagram of the embodiment of the present invention；
Fig. 8 is the 3rd section of tracking error contrast effect schematic diagram of semi-physical simulation target of the embodiment of the present invention.
Embodiment
With reference to specific embodiment, the present invention is furture elucidated, it should be understood that these embodiments are merely to illustrate the present invention
Rather than limitation the scope of the present invention, after the present invention has been read, various equivalences of the those skilled in the art to the present invention
The modification of form falls within the application appended claims limited range.
As shown in figure 1, the method for tracking target based on interactive multi-model of the present invention, designs five groups of Singer moulds first
Shape parameter, builds five Singer models, and estimation is interacted under interacting multiple model filters framework and obtains target motion
Position, speed and acceleration information；Then the turning angular speed of target is calculated, and is compared with the threshold value of setting and is judged, such as
The threshold value that obtained turning angular speed is more than setting is really calculated, then judges that turning motion occurs for target, and with three Turn Models
The formula multiple model filtering of interacting obtains tracking result；Think if the threshold value that the turning angular speed calculated is less than or equal to setting
Turning motion does not occur for target, and the location estimation that five Singer models interactive mode filtering are obtained is used as tracking result.
Table 1 is five groups of Singer model parameter examples of selection.
Table 1Singer model parameters
| Group | αx | αy | αz |
| 1 | 1/60 | 1/60 | 1/60 |
| 2 | 1/60 | 1/60 | 1 |
| 3 | 1 | 1 | 1/60 |
| 4 | 1 | 1 | 1 |
| 5 | 1/10 | 1/10 | 1/40 |
For the feasibility of the checking present invention, mathematical simulation and half thing based on measured data have been carried out under Matlab environment
Reason experiment, sampling time T=1s, turning angle rate-valve value Ω0=0.01rad/s, the nonlinear filter of interactive multi-model
From Gauss orthogonal integration point Kalman filtering.X is chosen, there is measurement equation Z (k) y, the position in tri- directions of z as measurement
=HX (k)+v (k), wherein v (k) are measurement noise vector,To measure square
Battle array, measures noise criteria difference σ=10m.
The initial state vector of wave filter is X (0)=[20,10,0,10,0,0.3,10,0,0.4]T；
Observation noise variance matrix is R=diag [σ2σ2σ2]；
Initial error variance matrix P0=diag [p p p]
The system noise variance matrix Q of Singer modelsSinger=diag [qSinger qSinger qSinger]
The system noise variance matrix Q of Turn ModelsCT(Ω)=diag [qCT(Ω) qCT(Ω) qCT(Ω)]
Mathematical simulation kinematic parameter sets as follows, and the common 180s of simulation time, motion of the target under three-dimensional situation is divided into three
Section：(1) with 0.05rad/s turning angle rate turn 60s；(2) linear uniform motion 60s；(3) with 0.14rad/s turning
Angular speed turning 60s；Initial position is [Sx(0),Sy(0),Sz(0)]=[20,10,10] m；Initial velocity is [Vx(0),Vy
(0),Vz(0)]=[10,10,0] m/s；Movement locus is as shown in Figure 2.
The site error curve of tracking result on tri- directions of x, y, z is as shown in figure 3, IMM1 solid line is represented by the uniform velocity
The tracking result for the interactive multi-model that motion model (CV), uniformly accelerated motion model (CA) and Turn Models (CT) are constituted；
IMM2 dotted line represents the tracking result for the interactive multi-model being made up of five groups of Singer models of step 2；IMM3 dotted line
Represent the tracking result for the interactive multi-model being made up of three groups of Turn Models of step 5.As seen from Figure 5, in preceding 60s and
Afterwards during 60s turning motions, IMM3 tracking effect is better than being better than with IMM2 and IMM1 tracking effect, IMM2 tracking effect
IMM1 tracking effect.And it is more violent to turn, IMM3 superiority more can be highlighted.Fig. 4 further illustrates the inventive method
Validity, Fig. 4 Point Sets are turning angular speed true value, and solid line is the turning angular speed calculated by IMM1 algorithms, and dotted line is logical
The turning angular speed of IMM2 algorithms calculating is crossed, dotted line is the turning angular speed that IMM3 algorithms are calculated, it can be seen that turned
The angular speed that the preceding 60s and rear 60s, IMM3 of motion are calculated is closest to true turning angular speed, next to that the turning that IMM2 is calculated
Angular speed.
The movement locus of semi physical experiment is as shown in Figure 5.In the experiment of this semi physical, target moves to B points from A points, motion
Situation is complex, includes the motion for decline of turning and spiral.In order to clear contrast IMM1, IMM2 and IMM3 algorithms with
Track effect, with Fig. 6, Fig. 7 and Fig. 8 time segments represent the error curve of tracking result.In 470s~800s time intervals, mesh
Mark does that flat bank is motor-driven, x to y to motor-driven larger this section of tracking result in, clear superiorities of the IMM3 relative to IMM1,
IMM3 reduces dispersion compared to IMM2；In 1100s~1600s time intervals, target is done declines machine more than 360o curve
It is dynamic, IMM3 x to, y to and z to error be all it is minimum, it is the most obvious to effect with y；In 1700s~1850s is interval,
Straight line declines after target obtuse angle is turned, wherein, interval in 1700s~1780s, target does obtuse angle turning, x to y to it is motor-driven compared with
Greatly, 1780s~1850s straight lines decline stage, y to z to it is motor-driven larger, interval herein, IMM3 tracking effects are superior to
IMM2 and IMM1 tracking effect.It can be seen that, Fig. 6~Fig. 8 is verified when target occurs motor-driven under the conditions of semi-physical simulation,
The tracking effect of IMM3 algorithms is better than IMM2 and IMM1, and IMM2 tracking effect is better than IMM1.
As fully visible, the present invention carries a kind of method for tracking target of interactive multi-model so that in motor-driven generation of turning
When, Turn Models can be effectively used, tracking accuracy is improved.
Claims (3)
1. a kind of method for tracking target based on interactive multi-model, it is characterised in that comprise the following steps：
Step 1) according to target dynamic condition, five groups of Singer model parameters are set, five groups of Singer models are built；Wherein, five
The specific establishing method of group Singer model parameters is as follows：
11) first group of αx, αy, αzInterval be [1/50,1/100], corresponding to carrier in x, y, z yaw maneuvers are smaller
Even without motor-driven situation；
12) second group of αx, αyInterval be [1/50,1/100], αzInterval be [1/5,1], corresponding to carrier
It is motor-driven smaller or even without motor-driven on x, y directions；Motor-driven violent situation on z directions；
13) the 3rd group of αx, αyInterval be [1/5,1], αzInterval be [1/50,1/100], corresponding to carrier
It is motor-driven violent on x, y directions；Smaller on z directions or even without motor-driven situation；
14) the 4th group of αx, αy, αzInterval be [1/5,1], corresponding to carrier in x, y, motor-driven violent feelings on z directions
Condition；
15) the 5th group is reinforcement group, αx, αyInterval be [1/20,1/5], αzInterval be [1/30,1/50], carry
Body is motor-driven larger on x, y directions, and slow motor-driven situation is done in a z-direction；
Step 2) interactive multi-model structure is based on, five groups of Singer models are interacted with formula nonlinear filtering, target is obtained
Estimated result, include position, speed and the acceleration information of target；
Step 3) utilize step 2) obtained the tracking velocity V (k) and acceleration a (k) at k moment, the angle of turn at calculating k momentAnd then calculate the turning angular speed at k moment
Step 4) obtained turning angular speed and the threshold value Ω of setting will be calculated0It is compared, if Ω (k)>Ω0, then it is assumed that occur
5) turning motion, go to step；If Ω (k)≤Ω0Then think that turning motion does not occur, by step 2) estimation obtain target position
Confidence breath is used as tracking result；
Step 5) if it is determined that there occurs turning motion, then according to step 3) calculate the angle speed at continuous three moment k, k-1 and k-2
Rate, build three three-dimensional turn models, using interactive multi-model nonlinear filtering algorithm carry out target state estimator, obtain target with
Track result.
2. the method for tracking target according to claim 1 based on interactive multi-model, it is characterised in that the Singer
Model concrete form is：
X (k+1)=diag [FS(αx),FS(αy),FS(αz)]X(k)+Wk (1)
Wherein,I=x, y, z, αiFor the time kept in reserve constant, τ in i directionsiFall
Number, αi=1/ τi, k is filtered time instant, and T is sampling time, WkFor system noise vector, system state variables is X (k)=[Sx
(k),Vx(k),Ax(k),Sy(k),Vy(k),Ay(k),Sz(k),Vz(k),Az(k)]T, Si(k) it is the position in i directions, Vi(k) it is i
The speed in direction, Ai(k) it is the rate of acceleration in i directions.
3. the method for tracking target according to claim 1 based on interactive multi-model, it is characterised in that described three-dimensional turn
Curved model concrete form is as follows：
X (k+1)=diag [FCT(Ω),FCT(Ω),FCT(Ω)]X(k)+Wk (2)
Wherein,Ω is the turning angular speed of target, and k is filtered time instant, and T is
Sampling time, WkFor system noise vector, state vector is X (k)=[Sx(k),Vx(k),Ax(k),Sy(k),Vy(k),Ay(k),
Sz(k),Vz(k),Az(k)]T, Si(k) it is the position in i directions, Vi(k) it is the speed in i directions, Ai(k) it is the rate of acceleration in i directions,
I=x, y, z.
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| CN105184027B (en) * | 2015-10-29 | 2018-04-06 | 山东大学 | A kind of power load modelling approach based on interacting multiple model algorithm |
| CN106168943A (en) * | 2016-07-12 | 2016-11-30 | 深圳大学 | A kind of method for following the tracks of turning machine moving-target and system thereof |
| CN106210484A (en) * | 2016-08-31 | 2016-12-07 | 上海鹰觉科技有限公司 | Waters surveillance polynary associating sensing device and cognitive method thereof |
| CN107289968B (en) * | 2017-06-23 | 2018-12-21 | 深圳大学 | A kind of method for estimating state and device of maneuvering target of turning |
| WO2018232740A1 (en) * | 2017-06-23 | 2018-12-27 | 深圳大学 | State estimation method and device for target performing turn maneuver |
| CN107390631B (en) * | 2017-07-14 | 2019-08-09 | 深圳大学 | A kind of track initial method and system for maneuvering target of turning |
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