CN111983601B - Group target tracking track starting method based on Bayesian principle - Google Patents

Group target tracking track starting method based on Bayesian principle Download PDF

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CN111983601B
CN111983601B CN202010693946.6A CN202010693946A CN111983601B CN 111983601 B CN111983601 B CN 111983601B CN 202010693946 A CN202010693946 A CN 202010693946A CN 111983601 B CN111983601 B CN 111983601B
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CN111983601A (en
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王锐
姜琦
胡程
周超
龙腾
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Beijing Institute of Technology BIT
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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
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/66—Radar-tracking systems; Analogous systems
    • 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
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/66—Radar-tracking systems; Analogous systems
    • G01S13/70—Radar-tracking systems; Analogous systems for range tracking only
    • 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
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
    • G01S7/411—Identification of targets based on measurements of radar reflectivity
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    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
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Abstract

A group target tracking track starting method based on Bayesian principle, which introduces information of the number of targets in a subgroup to describe a likelihood ratio expression, increases the utilization of characteristic information of the group target, and improves track starting efficiency aiming at a dense group target, especially under the condition of dense distribution; meanwhile, the likelihood ratio expression of the invention adopts Poisson distribution to describe the probability density of the target distribution condition in the group under the condition that the track is true, thereby avoiding the problem of overlarge residual error between an extrapolated value and an actual measured value caused by the jump phenomenon of equivalent measurement in the traditional track starting method and improving the robustness of the algorithm.

Description

Group target tracking track starting method based on Bayesian principle
Technical Field
The invention belongs to the technical field of radars, and particularly relates to a group target track tracking starting method based on a Bayesian principle.
Background
Group target tracking first performs group detection and group track initiation. After the grouping detection, calculating the equivalent measurement of each subgroup respectively, and judging whether the flight path is true or not by using the equivalent measurement of continuous multi-frame data. The existing group target track starting technology generally extrapolates according to equivalent measured data of a current frame, and judges whether the association is successful or not by utilizing the relation between the equivalent measured data of the next frame and an extrapolated value; once the association is successful, the common criteria for judging the track initiation include typical single-target track initiation methods such as a Bayesian criterion, an M/N criterion, a correction logic method and the like. For example, extrapolation is used as a center, the size of a correlation wave gate is specified according to the covariance of the track extrapolation error, a new equivalent measurement point falling into the wave gate is associated with an extrapolation point, and the track start is judged by using a correction logic method. However, the prior art is only suitable for a group target tracking scene with sparse target distribution and high radar resolution, when targets in a group are densely distributed, the radar has uncertain echo fluctuation due to limited resolution, view shielding between targets, multipath effect and the like, the equivalent measurement has a jump phenomenon in a certain range, the residual between an extrapolated value and an actual measured value is too large, the association probability is reduced, the track starting efficiency is reduced, and even the situation of mistaken track discarding occurs. On the other hand, the existing group target track initiation technology only uses equivalent measured state information for calculation, and has no substantial difference from the traditional single target track initiation, and the utilization of group target characteristic information (such as the number of traces of points in a subgroup) is not sufficient, so that the further improvement of performance is restricted.
Disclosure of Invention
In order to solve the problems, the invention provides a group target tracking track starting method based on the Bayesian principle, which makes full use of group target information, introduces Poisson distribution to construct a likelihood ratio expression, describes the probability density of the distribution condition of targets in a group under the condition that the track is true, improves the track starting efficiency aiming at the group target, and solves the problem of overlarge residual error caused by non-ideal measurement.
A group target tracking track starting method based on Bayesian principle comprises the following steps:
after pulse compression, constant false alarm detection and grouping processing are carried out on radar echoes, a group of target measurement sets of each subgroup in a scanning space at the t-th moment are obtained, and then each subgroup is respectively used as a current subgroup Z 0 Executing a track initial judgment operation, wherein the track initial judgment operation is as follows:
s1: according to the current subgroup Z 0 Target measurement set obtaining current subgroup Z 0 Equivalent measurement value of (m) 0 And a prediction correlation gate, wherein the prediction correlation gate is the current subgroup Z 0 A range of possible positions at the next time;
s2: re-receiving radar echo, and then obtaining a group of target measurement sets Z of each subgroup in the scanning space at the t +1 th moment according to the re-received radar echo 1 And an equivalent measure m for each subgroup 1 ；
S3: judging whether the time t +1 has the time falling into the current subgroup Z 0 Is measured m of the equivalent of the predictive correlation gate 1 If it exists, it falls into the current subgroup Z 0 Each equivalent measurement m of the predictive correlation gate of (2) 1 Proceeding to step S4; if not, go to step S5;
s4: will fall into the current subgroup Z respectively 0 Each equivalent measurement m of the predictive correlation gate of (2) 1 The corresponding subgroup as an alternative subgroup performs the following steps:
s41: obtaining alternative subgroup relative to current subgroup Z 0 Likelihood ratio L of 1 (D 1 )：
Figure BDA0002590356800000021
Where μ is a set coefficient related to the density of the target within the candidate subgroup, V 1 Volume of alternative sub-population, beta F To set false alarm probability density, n 1 Number of targets included for alternative subgroups! Is a factorial;
s42: based on Bayes principle, according to likelihood ratio L 1 (D 1 ) Calculating posterior probability P (T | D) of current subgroup belonging to true track 1 )；
S43: judging posterior probability P (T | D) 1 ) Whether the track is larger than a set track starting threshold gamma T Or less than a set track discard threshold gamma F Wherein, if it is larger than the track starting threshold gamma T If the current subgroup is the starting point of the track, and ending the track start of the group target tracking; if the number is less than the track discarding threshold gamma F If the current subgroup is not the starting point of the track, ending the track start of target tracking; if posterior probability P (T | D) 1 ) Between track start threshold gamma T And track discard threshold gamma F Step S44 is then entered;
s44: equivalent metric m from alternative subgroups 1 Calculating an equivalent measurement predicted value m 'at the t +2 th moment' 2 ：
m′ 2 ＝m 1 +Δ 1 ×Δt
Wherein, Delta 1 Equivalent measurement difference between the alternative subgroup at the t +1 th moment and the current subgroup at the t-th moment, wherein delta t is a sampling time interval;
s45: using equivalent measurement to predict value m' 2 As the center, equivalent measurement predicted value m' 2 The possible deviation range between the candidate subgroup and the corresponding true value is a radius, a prediction correlation gate of the candidate subgroup at the t +2 th moment is obtained, and then the step S46 is executed;
s46: re-receiving radar echo, and then obtaining a group of target measurement sets Z of each subgroup in the scanning space at the t +2 th moment according to the re-received radar echo 2 And an equivalent measure m for each subgroup 2 ；
S47: it is determined whether or not there is an equivalent measurement m of the predicted correlation gate falling into the candidate subgroup obtained in step S45 at the t +2 th time 2 If there are, the equivalent measures m of the predicted correlation gates falling into the candidate subgroups obtained in step S45 are respectively measured 2 And repeating the steps S41-S43 as a new candidate subgroup to judge whether the current subgroup is the starting point of the track, wherein if the current subgroup is judged to be the starting point of the track, the track starting of the group target tracking is ended, and if the current subgroup cannot be judged to be the starting point of the track, the steps S44-S47 are repeated, and the equivalent measurement m of each subgroup at the t +3 moment is used for measuring the equivalent value m 3 Judging whether the current subgroup is the starting point of the track; repeating the steps until judging whether the current subgroup is the starting point of the track, and ending the track starting of the target tracking; if not, go to step S5;
s5: and executing the following steps by taking the subgroups corresponding to the equivalent measurement entering the step as candidate subgroups respectively:
s51: calculating the relative of the candidate subgroup to the current subgroup Z 0 Likelihood ratio J of 1 (D 1 )：
Figure BDA0002590356800000041
Wherein, P D Is a priori detection probability, P, of the radar sensor F Probability of false alarm/clutter occurrence;
s52: based on Bayes principle, according to likelihood ratio J 1 (D 1 ) Calculating the current subgroup Z 0 Posterior probability P of true track 1 (T|D 1 )；
S53: the posterior probability P (T | D) obtained in step S52 is used 1 ) Instead of the posterior probability P (T | D) obtained in step S42 1 ) Replacing the candidate subgroup with the candidate subgroup, and then repeating the steps S43-S45 to obtain a predicted correlation gate at the next time corresponding to the candidate subgroup;
s54: re-receiving the radar echo, and then obtaining a group of target measurement sets of each subgroup in the scanning space at the next moment and equivalent measurement of each subgroup according to the re-received radar echo;
s6: respectively replacing the predicted correlation gate, the equivalent measurement and the candidate subgroup obtained in the step S47 with the predicted correlation gate, the equivalent measurement and the candidate subgroup obtained in the step S54 obtained in the step S53, and then repeating the step S47 to determine whether the current subgroup is a starting point of the track; and repeating the steps until judging whether the current subgroup is the starting point of the track, and ending the track starting of the target tracking.
Further, the current subgroup Z 0 Equivalent measured value m 0 The method for acquiring the door associated with the prediction comprises the following steps:
s11: calculating an equivalent measured value m of the current subgroup 0 ：
Figure BDA0002590356800000042
Wherein the target metric set of the current subgroup is denoted as
Figure BDA0002590356800000051
Is the state vector of the ith target in the current subgroup at the t-th moment, and the state vector includes the position, speed and acceleration of the target, i ═ 1, 2 0 ，n 0 The target number of the current subgroup contained at the tth moment;
s12: and predicting the position of the current subgroup which possibly appears at the next moment according to the speed upper limit value, the acceleration upper limit value, the average position and the sampling time interval of each target in the current subgroup to obtain a predicted correlation gate.
Further, the posterior probability P (T | D) of step S42 1 ) The calculation method comprises the following steps:
Figure BDA0002590356800000052
wherein, P (T | D) 1 ) The preset prior probability that the current subgroup belongs to the real track.
Further, the posterior probability P of step S52 1 (T|D 1 ) The calculating method comprises the following steps:
Figure BDA0002590356800000053
wherein, P (T | D) 0 ) Is the set prior probability that the current subgroup belongs to the true track.
Has the advantages that:
a group target tracking track initiation method based on Bayesian principle, which introduces information of the number of targets in a subgroup to describe a likelihood ratio expression, increases the utilization of characteristic information of the group target, and improves track initiation efficiency aiming at dense group targets, especially under dense distribution; meanwhile, the likelihood ratio expression of the invention adopts Poisson distribution to describe the probability density of the target distribution condition in the group under the condition that the track is true, thereby avoiding the problem of overlarge residual error between an extrapolated value and an actual measured value caused by the jump phenomenon of equivalent measurement in the traditional track starting method and improving the robustness of the algorithm.
Drawings
FIG. 1 is a flowchart of a group target tracking track initiation method based on Bayesian principle according to the present invention;
FIG. 2 is a schematic diagram of a group target volume and a radar beam volume provided by the present invention;
FIG. 3 is a schematic diagram of a starting result of tracking a track of a group target according to the present invention.
Detailed Description
In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application.
Example one
A group target tracking track starting method based on Bayesian principle comprises the following steps:
as shown in fig. 1, after pulse compression, constant false alarm detection, and clustering are performed on radar echoes, a group of target measurement sets of each subgroup in a scanning space at a t-th time is obtained, and then each subgroup is used as a current subgroup to perform a track start judgment operation, where the track start judgment operation is:
s1: according to the current subgroup Z 0 Target measurement set obtaining current subgroup Z 0 Equivalent measured value m 0 And a prediction correlation gate, wherein the prediction correlation gate is the current subgroup Z 0 A range of possible positions at the next time;
s11: calculating an equivalent measured value m of the current subgroup 0 ：
Figure BDA0002590356800000061
Wherein the target metric set of the current subgroup is denoted as
Figure BDA0002590356800000062
Is the state vector of the ith target in the current subgroup at the t-th moment, and the state vector includes the position, speed and acceleration of the target, i ═ 1, 2 0 ，n 0 The target number contained in the current subgroup at the t moment;
s12: predicting the position of the current subgroup which possibly appears at the next moment according to the speed upper limit value, the acceleration upper limit value, the average position and the sampling time interval of each target in the current subgroup to obtain a predicted correlation gate;
s2: re-receiving radar echo, and obtaining a group of targets of each subgroup in the scanning space at the t +1 th moment according to the re-received radar echoSet of scalar quantities Z 1 And an equivalent measure m for each subgroup 1 ；
That is, the step re-receives the radar echo and performs pulse compression, constant false alarm detection and clustering processing on the radar echo to obtain a group of target measurement sets of each subgroup in the scanning space at the t +1 th moment
Figure BDA0002590356800000071
Wherein n is 1 The target number contained in each subgroup obtained at the t +1 th moment, and then the equivalent measurement m of each subgroup obtained at the t +1 th moment is calculated according to the formula (1) 1 (ii) a It should be noted that the number of targets included in each subgroup obtained at the t +1 th time may be the same or different, and n may be n 1 It is only generalized to the target number contained in each subgroup obtained at time t +1, i.e. n is for different subgroups 1 Different values are available;
s3: judging whether the time t +1 has the time falling into the current subgroup Z 0 Is measured m of the equivalent of the predictive correlation gate 1 If it exists, it falls into the current subgroup Z 0 Each equivalent measurement m of the predictive correlation gate of 1 Proceeding to step S4; if not, go to step S5;
s4: will fall into the current subgroup Z respectively 0 Each equivalent measurement m of the predictive correlation gate of (2) 1 The corresponding subgroup as an alternative subgroup performs the following steps:
s41: obtaining alternative subgroup relative to current subgroup Z 0 Likelihood ratio L of 1 (D 1 )：
Figure BDA0002590356800000072
Where μ is a set coefficient related to the density of the target within the candidate subgroup, V 1 Is the volume of the alternative subgroup, and the volume of the alternative subgroup is determined by the area enclosed by the objects located at the outermost periphery, beta F For a set false alarm probability density, n 1 Number of targets included for alternative subgroups! Is a factorial;
s42: calculating posterior probability P (T | D) of current subgroup belonging to real track based on Bayes principle l )：
Figure BDA0002590356800000073
Wherein, P (T | D) 0 ) Setting prior probability that the current subgroup belongs to a real track;
s43: judging posterior probability P (T | D) 1 ) Whether the track is larger than a set track starting threshold gamma or not T Or less than a set track discard threshold gamma F Wherein, if it is larger than the track starting threshold gamma T If the current subgroup is the starting point of the track, ending the track starting of the group target tracking; if the number is less than the track discarding threshold gamma F If the current subgroup is not the starting point of the track, ending the track start of target tracking; if posterior probability P (T | D) 1 ) Between track start threshold gamma T And track discard threshold gamma F Otherwise, go to step S44;
s44: equivalent metric m according to alternative subgroup 1 Calculating an equivalent measurement predicted value m 'at the t +2 moment' 2 ：
m′ 2 ＝m 1 +Δ 1 ×Δt (4)
Wherein, Delta 1 Equivalent measurement difference between the alternative subgroup at the t +1 th moment and the current subgroup at the t th moment, wherein delta t is a sampling time interval;
s45: using equivalent measurement to predict value m' 2 As the center, equivalent measurement predicted value m' 2 The possible deviation range between the actual value and the corresponding actual value is a radius, the range of the prediction correlation gate of the alternative subgroup at the t +2 th moment is obtained, and then the step S46 is carried out;
s46: re-receiving radar echo, and then obtaining a group of target measurement sets Z of each subgroup in the scanning space at the t +2 th moment according to the re-received radar echo 2 And an equivalent measure m for each subgroup 2 ；
That is, this step re-receives the radar echo andafter pulse compression, constant false alarm rate detection and grouping processing are carried out on the radar echo, a group of target measurement sets of each subgroup in the scanning space at the t +2 th moment are obtained
Figure BDA0002590356800000081
Wherein n is 2 The target number contained in each subgroup obtained at the t +2 th moment, and then the equivalent measurement m of each subgroup obtained at the t +2 th moment is calculated according to the formula (1) 2 (ii) a It should be noted that the number of targets included in each subgroup obtained at the t +2 th time may be the same or different, and n is 2 It is only generalized to the target number contained in each subgroup obtained at time t +2, i.e. n is for different subgroups 2 Different values are available;
s47: it is determined whether or not there is an equivalent measurement m of the predicted correlation gate of the candidate subgroup obtained in step S45 at the t +2 th time 2 If there are, the equivalent measures m of the predicted correlation gates falling into the candidate subgroups obtained in step S45 are respectively measured 2 And repeating the steps S41-S43 as a new alternative subgroup to judge whether the current subgroup is the starting point of the track, wherein if the current subgroup is judged to be the starting point of the track, the track starting of the group target tracking is ended, and if the current subgroup cannot be judged to be the starting point of the track, the steps S44-S47 are repeated continuously, and according to the equivalent measurement m of each subgroup at the t +3 moment 3 Judging whether the current subgroup is the starting point of the track; repeating the steps until judging whether the current subgroup is the starting point of the track, and ending the track starting of the target tracking; if not, go to step S5;
s5: and executing the following steps by taking the subgroups corresponding to the equivalent measurement entering the step as candidate subgroups respectively:
s51: calculating the relative of the candidate subgroup to the current subgroup Z 0 Likelihood ratio J of 1 (D 1 )：
Figure BDA0002590356800000091
Wherein, P D Is the prior detection probability, P, of the radar sensor F Probability of false alarm/clutter occurrence;
s52: according to likelihood ratio J 1 (D 1 ) Calculating the current subgroup Z 0 Posterior probability P of true track 1 (T|D 1 )：
Figure BDA0002590356800000092
S53: the posterior probability P (T | D) obtained in step S52 is used 1 ) Instead of the posterior probability P (T | D) obtained in step S42 1 ) Replacing the candidate subgroup with the candidate subgroup, and then repeating the steps S43-S45 to obtain a predicted correlation gate at the next time corresponding to the candidate subgroup;
s54: re-receiving the radar echo, and then obtaining a group of target measurement sets of each subgroup in the scanning space at the next moment and equivalent measurement of each subgroup according to the re-received radar echo;
that is, the step receives the radar echo again, and performs pulse compression, constant false alarm detection and grouping processing on the radar echo to obtain a group of target measurement sets of each subgroup in the scanning space at the next moment, and then calculates the equivalent measurement of each subgroup obtained at the next moment;
s6: respectively replacing the predicted correlation gate, the equivalent measurement and the candidate subgroup obtained in the step S47 with the predicted correlation gate, the equivalent measurement and the candidate subgroup obtained in the step S54 obtained in the step S53, and then repeating the step S47 to determine whether the current subgroup is a starting point of the track; and repeating the steps until judging whether the current subgroup is the starting point of the track, and ending the track starting of the target tracking.
Example two
Based on the above embodiments, the present embodiment further describes a group target track initiation method by taking a group target as a bird group as an example, and specifically includes the following steps:
step 1, observing a bird group target by using a high-resolution radar only containing distance information; 785MHz distance of high resolution radar bandwidthThe resolution power DeltaR/2B is 0.19m, wherein c is the speed of light; the radar beam width is 1.5 degrees, and the sampling interval is delta t which is 40 ms; after pulse compression and constant false alarm detection are carried out on data after scanning, two equivalent measurements are obtained at 157.8s (marked as 1 st sampling moment), namely 250.1m and 253.2m of distance radar respectively and marked as
Figure BDA0002590356800000101
And
Figure BDA0002590356800000102
the equivalent measurement obtained by calculation is
Figure BDA0002590356800000103
Figure BDA0002590356800000104
Since the equivalent measurements cannot be correlated with any existing group targets, the equivalent measurements are recorded as pre-starting track points, and the prior probability that the track is true is denoted as P 0 (T) ═ 0.3; the predicted state m 'at the next time is the 1 st equivalent measurement point' 1 The current equivalent measurement state is obtained; according to the bird characteristics, the maximum flight speed of the bird is generally not more than 30m/s, and the displacement variation range after 1 sampling interval is +/-1.2 m, so that the displacement variation range is used as the correlation gate range at the next moment;
step 2. the radar receives 3 measuring points at the 2 nd sampling moment:
Figure BDA0002590356800000105
Figure BDA0002590356800000106
calculating equivalent measure points
Figure BDA0002590356800000107
Figure BDA0002590356800000111
Difference from predicted state Δ ═ m' 1 -m 1 The association is successful if 0.1 is less than 1.2;
step 3, calculating a likelihood ratio expression beta according to the target number and the group product in the group at the current moment F ＝5×10 -5 ，μ＝5×10 -4 (ii) a Since the radar has only distance information, the present embodiment uses the beam volume occupied by the group target at the current time as the group target volume at the current time, as shown in fig. 2; calculating likelihood ratio to obtain L 1 (D 1 )＝5.7136；
Step 4, calculating a result L by using the likelihood ratio 1 (D 1 ) Calculating the posterior probability of true track according to Bayes principle, and solving to obtain P (T | D) 1 ) 0.7100; this embodiment sets the posterior probability to be greater than γ T When the value is 0.95, the flight path is judged to be true, and when the posterior probability is less than gamma F When the track is 0.05, judging the track to be false; existing P (T | D) 1 ) Between gamma and T and gamma F And extrapolating the equivalent measurement state at the next moment by taking the current equivalent measurement point as the center: m' 2 ＝251.5；
And 5, receiving 3 measuring points by the radar at the 3 rd sampling moment:
Figure BDA0002590356800000112
Figure BDA0002590356800000113
calculating equivalent measure points
Figure BDA0002590356800000114
251.6m, and the difference Δ ═ m 'from the predicted state' 2 -m 2 The association is successful if 0.1 is less than 1.2; repeating the processing in step 3 and step 4 to obtain a likelihood ratio L 2 (D 2 ) 5.7263, the posterior probability P (T | D) that the track is true 2 ) 0.9334, based on γ T And gamma F Extrapolating the equivalent measuring state at the next moment by taking the current equivalent measuring point as the center: m' 3 ＝251.6；
Step 6, the radar receives 3 measuring points at the 4 th sampling moment:
Figure BDA0002590356800000115
Figure BDA0002590356800000116
calculating equivalent measure points
Figure BDA0002590356800000117
Difference delta m 'from predicted state' 3 -m 3 The association is successful if the | -0.1 is less than 1.2; repeating the processing in step 3 and step 4 to obtain a likelihood ratio L 3 (D 3 ) 5.7103, the posterior probability P (T | D) that the track is true 3 ) 0.9877, the threshold γ is exceeded T And judging the track start.
The flow of the whole embodiment is shown in fig. 3, wherein a solid dot represents a measuring point trace, a star point represents equivalent measurement obtained by calculation, a number above the equivalent measurement represents the probability that the track is true, and a dashed circle represents a subgroup range; therefore, the track starting method provided by the embodiment can quickly start the real track and can meet the requirements in practical application.
The present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof, and it will be understood by those skilled in the art that various changes and modifications may be made herein without departing from the spirit and scope of the invention as defined in the appended claims.

Claims (4)

1. A group target tracking track starting method based on Bayesian principle is characterized by comprising the following steps:
after pulse compression, constant false alarm detection and grouping processing are carried out on radar echoes, a group of target measurement sets of each subgroup in a scanning space at the t-th moment are obtained, and then each subgroup is respectively used as a current subgroup Z 0 Executing a track initial judgment operation, wherein the track initial judgment operation is as follows:
s1: according to the current subgroup Z 0 Target measurement set obtaining current subgroup Z 0 Equivalent measured value m 0 And a prediction correlation gate, wherein the prediction correlation gate is the current subgroup Z 0 A range of possible positions at the next time;
s2: re-receiving the radar echo, and then obtaining a group of target measurement sets Z of each subgroup in the scanning space at the t +1 th moment according to the re-received radar echo 1 And equivalent measure m for each subgroup 1 ；
S3: judging whether the current subgroup Z exists at the t +1 th moment 0 Is measured m of the equivalent of the predictive correlation gate 1 If it exists, it falls into the current subgroup Z 0 Each equivalent measurement m of the predictive correlation gate of 1 Proceeding to step S4; if not, go to step S5;
s4: will fall into the current subgroup Z respectively 0 Each equivalent measurement m of the predictive correlation gate of 1 The corresponding subgroup as an alternative subgroup performs the following steps:
s41: obtaining alternative subgroup relative to current subgroup Z 0 Likelihood ratio L of 1 (D 1 )：
Figure FDA0002590356790000011
Where μ is a set coefficient related to the density of the target within the candidate subgroup, V 1 Volume of alternative sub-population, beta F For a set false alarm probability density, n 1 Number of targets included for alternative subgroups! Is a factorial;
s42: based on Bayes principle, according to likelihood ratio L 1 (D 1 ) Calculating posterior probability P (T | D) of current subgroup belonging to true track 1 )；
S43: judging posterior probability P (T | D) 1 ) Whether the track is larger than a set track starting threshold gamma or not T Or less than a set track discard threshold gamma F Wherein, if it is larger than the track initial threshold gamma T If the current subgroup is the starting point of the track, ending the track starting of the group target tracking; if the number is less than the track discarding threshold gamma F If the current subgroup is not the starting point of the track, ending the track start of target tracking; if the posterior probability P (T | D) 1 ) Between track start threshold gamma T With track discard threshold gamma F BetweenThen, go to step S44;
s44: equivalent metric m according to alternative subgroup 1 Calculating an equivalent measurement predicted value m 'at the t +2 th moment' 2 ：
m′ 2 ＝m 1 +Δ 1 ×Δt
Wherein, Delta 1 Equivalent measurement difference between the alternative subgroup at the t +1 th moment and the current subgroup at the t th moment, wherein delta t is a sampling time interval;
s45: predicting m 'by equivalent measurement' 2 As the center, equivalent measurement predicted value m' 2 The possible deviation range between the actual value and the corresponding actual value is a radius, a prediction correlation gate of the alternative subgroup at the t +2 th moment is obtained, and then the step S46 is carried out;
s46: re-receiving radar echo, and then obtaining a group of target measurement sets Z of each subgroup in the scanning space at the t +2 th moment according to the re-received radar echo 2 And equivalent measure m for each subgroup 2 ；
S47: it is determined whether or not there is an equivalent measurement m of the predicted correlation gate of the candidate subgroup obtained in step S45 at the t +2 th time 2 If there are, the equivalent measurement m of the gate associated with the prediction of the candidate subgroup obtained in step S45 is individually set 2 And repeating the steps S41-S43 as a new alternative subgroup to judge whether the current subgroup is the starting point of the track, wherein if the current subgroup is judged to be the starting point of the track, the track starting of the group target tracking is ended, and if the current subgroup cannot be judged to be the starting point of the track, the steps S44-S47 are repeated continuously, and according to the equivalent measurement m of each subgroup at the t +3 moment 3 Judging whether the current subgroup is the starting point of the track; repeating the steps until judging whether the current subgroup is the starting point of the track, and ending the track starting of the target tracking; if not, go to step S5;
s5: and executing the following steps by taking the subgroups corresponding to the equivalent measurement entering the step as candidate subgroups respectively:
s51: calculating the relative of the candidate subgroup to the current subgroup Z 0 Likelihood ratio J of 1 (D 1 )：
Figure FDA0002590356790000031
Wherein, P D Is a priori detection probability, P, of the radar sensor F Probability of false alarm/clutter occurrence;
s52: based on Bayes principle, according to likelihood ratio J 1 (D 1 ) Calculating the current subgroup Z 0 Posterior probability P of true flight path 1 (T|D 1 )；
S53: the posterior probability P (T | D) obtained in step S52 is used 1 ) Instead of the posterior probability P (T | D) obtained in step S42 1 ) Replacing the candidate subgroup with the candidate subgroup, and then repeating the steps S43-S45 to obtain a predicted correlation gate at the next time corresponding to the candidate subgroup;
s54: re-receiving the radar echo, and then obtaining a group of target measurement sets of each subgroup in the scanning space at the next moment and equivalent measurement of each subgroup according to the re-received radar echo;
s6: respectively replacing the predicted correlation gate, the equivalent measurement and the candidate subgroup obtained in the step S47 with the predicted correlation gate, the equivalent measurement and the candidate subgroup obtained in the step S54 obtained in the step S53, and then repeating the step S47 to determine whether the current subgroup is a starting point of the track; and repeating the steps until judging whether the current subgroup is the starting point of the track, and ending the track starting of the target tracking.
2. The Bayesian-principle-based group target tracking track initiation method as recited in claim 1, wherein the current subgroup Z is 0 Equivalent measured value m 0 The method for acquiring the door associated with the prediction comprises the following steps:
s11: calculating an equivalent measured value m of the current subgroup 0 ：
Figure FDA0002590356790000041
Wherein the target metric set of the current subgroup is denoted as
Figure FDA0002590356790000042
Figure FDA0002590356790000043
Is the state vector of the ith target in the current subgroup at the t-th moment, and the state vector includes the position, speed and acceleration of the target, i ═ 1, 2 0 ，n 0 The target number contained in the current subgroup at the t moment;
s12: and predicting the position of the current subgroup which possibly appears at the next moment according to the speed upper limit value, the acceleration upper limit value, the average position and the sampling time interval of each target in the current subgroup to obtain a predicted correlation gate.
3. The Bayesian-principle-based group target tracking track initiation method as recited in claim 1, wherein the posterior probability P (TlD) in step S42 1 ) The calculation method comprises the following steps:
Figure FDA0002590356790000044
wherein, P (T | D) 0 ) The preset prior probability that the current subgroup belongs to the real track.
4. The Bayesian-principle-based group target tracking track starting method as recited in claim 1, wherein the posterior probability P of step S52 1 (T|D 1 ) The calculation method comprises the following steps:
Figure FDA0002590356790000045
wherein, P (T | D) 0 ) The preset prior probability that the current subgroup belongs to the real track.
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