JPH07101232B2 - Multi-target tracking method and apparatus - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION [Industrial field of application] This invention generates a track hypothesis indicating whether the detection data is a new target, a tracked target, or an unnecessary signal such as a clutter, and based on the reliability of the hypothesis, the clutter The present invention relates to a multi-target tracking method and apparatus for tracking multi-targets while removing unnecessary signals such as.

[Conventional technology]

The conventional method inputs detection data such as the position and detection time of the target as shown in FIG. 3 (step 12), and based on this detection data (detection time) and smoothing specifications of each target, Prediction parameters are calculated (step 13), the detection data is converted from polar coordinates to Cartesian coordinates (step 14), and the software gate of each target (target prediction at the next and subsequent detection times) is calculated based on the above prediction parameters. Existence range) is calculated (step 16), a cluster is generated based on the detection data and the software gate (step 17), and whether the detection data is a new target or a tracked target based on the generation result of the cluster. A hypothesis of a wake such as an unwanted signal such as clutter is generated (Step 1
8) Calculate the reliability based on this hypothesis and the above detection data, and remove unnecessary signals such as clutter (step 19), and the hypothesis reliability after removing unnecessary signals such as this clutter and the above detection data. Then, the smoothing parameters of each target are calculated based on the above prediction parameters (step 20), and it is judged from the reliability of the above hypothesis whether tracking has been established (step 21). Output the original (step 22),
It was judged whether or not it was finished (step 23), and when it was not finished, it was repeated from the beginning.

As shown in FIG. 4, the conventional device is a phased array antenna (1) for receiving a radar video and a radar signal processing for processing a radar video obtained from the phased array antenna (1) as a radar signal. A device (2) and a coordinate conversion device (4) for converting detection data in a polar coordinate system calculated from the radar signal processing device (2) into rectangular coordinates.
And a target prediction processing device (3) for calculating prediction data of each target based on the detection data calculated from the coordinate conversion device (4) and smooth data of each target, and the target prediction processing device (3). ), A software gate calculation device (8) for calculating a software gate of each target (predicted existence range of the target at the next detection time) based on the prediction specifications calculated from
A cluster generation device (9) for generating a cluster based on the software gate calculated by the software gate calculation device (8) and the detection data calculated by the coordinate conversion device (4), and this cluster generation device ( The coordinate conversion device (4) based on the cluster generation result obtained from 9).
A track hypothesis generator (10) that generates a track hypothesis that the detection data calculated from is a new target, an already-tracked target, or an unnecessary signal such as clutter, and a hypothesis obtained from this track hypothesis generator (10) and the above A hypothesis reliability calculation device (11) that calculates the reliability based on detection data and removes unnecessary signals such as clutter, and removes unnecessary signals such as clutter calculated from this hypothesis reliability calculation device (11) Target smoothing device (12) for calculating smoothing parameters of each target based on the reliability of the hypothesis, the detection data, and the prediction parameters calculated from the target prediction processing device (3); The tracking establishment determination device (13) determines whether tracking has been established according to the degree, and the track display device (14) that displays the track connected to this tracking establishment determination device (13).

[Problems to be Solved by the Invention]

In the conventional multi-target tracking method and apparatus as shown in FIG. 3 and FIG. 4, since the input transform data is always processed by the coordinate transformation device, the number of the sense data input is small. If there are many, the coordinate conversion process takes too much time and cannot be processed in real time. In particular, since the predicted existence range of the target is not definitely determined at the start of tracking, there is a high possibility that many detection data will be input. As a result, the performance at the start of tracking multiple targets was extremely poor.

The present invention has been made to solve such a problem, and an object thereof is to shorten the processing time at the start of tracking and improve the multi-target tracking capability.

[Means for Solving the Problems]

The multi-target tracking method and apparatus according to the present invention are provided with a coordinate system selection device in order to shorten the processing time at the start of tracking.

[Action]

In the present invention, during tracking start processing, coordinate conversion is not performed for the first few operations, and high-speed processing is performed in the polar coordinate system, which is the specification of the observation. By switching to a Cartesian coordinate system that enables accurate calculation of specifications, it is possible to shorten the time required to establish tracking and improve multi-target tracking capability.

〔Example〕

FIG. 1 is a block diagram of a multi-target tracking device showing one embodiment of the present invention. In FIG. 1, (1) to (4),
(8) to (14) are the same as those shown in FIG.
(5) is a coordinate conversion device that converts the prediction data of each target output from the target prediction processing device (3) in the polar coordinate system into north reference Cartesian coordinates, and (6) is the radar signal processing device (2) and target prediction A coordinate system selecting device for selecting the coordinate system of each target detection position and prediction data input from the processing device (3),
(7) is a selection data table that stores in advance the data that defines the judgment criteria when making a selection in the coordinate system selection device (6).

FIG. 2 is a diagram showing a processing procedure of an embodiment of the multi-target tracking method according to the present invention. In FIG. 2, the position of a radar signal processing device (2) for processing radar video data obtained from the phased array antenna (1) from the radar signal processing device (2),
The detection data such as the detection time is input (step 12), and the target prediction processing unit (3) calculates the prediction parameters of each target based on the detection data (detection time) and the smooth parameters of each target (step 12). 13), the first coordinate conversion device (4) and the second coordinate conversion device (5) convert from the polar coordinate system to the orthogonal coordinate system (step 14), and the coordinate system selection device (6) converts the two coordinate systems Either of them is selected (step 15), and the software gate calculation device (8) calculates the software gate of each target (predicted existence range of the target at the detection time after that) based on the above-mentioned prediction specifications. (Step 16), the cluster generator (9) generates a cluster based on the detection data, the initial software gate and the software gate (step 17), and the track hypothesis generator (10) generates the cluster. Based on the generated result The intelligent data generates a track hypothesis as to whether the new target is an already tracked target or an unnecessary signal such as clutter (step 18), and the hypothesis reliability calculation device (11) uses this hypothesis and the above detection data to determine the reliability of the hypothesis. Is calculated and unnecessary signals such as clutter are removed (step 19), and the hypothesis reliability after the unnecessary signals such as clutter are removed by the target smoothing processor (12), the detection data, and the above-mentioned prediction parameters are calculated. Then, the smoothing parameters of each target are calculated (step 20), and the tracking establishment determination device (13) judges whether or not the tracking is established based on the reliability of the above hypothesis (step 21). When the tracking is established,
The above smoothed parameters are output to the track display device (14) (step
22), it is judged whether or not it is finished (step 23), and when it is not finished, it is repeated from the beginning.

The above processing will be specifically described below.

The target prediction processing device (3) calculates the prediction specifications of each target by the formula (1).

Here X _k m (-) prediction specifications vector Φ _k-1 is the transition matrix X _k m (+) is smooth specifications vector K is time t _k m is already tracking the target number P _k m (-) prediction Parameters (error covariance matrix) P _k-1 m (+) is smooth parameter (error covariance matrix) Γ _{1 (k-1)} is process noise conversion matrix Q _k-1 is process noise in Kalman filter (target Motion fluctuation component) T represents the meaning of a transposed matrix.

The method of coordinate conversion in the first coordinate conversion device (4) and the second coordinate conversion device (5) is as follows.

The criterion for the determination by the coordinate system selection device (6) can be determined by the number of tracking operations (switching at the third time, etc.). Table 1 shows an example of the operation.

The software gate calculation method in the software gate calculation device (8) is shown below.

Where Z _k (−) m is the center position vector of the software gate H _k is the observation transformation matrix S _{k, m} is the matrix showing the spread of the software gate Γ ₂ (k) is the observation noise transformation matrix R _k is the observation noise The covariance matrix cluster generation device (9) shows a cluster generation condition and a calculation method.

Here, Z _k is the detection position vector Z _k (−) l is the predicted position vector Z _k (−) m of the tracked target l, and the predicted position vector d of the tracked target m is d.

As described above, when the detection data Z _k applies to both the software gates of the already tracked targets l and m, S _{k, m}
And S _{k, l} are integrated to generate a cluster.

S _k ′ = S _{k, m} + S _{k, l} (5) Here, S _k ′ is a matrix showing the spread of the cluster.

A hypothesis generation method in a track hypothesis generation device (10) is shown.

(A) Identification of detection data Clutter F Z _{k, n} Tracked target T _g New target N _h where n is the number of detection data.

g is the already-tracked target number.

h is the new target number.

The detection data is identified by any of the above three. The result of this discrimination is hypothesis X _k .

(B) Generation of hypothesis The hypothesis _Xk is generated by combining the hypothesis Xk _-1 before sampling with the latest detection data identification result. Multiple hypotheses are generated by combining detection data.

^Xk = { _Xk-1 } { _Xk } = { _Xk-1 } {F, _Tg , _Nh } ... (6) The calculation method of the hypothesis reliability in the hypothesis reliability calculation device (11) It is shown below.

P ^k (i, j) = N (R _p ^k i−Ro ^k j, B _R ^k i) ≧ K ₀ (7) where P: hypothesis reliability N (R _p ^k i−Ro ^k j , S _R ^k i): Position distribution between the i-th predicted position at time T _k-1 and the j-th detected position data at time T _k R _p ^k i = (R _xp ^k i, R _yp ^k i , R _zp ^k i): i-th target predicted position vector at time T _k−1 Ro ^k j = (R _xo ^k j, R _yo ^k j, R _zo ^k j): j-th time at time T _k Target predicted position data vector B _R ^k j: Spread of i-th S / W gate at time T _k-1 N: Normal distribution probability density function K ₀ : Constant When the above equation holds, the detection data for tracking start Considering the combination of the hypothesis X _k as a candidate, there is a correlation between the i-th predicted target at time t _k−1 and the j-th detection data at time t _k , and it is regarded as a “track”.

The smoothing value calculation method in the target smoothing device (12) is shown below.

(A) Kalman gain calculation for smoothing K _{k, m} = P _k (-) mH _k S _k , m ^-1 (8) where K _{k, m} is Kalman gain (b) Smoothing value calculation Here, X _k ^m (+) is a smoothing parameter (vector) P _k ^m (+) is a smoothing error covariance matrix.

A tracking establishment determination method in the tracking establishment determination device (13) will be described.

(A) Check whether the same track exists in all hypotheses.

(B) When the above conditions are met, tracking is established.

(C) If the above conditions are not satisfied, the process returns to the beginning.

Also, "Tracking has been established. ], The target smoothing specifications calculated from the target smoothing processing device (12) are output to the track display device (14).

〔The invention's effect〕

As described above, according to the present invention, by processing the detection data at the start of tracking in the polar coordinate system as it is, the tracking start processing of multiple targets can be executed at high speed, and as a result, it is necessary to establish the tracking. It is possible to shorten the time and improve the multi-target tracking ability.

[Brief description of drawings]

FIG. 1 is an overall configuration diagram of an embodiment of a multi-target tracking device according to the present invention, FIG. 2 is a diagram showing a processing procedure of an embodiment of a multi-target tracking method according to the present invention, and FIG. FIG. 4 is an overall configuration diagram of an embodiment of the multi-target tracking device of FIG. 4, and FIG. 4 is a diagram showing a processing procedure of an embodiment of a conventional multi-target tracking method. In the figure, (1) is a phased array antenna,
(2) is a radar signal processing device, (3) is a target prediction processing device, (4) is a first coordinate conversion device, (5) is a second coordinate conversion device, (6) is a coordinate system selection device, ( 7) is a selection data table, (8) is a software gate calculator,
(9) is a cluster generation device, (10) is a track hypothesis generation device, (11) is a hypothesis reliability calculation device, (12) is a target smoothing device, (13) is a tracking establishment determination device, and (14) is a track It is a display device. In the drawings, the same reference numerals indicate the same or corresponding parts.

Front page continuation (72) Inventor Hiromichi Kawazoe 325 Kamimachiya, Kamakura City, Kanagawa Mitsubishi Electric Corporation Kamakura Factory Examiner Kazuo Nakamura (56) References JP-A-61-186877 (JP, A)

Claims (2)

[Claims] 1. Detecting data such as position of target and unnecessary signal and detection time such as detection time, calculating prediction data of each target based on this detection data and smoothing data of each target, and observing detection data The specifications are converted from the polar coordinate system to the rectangular coordinate system, one of the above coordinate systems is selected, and the software gate of each target (the predicted existence range of the target at the next and later detection times) is selected based on the above prediction specifications. ) Is calculated, a cluster (aggregate of target predicted existence ranges) is generated based on the detection data and the software gate, and based on the generation result of the cluster, the detection data is a new target, a tracked target, or a clutter. A hypothesis of a wake such as an unnecessary signal such as is generated, the reliability of the hypothesis is calculated based on this hypothesis and the above detection data, unnecessary signals such as clutter are removed, and unnecessary signals such as clutter are removed. Hypothesis reliability, above The smoothing parameters of each target are calculated based on the detection data and the above prediction parameters, and it is judged from the reliability of the above hypothesis whether tracking has been established. When tracking has been established, the smoothing parameters are output and the processing ends. If it is not finished,
In addition, a multi-target tracking method characterized by repeatedly performing the above processing from the beginning. 2. A phased array antenna for receiving a radar video, a radar signal processor for processing a radar signal obtained from the phased array antenna as a radar signal, and detection data calculated by the radar signal processor. And a target prediction processing device for calculating the prediction data of each target based on the smooth data of each target, and the first and second coordinates for converting the polar coordinate system, which is the observation data of the detection data, into the orthogonal coordinate system. Based on a conversion device, a coordinate system selection device that selects the coordinate system, a selection data table that stores data that defines the selection criteria of the coordinate system selection device, and prediction specifications calculated from the target prediction processing device. And a software gate calculation device that calculates the software gate of each target (predicted existence range of the target at the detection time after that) and this software gate calculation device. A cluster generation device that generates a cluster based on the calculated software gate and the detection data calculated from the radar signal processing device, and a calculation from the radar signal processing device based on the cluster generation result obtained from the cluster generation device A track hypothesis generating device for generating a track hypothesis indicating whether the detected data is a new target, a tracked target, or an unnecessary signal such as a clutter, and a hypothesis obtained from the track hypothesis generating device and the reliability of the hypothesis based on the detection data. Hypothesis reliability calculating device for calculating the degree and removing unnecessary signals such as clutter, and hypothesis reliability after removing unnecessary signals such as clutter calculated from the hypothesis reliability calculating device, the detection data, and the target A target smoothing processor that calculates smoothing specifications of each target based on the prediction specifications calculated from the prediction processor, and the hypothesis reliability And tracking establishment determination device for determining whether the tracking has been established, the multi-target tracking apparatus characterized by comprising a track display device for displaying a track leading to the tracking establishment determination device.