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A multi-extended target tracking method based on spatio-temporal correlation

A multi-expanded target and expanded target technology, applied in the field of multi-expanded target tracking based on space-time correlation, can solve problems such as short distance and target number estimation, and achieve the effect of reducing the amount of calculation and reducing interference

Active Publication Date: 2022-04-26
UNIV OF ELECTRONICS SCI & TECH OF CHINA +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to overcome the deficiencies of the existing methods, propose a multi-extended target tracking method based on time-space correlation, solve the problem of multi-extended target distance and target state and target number estimation under the crossing of track, has good performance, and at the same time The method is also not affected by the measured density

Method used

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  • A multi-extended target tracking method based on spatio-temporal correlation
  • A multi-extended target tracking method based on spatio-temporal correlation
  • A multi-extended target tracking method based on spatio-temporal correlation

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0050] The purpose of this example is to verify the filtering performance of the proposed method in the scene where the distance between two extended targets is close and the target is moving in parallel. The initial state of target 1 is [-600m, -500m, 0m / s, 0m / s] T , the survival time is 1~100s; the initial state of target 2 is [-600m,-600m,0m / s,0m / s] T , the survival time is 1-100s; the intensity function of the newborn target in this scenario is:

[0051]

[0052] In the formula P γ,t =diag([100,100,25,25]).

[0053] figure 2 It is the comparison between the target state estimation of the present invention and the target real state under embodiment 1. It can be seen that the present invention can also obtain a better tracking result when the extended targets are relatively close to each other.

[0054] image 3 It is the comparison of the OSPA error between the method of the present invention and the method of distance division and directed graph SNN division un...

Embodiment 2

[0058] The simulation parameters are the same as Example 1. The purpose of this embodiment is to verify the filtering performance of the algorithm in the case of target intersection. There are 2 targets in the scene, and the initial state of target 1 is [250m, 250m, 0m / s, 0m / s] T , the survival time is 1~100s; the initial state of target 2 is [-250m,-250m,0m / s,0m / s] T , the survival time is 1~100s; the two targets intersect at 56s. The strength function of the nascent target in this scenario is:

[0059]

[0060] In the formula, P γ,t =diag([100,100,25,25]).

[0061] Figure 6 It is a comparison between the target state estimation of the present invention and the target real state under embodiment 2. It can be seen that a better estimation result can be obtained even at the time when the target track crosses.

[0062] Figure 7 It is the comparison of the OSPA error between the method of the present invention and the method of distance division and directed graph ...

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Abstract

The invention relates to a multi-extension target tracking method based on time-space correlation. When a target occupies multiple fractional rate units of the sensor, a single target will generate multiple measurement values, which is an extended target. In this context, when the extended target crosses, the general distance-based division method will divide the measurement values ​​of different targets into the same measurement set, resulting in a decrease in the accuracy of the filter and an error in the potential estimation. The present invention is based on the ET-GM-PHD algorithm, adopts the idea of ​​spatio-temporal correlation, utilizes the relevance of the measured values ​​of extended targets at adjacent moments, and tracks multiple extended targets on the basis of a directed graph SNN division. The method of the invention greatly reduces the tracking error of the extended target at the intersection, and realizes accurate estimation of the number of targets and the position of the target. At the same time, the tracking process of the extended target and the point target is separated, which greatly reduces the amount of calculation.

Description

technical field [0001] The invention belongs to the field of information fusion and relates to a multi-extended target tracking method based on time-space association. Background technique [0002] With the development of modern sensor technology, the resolution of the sensor is getting higher and higher. A single target will occupy multiple resolution units of the sensor and obtain multiple measurement information about the target at the same time. This target type becomes an extended target. ET-GM-PHD (Extended Target Gaussian Mixture PHD) is a filtering algorithm for tracking multi-extended targets under the theory of random finite sets. This method uses Gaussian mixture to represent the intensity function of multiple targets, and uses it to approximate multiple targets. the posterior distribution of . The multi-extended target method based on random finite sets avoids data association and reduces computational complexity. The indispensable part is to divide the measurem...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/16G06K9/62G06F17/15
CPCG06F17/16G06F17/15G06F18/23213
Inventor 甘露林晨徐政五廖红舒
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA