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Improved multi-expansion target tracking method

A multi-expansion target and target technology, applied in the reflection/re-radiation of radio waves, instruments, measuring devices, etc., can solve the problems of complex calculation and loss of measurement data, etc.

Inactive Publication Date: 2018-03-23
NANJING UNIV OF SCI & TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

To sum up, in the actual radar measurement information, there are problems of multi-extended target measurement set division, measurement data loss and complex calculation.

Method used

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  • Improved multi-expansion target tracking method

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Experimental program
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Effect test

Embodiment 1

[0170] Effect of the present invention can be further illustrated by following simulation experiments:

[0171] 1. Simulation conditions

[0172] set goal state The unit of position is m, and the unit of speed is m / s. There are four targets in this simulation. The target motion model includes the turning (CT) model and the Jerk model. The initial states of the four targets are as follows:

[0173] x t1 =[3000,3000,2400,-30,-30,-10,-0,-0,0.4,0,0,-0.01] T ;

[0174] x t2 =[2000,1000,1600,30,30,15,-1,-1,0,0,0,-0] T ;

[0175] x t3 =[2000,1000,1600,30,30,15,-1,-1,0,0.01,0,-0.01] T ;

[0176] x t4 =[4000,2000,2100,-20,-30,-10,1,1,0,0,0,0.01] T ;

[0177] For different motion models, the motion equations of the target are:

[0178] Jerk model:

[0179] CT model:

[0180] In the formula: p1=(2-2*alpha*T+alpha^2*T^2-2*exp(-alpha*T)) / (2*alpha^3);

[0181] q1=(exp(-alpha*T)-1+alpha*T) / alpha^2;

[0182] r1=(1-exp(-alpha*T)) / alpha;

[0183] s1=exp(-alpha*T); alpha is...

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Abstract

The t invention discloses an improved multi-expansion target tracking method. The method comprises the following steps: carrying out clustering and division on a measurement data set of a sensor and initializing a probability hypothesis density value and a potential distribution value of a target; predicting and updating a probability hypothesis density value and a potential distribution value oftarget state set at a next time to obtain a probability hypothesis density value and a potential distribution value at the current time; carrying out trimming and combination on a Gaussian term of anintensity function of the target, extracting target state estimation, and carrying out performance evaluation; and carrying out prediction, updating, and trimming and combination repeatedly and tracking the target till disappearance of the target. Therefore, the tracking accuracy of the target in a clutter environment is improved; the precision losses caused by the blind area of the radar are reduced; the computing load of the filter is reduced; and the engineering application of the GM-CPHD filter is realized well.

Description

technical field [0001] The invention belongs to the field of target tracking, in particular to an improved multi-extension target tracking method. Background technique [0002] With the widespread application of high-resolution sensors, the study of Extended Target Tracking (ETT) technology has become a hot spot. In particular, with the continuous improvement of radar resolution, multiple measurements of the same target with different equivalent scattering centers can be received at each moment. At this time, the target is no longer a point target, but an extended target. In recent years, Professor Ronald P.S. Mahler has proposed a probability hypothesis density (Probability Hypothesis Density, PHD) filtering algorithm based on random finite set (RFS) theory, which can simultaneously realize the target number and target state without considering data association. estimate. It first tracks the entire target population and then detects each variable. However, PHD filtering ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S13/66G01S7/41G06K9/62
CPCG01S7/41G01S13/66G06F18/2321
Inventor 吴盘龙邓宇浩何山王雪冬肖仁强曹竞丹
Owner NANJING UNIV OF SCI & TECH
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