Unknown Clutter Passive Co-Location Method Based on Sparsity Order Optimization

A technology of cooperative positioning and sparsity, which is applied in positioning, radio wave measurement systems, instruments, etc., can solve the problems of uneven distribution of clutter and affect the performance of target tracking, so as to solve the problem of multi-target tracking and improve multi-target tracking performance effect

Active Publication Date: 2021-02-09
HANGZHOU DIANZI UNIV
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  • Abstract
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  • Application Information

AI Technical Summary

Problems solved by technology

The PCL system environment is complex and changeable, especially near the coastline. In complex environments, the clutter distribution will no longer be uniform. When the assumed clutter distribution model is inconsistent with the actual clutter distribution, it will affect the performance of target tracking.

Method used

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  • Unknown Clutter Passive Co-Location Method Based on Sparsity Order Optimization
  • Unknown Clutter Passive Co-Location Method Based on Sparsity Order Optimization
  • Unknown Clutter Passive Co-Location Method Based on Sparsity Order Optimization

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Embodiment Construction

[0017] The present invention is further analyzed below in conjunction with specific embodiment.

[0018] N k unknown and N k The target ≥ 0 appears within the detection range of the sensor, and the position of the receiving station is marked as X Rr =[x Rr ,y Rr ], considering that the external radiation source is an airborne external radiation source, the position of the transmitting station at the kth moment is denoted as X k,T =[x k,Ts ,y k,Ts ]. Consider a single target t(0≤t≤N k ) state X at time k k,t for in is the position of the target t in the Cartesian coordinate system at time k, is the instantaneous velocity of the target t at time k, and the state transition model is as follows:

[0019] x k+1.t =F·X k,t +v k (1)

[0020]

[0021] Where F is the state transition matrix, I 2 represents the second-order identity matrix, is the Kronecker product, the process noise v k ~N(0,Q), σ v is the standard deviation of the process noise, and τ is ...

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Abstract

The invention proposes an unknown clutter passive cooperative positioning method based on sparseness order optimization. This method embeds the sparsity order optimized clutter density estimator into the Gaussian mixture probability hypothesis density filter to estimate the states and numbers of multiple targets. First, the target measurement is eliminated by threshold technology and target state feedback to obtain clutter measurement; secondly, samples are selected from the clutter measurement, and the samples are fitted by GA-SVR; finally, the extreme point of the fitting curve is obtained by the gradient method. The abscissa of the value point is rounded down to the optimal sparsity order n. The invention can effectively improve the passive cooperative positioning multi-target tracking performance under unknown clutter, and solve the difficult problem of multi-target tracking.

Description

technical field [0001] The invention belongs to the field of target detection and tracking, and relates to an unknown clutter passive cooperative positioning method based on sparsity order optimization. Background technique [0002] The passive co-location (Passive Coherent Location, PCL) system is a system composed of a receiving station and an external radiation source signal. Usually, a TV or broadcast signal is used as the external radiation source signal, and the direct wave of the external radiation source is received after being reflected by the target. The target can be located after coherent processing of the reflected wave. Because the system itself does not emit electromagnetic energy, it has good concealment, and at the same time, PCL has the advantages of effectively dealing with stealth targets and low cost. Applying the traditional data association filter to the PCL system has the characteristics of high complexity. The probability hypothesis density filter b...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01S5/02
Inventor 郭云飞钱恒泽陈志坤薛梦凡
Owner HANGZHOU DIANZI UNIV
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