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Joint estimation algorithm for multi-targets’ motion parameters

When multiple targets are within the same radar antenna beam and cannot be separated in the range dimension, the conventional imaging methods cannot be directly used to obtain a focused radar image. In this study, a new joint estimation algorithm for multi-targets’ motion parameters is proposed. In...

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Published in:IET radar, sonar & navigation sonar & navigation, 2014-10, Vol.8 (8), p.939-945
Main Authors: Tian, Jing, Cui, Wei, Lv, Xiao-lei, Wu, Shuang, Hou, Jian-gang, Wu, Si-liang
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cited_by cdi_FETCH-LOGICAL-c5759-6713ccca1feb51d5e2e4914dddacdc9f527fb80a73fc9e3ab80331f4734c874f3
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container_title IET radar, sonar & navigation
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creator Tian, Jing
Cui, Wei
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Hou, Jian-gang
Wu, Si-liang
description When multiple targets are within the same radar antenna beam and cannot be separated in the range dimension, the conventional imaging methods cannot be directly used to obtain a focused radar image. In this study, a new joint estimation algorithm for multi-targets’ motion parameters is proposed. In this method, the first-order Keystone transform is first applied to correct the range walk of multiple targets simultaneously, and then the Lv's transform is used to estimate the motion parameters of targets including velocity and acceleration. The signal-to-noise ratio threshold for the proposed method is also given. The proposed method is fast and can obtain the accurate parameter estimation without knowing the number of targets and their motion information. Experimental results demonstrate the performance of the proposed algorithm. Comparisons between the proposed method and other methods, the maximum-likelihood method, fractional Fourier transform and discrete polynomial transform, are performed, which show that the proposed method can efficiently obtain the accurate parameter estimation with low computational burden.
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ispartof IET radar, sonar & navigation, 2014-10, Vol.8 (8), p.939-945
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subjects Acceleration
Algorithms
Beams (radiation)
discrete polynomial transform
first‐order Keystone transform
focused radar image method
Fourier transforms
fractional Fourier transform
Imaging
joint estimation algorithm
Lv transform
maximum likelihood estimation
maximum‐likelihood method
motion estimation
multitarget motion parameter estimation
Parameter estimation
Radar
radar antenna beam
Radar antennas
radar imaging
range walk correction
signal‐to‐noise ratio threshold
Transforms
title Joint estimation algorithm for multi-targets’ motion parameters
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