Algorithm of Discriminating Phantom Track and Target Track for Radar Network Based on Multivariate Statistical Analysis Theory

SUN Dian-xing; WANG Guo-hong; ZHANG Xiang-yu

doi:10.3969/j.issn.0372-2112.2014.09.003

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Algorithm of Discriminating Phantom Track and Target Track for Radar Network Based on Multivariate Statistical Analysis Theory

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- Algorithm of Discriminating Phantom Track and Target Track for Radar Network Based on Multivariate Statistical Analysis Theory
- Acta Electronica Sinica Vol. 42, Issue 9, Pages: 1680-1685(2014)
- 作者机构：
  
  海军航空工程学院电子信息工程系,山东,烟台,264001
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China (No.61002006)
- DOI：10.3969/j.issn.0372-2112.2014.09.003
  CLC： TN953.6
- Published：2014
- 稿件说明：
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SUN Dian-xing, WANG Guo-hong, ZHANG Xiang-yu. Algorithm of Discriminating Phantom Track and Target Track for Radar Network Based on Multivariate Statistical Analysis Theory[J]. Acta Electronica Sinica, 2014, 42(9): 1680-1685.
DOI：

SUN Dian-xing, WANG Guo-hong, ZHANG Xiang-yu. Algorithm of Discriminating Phantom Track and Target Track for Radar Network Based on Multivariate Statistical Analysis Theory[J]. Acta Electronica Sinica, 2014, 42(9): 1680-1685. DOI： 10.3969/j.issn.0372-2112.2014.09.003.

摘要

文章以雷达组网为研究背景，从虚假航迹形成原理出发，针对真假航迹统计特性的差异，提出了一种基于多元统计分析理论的雷达网航迹欺骗鉴别方法.利用电子战飞机（ECAV）编队对雷达网进行航迹欺骗干扰时，由于ECAV编队自身飞行控制等原因，引入一定的随机误差，引起了原有量测误差的变化.本文通过构造一种样本向量，将这种差异加以提取，然后利用似然比检验的方法对虚假航迹进行鉴别.仿真结果证明了该技术的可行性和有效性.

Abstract

In the presence of the statistical property of phantom track and target track

an algorithm of discriminating phantom track and target track is proposed

which is based on multivariate statistical analysis theory.The algorithm originates from the generation mechanism of phantom track in the background of radar network.When the phantom track is generated by the ECAVs

the variance of the phantom track is different from the variance of target track because of the random error caused by the ECAVs.A kind of sample vector is constructed to extract the variance then the phantom track is recognized by likelihood ratio tests.Simulation results verify the feasibility and validity of the proposed algorithm.

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