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基于一维距离像的抗箔条干扰算法研究
引用本文:郭裕兰,万建伟,欧建平,陈付彬.基于一维距离像的抗箔条干扰算法研究[J].雷达科学与技术,2011,9(1):67-71.
作者姓名:郭裕兰  万建伟  欧建平  陈付彬
作者单位:国防科技大学电子科学与工程学院,湖南长沙,410073
基金项目:国防科技大学优秀研究生创新基金
摘    要:对箔条进行有效识别是对抗雷达箔条干扰特别是冲淡式干扰的关键。阐述了箔条干扰的原理,分析了舰船和箔条一维距离像的波形稳定性、距离像分布及相邻距离像相关性等差异,提取了距离像峰值点位置熵、距离像分散性以及相邻距离像相关系数三个目标特征,构造了BP神经网络识别器并完成了相应的参数设计以实现目标识别。利用真实数据进行了舰船和箔条的目标识别实验,结果表明该算法识别率高,收敛速度快,便于工程实现,具有较强的应用价值。

关 键 词:抗干扰  距离像  箔条  神经网络

Research on Anti-Chaff Jamming Method Based on Range Profile
GUO Yu-lan,WAN Jian-wei,OU Jian-ping,CHEN Fu-bin.Research on Anti-Chaff Jamming Method Based on Range Profile[J].Radar Science and Technology,2011,9(1):67-71.
Authors:GUO Yu-lan  WAN Jian-wei  OU Jian-ping  CHEN Fu-bin
Affiliation:(School of Electronic Science and Engineering,National University of Defense Technology,Changsha 410073,China)
Abstract:Distinguishing the chaff effectively is the key of anti-chaff-jamming.The principle of chaff jamming is presented.The differences of wave stability,distribution and neighboring correlation between ship and chaff range profiles are analyzed.Three target features such as range profile peak position entropy,range profile decentralization and neighboring range profile correlation coefficient are extracted.A BP neural network classifier is constructed and the related parameters are designed to fulfill the recognition task.A target recognition experiment is performed with the real data of ship and chaff.The results show that this method owns high recognition rate and convergence speed,and is capable for applications.
Keywords:anti-jamming  range profile  chaff  neural network
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