网络雷达对抗系统无源探测及搜索力的优化  

Passive Detection of Network Radar Counter-measure System for Stealthy Targetsand Optimal Allocation of Search Capability

作　　者：骆胜阳 曾瑞琪 刘方正 LUO Sheng-yang;ZENG Rui-qi;LIU Fang-zheng(Institute of Electronic Countermeasure,National University of Defense Technology,Electronic Countermeasure Signal Processing Key Laboratory,Hefei Anhui 230037,China)

机构地区：[1]国防科技大学电子对抗学院,安徽合肥230037

出　　处：《计算机仿真》2020年第3期14-17,51,共5页Computer Simulation

摘　　要：为网络雷达对抗系统快速有效地搜索空中隐身目标的理论和方法,将搜索理论运用到网络雷达对抗系统协同对空中隐身目标的探测分析中,给出了其无源模式搜索的马尔可夫过程,同时给出无源模式搜索密度的计算方法以及三站协同搜索确定隐身目标位置和速度的方法,根据搜索空域的划分,建立了搜索力最优分配模型,并运用遗传算法对模型进行求解。通过实例计算表明,所提方法和模型是准确的,并且用遗传算法求解隐身目标搜索力分配问题是正确有效的。In order to detect the stealthy by NRCS(network radar counter-measure system)rapidly and effectively,search theory is introduced to analysis the cooperative detection of stealthy targets.The Markov process of passive search of NRCS was described,and the method of calculating the search consistency was educed.The method of the position and velocity detection of stealthy targets by three stations cooperation was researched.The model for optimal allocation of search capability according to the divide of detection regions was established,and the genetic algorithm was applied to solve the model.The model was verified using an example,and the results show that the method and model above are exact and the genetic algorithm applied to solve the model is effective.

关 键 词：网络雷达对抗系统 隐身目标 搜索论 发现目标概率 搜索力优化分配 

分 类 号：TN975[电子电信—信号与信息处理]