基于低截获概率优化的雷达组网系统最优功率分配算法(英文) 被引量：7

Optimal Power Allocation Algorithm for Radar Network Systems Based on Low Probability of Intercept Optimization

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摘要针对现代电子战中对低截获概率(LPI)技术的需求,该文提出了一种基于LPI性能优化的最优功率分配算法。该文首先推导了雷达组网系统的Schleher截获因子。然后,以最小化系统的Schleher截获因子为目标,在满足系统跟踪性能要求的前提下,通过优化组网雷达的功率配置,提升雷达组网系统的LPI性能。并用基于非线性规划的遗传算法(NPGA)对此非凸、非线性约束优化问题进行了求解。仿真结果验证了所提算法的有效性。 A novel optimal power allocation algorithm for radar network systems is proposed for Low Probability of Intercept （LPI） technology in modern electronic warfare. The algorithm is based on the LPI optimization. First, the Schleher intercept factor for a radar network is derived, and then the Schleher intercept factor is minimized by optimizing the transmission power allocation among netted radars in the network to guarantee target-tracking performance. Furthermore, the Nonlinear Programming Genetic Algorithm （NPGA） is used to solve the resulting nonconvex, nonlinear, and constrained optimization problem. Numerical simulation results show the effectiveness of the proposed algorithm.

作者时晨光汪飞周建江陈军

机构地区南京航空航天大学雷达成像与微波光子技术教育部重点实验室

出处《雷达学报（中英文）》 CSCD 2014年第4期465-473,共9页 Journal of Radars

基金 Supported by the National Natural Science Foundation of China(61371170) Funding of Jiangsu Innovation Program for Graduate Education(CXLX13_154) the Fundamental Research Funds for the Central Universities,the Priority Academic Program Development of Jiangsu Higher Education Institutions(PADA) Key Laboratory of Radar Imaging and Microwave Photonics,Ministry of Education,Nanjing University of Aeronautics and Astronautics

关键词雷达组网系统低截获概率(LPI) Schleher截获因子目标跟踪 Kullback-Leibler(KL)距离 Radar network systems Low Probability of Intercept （LPI） Schleher intercept factor Target tracking Kullback-Leibler （KL） divergence

分类号 TN958 [电子电信—信号与信息处理]

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1Phillip E P.Detecting and Intercept Radar[M].Boston Classifying Low Probability of Artech House,2009:342-352.
2Haimovich A M,Blum R S,and Cimini L J Jr.MIMO radar with widely separated antennas[J].IEEE Signal Processing Magazine,2008,25(1):116-129.
3Teng Y,Griffiths H D,Baker C J,et al.Netted radar sensitivity and ambiguity[J].IET Radar-Sonar and Navigation,2007,1(6):479-486.
4Fishier E,Haimovich A,Blum R S,et al.Optimizations of multisite radar system with MIMO radars for target detection[J].IEEE Transations on Aerospace and Electronic Systems,2011,47(4):2329-2343.
5Frieldlander B.Waveform design for MIMO radars[J].IEEE Transations on Aerospace and Electronic Systems,2007,43(3):1227-1238.
6Tang B,Tang J,and Peng Y N.MIMO radar waveform design in colored noise based on information theory[J].IEEE Transations on Signal Processing,2010,58(9):4684-4697.
7Yang Y and Blum R S.MIMO radar waveform design based on mutual information and minimum mean-square error estimation[J].IEEE Transations on Aerospace and Electronic Systems,2007,43(1):330-343.
8Chen Y F,Nijsure Y,Yuen C,et al.Adaptive distributed MIMO radar waveform optimization based on mutual information[J].IEEE Transations on Aerospace and Electronic Systems,2013,49(2):1374-1385.
9Song X F,Peter W,Zhou S L,et al.The MIMO radar and jammer games[J].IEEE Transations on Signal Processing,2012,60(2):687-699.
10Niu R X,Blum R S,Varsbney P K,et al.Target localization and tracking in noncoherent multipleinput multiple-output radar systems[J].IEEE Transations on Aerospace and Electronic Systems,2012,48(2):1466-1487.