DAI Wen-shu1, BAO Kai-kai2, WANG Ping3, WANG Li-ming1
（1. School of Information and Communication Engineering, North University of China, Taiyuan 030051, China； 2. Department of Demand and Control, Northern Institute of Automatic Control Technology, Taiyuan 030051, China； 3. Beijing AppSoft Technology Co. Ltd., Beijing 100085, China）
Abstract： When signal-to-interference ratio is low, the energy of strong interference leaked from the side lobe of beam pattern will infect the detection of weak target. Therefore, the beam pattern needs to be optimized. The existing Dolph-Chebyshev weighting method can get the lowest side lobe level under given main lobe width, but for the other non-uniform circular array and nonlinear array, the low side lobe pattern needs to be designed specially. The second order cone programming optimization (SOCP) algorithm proposed in the paper transforms the optimization of the beam pattern into a standard convex optimization problem. Thus there is a paradigm to follow for any array formation, which not only achieves the purpose of Dolph-Chebyshev weighting, but also solves the problem of the increased side lobe when the signal is at end fire direction. The simulation proves that the SOCP algorithm can detect the weak target better than the conventional beam forming.
Key words： anti-interference beam pattern; second-order cone programming optimization (SOCP); weak signal detection
CLD number： TN911.7 Document code： A
Article ID： 1674-8042（2016）03-0255-06 doi： 10.3969/j.issn.1674-8042.2016.03.008
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基于二阶锥优化的抗干扰波束图设计
戴文舒1， 鲍凯凯2， 王 萍3， 王黎明1
（1 中北大学 信息与通信工程学院， 山西 太原 030051； 2 北方自动控制技术指挥控制部, 山西 太原 030051； 3. 北京神州惠普科技股份有限公司， 北京 100085）
摘 要: 当信干比较低时， 强干扰会通过波束图的旁瓣泄露影响弱目标的检测， 因此需要对波束图进行优化设计。 已有的Dolph-Chebyshev加权方法可以在给定的主瓣宽度下获得最低的旁瓣级， 但是对于圆阵或其他非均匀线阵， 需要根据阵型进行低旁瓣的波束图设计。 本文提出的基于二阶锥优化方法， 将波束优化问题转化为标准的凸优化数学问题， 进而有范式可循， 而且可以达到Dolph-Chebyshev加权的效果， 同时解决了目标端射时旁瓣升高的问题。 仿真验证了基于二阶锥优化的算法较常规算法能更好的识别弱目标。
关键词: 抗干扰波束图； 二阶锥优化； 弱信号检测
引用格式： DAI Wen-shu, BAO Kai-kai, WANG Ping, et al. Anti-interference beam pattern design based on second-order cone programming optimization. Journal of Measurement Science and Instrumentation, 2016, 7(3)： 255-260. ［doi： 10.3969／j.issn.1674-8042.2016.03.008］
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