基于PSO-MUSIC算法的分布式目标DOA估计  

DOA Estimation for Distributed Source Based on PSO-MUSIC

作　　者：李海[1] 居梦琪 张喆[1] LI Hai;JU Mengqi;ZHANG Zhe(Tianjin Key Lab for Advanced Signal Processing, Civil Aviation University of China, Tianjin 300300, China)

机构地区：[1]中国民航大学天津市智能信号与图像处理重点实验室,天津300300

出　　处：《雷达科学与技术》2019年第2期119-123,130,共6页Radar Science and Technology

基　　金：国家自然科学基金(No.61471365;U1733116;U1633106);中国民航大学蓝天青年学者培养经费;中央高校基本科研业务费项目资助课题(No.3122017007)

摘　　要：提出了一种基于粒子群优化算法(PSO)和多重信号分类(MUSIC)算法的分布式目标波达方向(Direction of Arrival,DOA)估计方法。在空间欠采样情况下,该方法首先利用粒子群优化算法优化阵列阵元间距,得到阵列天线方向图高旁瓣电平最小情况下的阵元间距,阵列阵元间距决定了阵列流形,然后在该阵列流形下构造分布式目标信号模型,最后结合分布式目标导向矢量和MUSIC算法获得空间欠采样情况下分布式目标中心DOA的准确估计。仿真结果表明了该方法的有效性。In this paper, we propose a distributed target DOA estimation method based on particle swarm optimization (PSO) and MUSIC algorithms. In this method, the PSO algorithm is used to optimize the spacing of array elements in the case of spatial under-sampling. The spacing of array element under the condition of the highest sidelobe level of the array antenna pattern is obtained. The manifold of array is determined by the array element spacing. And then a distributed target model is constructed. Finally, with the distributed target vector and MUSIC algorithm, the DOA estimation of distributed target under spatial under-sampling condition is obtained. Simulation results show the effectiveness of the method.

关 键 词：空间欠采样 旁瓣电平 波达方向估计 分布式目标 

分 类 号：TN959.73[电子电信—信号与信息处理] TN957.51[电子电信—信息与通信工程]