基于压缩感知的低复杂度超分辨角度估计方法  

Low complexity super-resolution angle estimation method based on compressive sensing

作　　者：吴敏 黎子皓 郝程鹏[1,2] 胡桥 WU Min;LI Zihao;HAO Chengpeng;HU Qiao(Institute of Acoustics,Chinese Academy of Sciences,Beijing 100190,China;University of Chinese Academy of Sciences,Beijing 100049,China;School of Mechanical Engineering,Xi’an Jiaotong University,Xi’an 710049,China)

机构地区：[1]中国科学院声学研究所,北京100190 [2]中国科学院大学,北京100049 [3]西安交通大学机械工程学院,陕西西安710049

出　　处：《系统工程与电子技术》2024年第6期1831-1837,共7页Systems Engineering and Electronics

基　　金：国家自然科学基金青年基金(62001468);国家自然科学基金(62371446,61971412);中国科学院青年创新促进会资助基金(2023030)资助课题。

摘　　要：在空域目标角度估计中,分辨率受阵列孔径的限制,依靠增加阵元数量提高分辨率会增加系统成本。为了在受限阵列尺寸中减少阵元数量,基于压缩感知(compressive sensing,CS)理论,提出了一种超分辨角度估计算法。首先建立阵列接收信号模型并构造冗余字典,然后利用目标空间域稀疏先验信息将目标角度估计问题建模为优化问题,最后设计低复杂度算法对优化问题求解。所提算法通过贝叶斯CS理论推导了正则化系数,保证了算法的噪声抑制性能,通过共轭梯度运算及Hadamard乘积提高了算法效率。所提算法可利用较少快拍在信号数目未知的条件下,实现高精度角度估计。仿真结果和实测数据验证了所提算法的有效性。In aerial target angle estimation,the resolution is constrained by the aperture length.Increasing the number of array elements to improve the resolution will increase the system lost.To reduce the number of elements in the limited array size,a novel algorithm of super-resolution angle estimation is addressed based on compressive sensing(CS)theory.The array received signal model is established and the redundant dictionary is formed.By exploiting the sparse prior information of the observation area,the target angle estimation problem is converted into the optimization problem.The direction of arrival of targets can be estimated with accuracy via an iterative optimization algorithm.In the proposed algorithm,the regularization coefficient is derived by Bayesian CS theory to ensure the noise robustness of the algorithm.Besides,the efficiency of the proposed algorithm is improved by using the conjugate gradient algorithm and Hadamard product.The effectiveness of the proposed algorithm is verified by simulation and measured data.

关 键 词：阵列信号处理 压缩感知 波达方向估计 波束形成 

分 类 号：TN911.7[电子电信—通信与信息系统]