摘要
针对传统波达方向角(DOA)估计算法需要大量采样数据从而导致较高计算复杂度的问题,基于压缩感知理论,利用目标信号空域稀疏性,提出一种基于波束域的多测量矢量欠定系统正则化聚焦求解DOA估计算法。该算法将压缩信号从阵元域映射至波束域,一定程度上克服了稀疏重构算法无法用于低信噪比情况下的缺陷。数值仿真表明,与传统的Capon,MUSIC和l1-SVD算法相比,所提算法可对相干信号进行有效DOA估计,具有较高角度分辨力和估计精度;与RMFOCUSS和l1-SVD算法相比,所提算法具有较低计算复杂度。
The traditional Direction of Arrival( DOA) estimation algorithms require a large amount of sampling data,which causes high computational complexity.To address this problem,based on the compressive sensing theory,a beamspace based Regularized Multi-vector Focal Undetermined System Solver( RMFOCUSS) DOA estimation algorithm is proposed,which uses the spatial sparsity characteristic of targets of interest.The proposed algorithm maps the received compressed signals from the element-space to the beamspace,which overcomes the flaw that the sparse reconstruction algorithm cannot be used under the conditions of low SNR to some extent.Numerical simulations demonstrate that: 1) Compared with the traditional Capon,MUSIC and l1-SVD algorithms,the proposed algorithm can effectively carry out DOA estimation of the coherent signals with higher angle resolution and estimation accuracy; and 2) Compared with the element-space based RMFOCUSS and l1-SVD algorithms,the proposed method has a lower computational complexity.
作者
房云飞
王洪雁
裴炳南
FANG Yun-fei;WANG Hong-yan;PEI Brag-nan(Dalian University,1.Liaoning Engineering Laboratory of Beidou High-precision Location Service;Dalian Key Laboratory of Environmental Perception and Intelligent Control,Dalian 116622,China)
出处
《电光与控制》
北大核心
2018年第8期88-92,共5页
Electronics Optics & Control
基金
国家自然科学基金(61301258
61271379)
中国博士后科学基金(2016M590218)