DOA estimation based on compressive sampling array with novel beamforming
DOA estimation based on compressive sampling array with novel beamforming
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基于新型波束形成压缩采样阵列的 DOA 估计
DOI：
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
Guangming Huang
中科院分区：
文献类型：
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作者：
Guiliang Li;Guangming Huang
针对目标空间分布稀疏的特点，提出了一种基于压缩采样阵列（CSA）的压缩感知波束形成（CSB）DOA估计算法。设计了一种新的压缩矩阵，使CSA能够将大规模阵列压缩成小规模阵列，从而降低了硬件和软件复杂度; CSB结合了传统Capon方法和MUSIC方法的优点，不仅跳过了源数目估计和EVD，而且只需少量快拍就能达到令人满意的性能。仿真结果表明，该算法具有分辨率高、抗噪声能力强、计算量小等优点。
Based on the sparse property of the targets distributed in spatial domain, a novel Compressive Sensing Beamforming (CSB) algorithm based on compressive sampling array (CSA) is proposed for DOA estimation. A new compression matrix is designed for CSA to be able to compress a large size array into small size array that brings the advantage of reducing both hardware and software complexity, and the CSB can be viewed as a combination of merit of conventional Capon and MUSIC method which not only skips sources number estimation and EVD, but also behaves satisfactorily with a few snapshot. Simulation results demonstrate that the proposed algorithm possess high resolution, robust to additive noise, reduction computational burden and so on.