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Direction-of-arrival estimation based on modified Bayesian compressive sensing method

机译:基于改进贝叶斯压缩感知方法的到达方向估计

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In this paper, the narrowband DOA estimation problem is studied in compressive sensing (CS) perspective. A novel DOA estimation approach based on extended Bayesian compressive sensing (BCS) is presented. To avoid the matrix singular drawback in BCS, a basis pruning procedure through iterative hard thresholding is utilized. The proposed method is hyper-parameter free and needs not know the number of sources a prior. Simulation results demonstrate that the proposed scheme has high space resolution and can resolve highly correlated or coherent sources.
机译:本文从压缩感知(CS)的角度研究了窄带DOA估计问题。提出了一种基于扩展贝叶斯压缩感知(BCS)的DOA估计新方法。为了避免BCS中矩阵奇异的缺点,使用了通过迭代硬阈值进行的基本修剪过程。所提出的方法是无超参数的,并且不需要事先知道源的数量。仿真结果表明,该方案具有较高的空间分辨率,可以解析高度相关或相干的信号源。

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