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均匀圆形阵列天线的压缩感知二维DOA估计方法
Compressed Sensing 2-D DOA Estimation for the Uniform Circular Array

DOI: 10.12677/JA.2020.92003, PP. 19-29

Keywords: 均匀圆型阵列,压缩感知,模式空间转换,奇异值分解,正交匹配追踪
Uniform Circular Array Structure
, Compressed Sensing (CS), Pattern Space Transformation, Singular Value Decomposition (SVD), Orthogonal Matching Pursuit (OMP)

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Abstract:

结合均匀圆型阵列结构的特殊性,论文提出了一种基于压缩感知的二维波达方向估计方法。该方法首先利用模式空间转换将阵元空间的均匀圆阵转换成模式空间的虚拟线阵;其次采用奇异值分解的方法进行降维,得到低维数据矩阵;最后借助正交匹配追踪算法进行求解,获得二维角度估计值。通过理论推导和实验仿真表明该方法无须谱峰搜索,计算量较小,对于二维相干信号和非相干信号也都具有良好的估计性能。相比于经典算法,对于不同条件下的二维DOA估计该方法也具有一定的优越性。
Combining the particularity of the uniform circular array structure, this paper proposes a 2-D DOA estimation method based on CS theory. This method first uses the pattern space transformation to convert the uniform circular array of array element space into the virtual linear array of pattern space; secondly, the SVD processing is used to reduce the dimension to obtain a low-dimensional data matrix; finally, utilizes the OMP algorithm to solve the problem to obtain the 2-D angle estima-tion value. Theoretical derivation and experimental simulations show that this method does not re-quire spectral peak search and has a small amount of calculation. It also has good estimation per-formance for two-dimensional coherent and non-coherent signals. Compared with the classic algo-rithm, this method also has certain advantages for 2-D DOA estimation under different conditions.

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