基于降维噪声子空间的二维阵列DOA估计算法
doi: 10.3724/SP.J.1146.2011.00859
2-D DOA Estimation Method Based on Dimension Descended Noise Subspace
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摘要: 为提高波达方向(Direction Of Arrival, DOA)的估计速度，该文基于子空间的正交性原理，利用噪声子空间及其共轭的交集进行奇异值分解(SVD)实现噪声子空间的降维，并基于降维噪声子空间与导向矢量及其共轭的双正交性提出一种2维阵列快速DOA估计算法。理论分析和仿真实验表明：该算法不受实际阵型的限制，能将传统MUSIC谱的角度范围压缩至原来的一半，从而将DOA估计的计算量降至传统方法的50%，并具有与MUSIC算法相当的角度分辨率。Abstract: To improve the speed of the estimation of Direction Of Arrival (DOA), the dimension of the noise subspace is descended by the Singular Value decomposing (SVD) on the intersection of noise subspace and its conjugate one. Then a new method for fast 2-D DOA estimation is proposed based on the double orthogonality of the descended noise subspace to the steering vector and its conjugate one. Theoretical analysis and experiment results show that the newly developed method can be used without any restriction by the array structure and is capable of compressing the range of the dimension of traditional MUltiple SIgnal Classification (MUSIC) spectrum for 2 times, therefore, the calculation capacity of DOA estimate can be reduced to 50% while the estimation precision is the same as that of MUSIC.
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