Based on sparse representations, the problem of two-dimensional (2-D) direction of arrival (DOA) estimation is addressed in this paper. A novel sparse 2-D DOA estimation method, called Dimension Reduction Sparse Reconstruction (DRSR), is proposed with pairing by Spatial Spectrum Reconstruction of Sub-Dictionary (SSRSD). By utilizing the angle decoupling method, which transforms a 2-D estimation into two independent one-dimensional (1-D) estimations, the high computational complexity induced by a large 2-D redundant dictionary is greatly reduced. Furthermore, a new angle matching scheme, SSRSD, which is less sensitive to the sparse reconstruction error with higher pair-matching probability, is introduced. The proposed method can be applied to any type of orthogonal array without requirement of a large number of snapshots and a priori knowledge of the number of signals. The theoretical analyses and simulation results show that the DRSR-SSRSD method performs well for coherent signals, which performance approaches Cramer–Rao bound (CRB), even under a single snapshot and low signal-to-noise ratio (SNR) condition.

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orthogonal array computational complexity pairmatching spatial spectrum reconstruction of subdictionary ssrsd angle decoupling method cramerrao bound crb signaltonoise ratio angle matching scheme ssrsd coherent signals dimension reduction sparse reconstruction twodimensional 2d direction of arrival doa estimation onedimensional 1d snapshot snapshots 2d redundant dictionary

Xiuhong Wang,Xingpeng Mao,Yiming Wang,Naitong Zhang,Bo Li,.A Novel 2-D Coherent DOA Estimation Method Based on Dimension Reduction Sparse Reconstruction for Orthogonal Arrays. 16 (9),.

Xiuhong Wang,Xingpeng Mao,Yiming Wang,Naitong Zhang,Bo Li,"A Novel 2-D Coherent DOA Estimation Method Based on Dimension Reduction Sparse Reconstruction for Orthogonal Arrays" 16

Xiuhong Wang,Xingpeng Mao,Yiming Wang,Naitong Zhang,Bo Li,"A Novel 2-D Coherent DOA Estimation Method Based on Dimension Reduction Sparse Reconstruction for Orthogonal Arrays"