A Novel 2-D Coherent DOA Estimation Method Based on Dimension Reduction Sparse Reconstruction for Orthogonal Arrays

Sensors

卷:16

Yiming Wang¹  Xiuhong Wang¹  Naitong Zhang¹  Xingpeng Mao¹  Bo Li² 

[1] School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150001, China;

[2] School of Information and Electrical Engineering, Harbin Institute of Technology (Weihai), Weihai 264209, China;

关键词: direction of arrival (DOA);    two-dimensional (2-D) DOA estimation;    coherent sources;    dimension reduction sparse reconstruction;    redundant sub-dictionary;   

DOI  :  10.3390/s16091496

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown