A Novel Method of DOA Estimation for Wideband Signals Based on Sparse Representation

A novel wideband signals Direction-Of-Arrival (DOA) estimation method based on sparse representation is proposed. This algorithm can reduce the storage and calculation of the traditional sparse representation methods in wideband signals process, which is caused by the large dimension of base matrix. The over-complete dictionary is constructed by using one-frequency to replace the 2D combination of frequency and angle. The column number of constructed dictionary only equals to that of single-frequency redundant dictionary. The proposed method first adopts focused thought to stack the different frequency data to the reference frequency and founds the redundant dictionary with a single frequency. Then, a sparse recovery model is established to obtain the DOA estimations, which are coming from following the focus process. At the same time, the Singular Value Decomposition (SVD) is used to summarize each frequency to reduce computation burden further. Finally, an automatic selection criterion for the regularization parameter involved in the proposed approach is introduced. The proposed algorithm can effectively distinguish the correlative signals without any decorrelation processing, and it has higher accuracy and detection possibility. The experiment results indicate that the proposed method is effective to estimate the DOA of wideband signals.