DOA estimation of coherently distributed sources based on block-sparse constraint with measurement matrix uncertainty

Abstract

In this letter, we proposed a new algorithm to solve the problem concerning the direction-of-arrivals (DOAs) estimation of coherently distributed sources based on the block sparse signal matrix uncertainty model of compressed sensing. Considering the measurement matrix corrupted by the unknown noise, the central DOA and the angular spread estimation may degrade considerably. But our method is robust with the measurement matrix uncertainty. Furthermore, the proposed method has better performance in low signal-to-noise (SNR). The effectiveness of our method is confirmed by simulation results.