Expected likelihood for compressive sensing-based DOA estimation

This work addresses the problem of spatial compressive sensing (SCS) DOA estimation performance evaluation by exploiting an estimation-theoretic method known as expected likelihood (EL). This work provides a novel application of the EL method to mitigate two bias sources present in the SCS DOA estimation approach due to discretization of the azimuth bearing space and L1-regularization.