DOA Estimation Method Using Sparse Representation with Orthogonal Projection

Abstract

In order to reduce the effect of noises on DOA estimation, this paper proposes a direction-of-arrival (DOA) estimation method using sparse representation with orthogonal projection (OPSR). The OPSR method obtains a new covariance matrix by projecting the covariance matrix of the array data to the signal subspace, leading to the elimination of the noise subspace. Afterwards, based on the new covariance matrix after the orthogonal projection, a new sparse representation model is established and employed for DOA estimation. Simulation results demonstrate that compared to other methods, the OPSR method has higher angle resolution and better DOA estimation performance in the cases of few snapshots and low SNRs.

Keywords

DOA estimation / signal subspace / orthogonal projection / sparse representation