A Computationally Efficient Direction-of-Arrival Estimation Algorithm, Robust Against Coherent Sources and Small Sample Size

A Computationally Efficient Direction-of-Arrival Estimation Algorithm, Robust Against Coherent Sources and Small Sample Size

Direction-of-arrival (DOA) estimation algorithms usually impose high computation burden and most of them are incapable of facing the coherent sources. In this paper, a newcomputationally efficient algorithm that is robust against the coherent sources is proposed. This method is based on acombination of the Maximum Likelihood (ML) and Orthogonal- Matching-Pursuit (OMP) algorithms. Simulation results show that the proposed algorithm has good performance in the small sample size cases and the coherency does not affect its performance

Direction-of-arrival (DOA) estimation algorithms usually impose high computation burden and most of them are incapable of facing the coherent sources. In this paper, a newcomputationally efficient algorithm that is robust against the coherent sources is proposed. This method is based on acombination of the Maximum Likelihood (ML) and Orthogonal- Matching-Pursuit (OMP) algorithms. Simulation results show that the proposed algorithm has good performance in the small sample size cases and the coherency does not affect its performance