A Spatial-spectrum-based Method for DOA Estimation in low Signal-to-noise Ratio

Direction-of-arrival (DOA) estimation problems are extensively studied in array processing. Conventional beamforming (CBF) is robust but with wide beamwidth and high sidelobes. High-resolution methods provide narrow beamwidth and low sidelobe, but the snapshots need to meet Nyquist-rate sampling which is a large amount of data. This paper develops a DOA estimation method combining compressive sensing algorithms with CBF. Compressive sensing algorithm is applied in the beam space after the incoming signal has been beamformed by CBF. Under the framework of compressed sensing, we consider the spatial spectrum gained by CBF as the observation vector and beam pattern matrix as the sensing matrix. To reconstruct the incident signal accurately, we propose a division method of angle based on genetic algorithm (GA) to improve orthogonality of the sensing matrix. Orthogonal matching pursuit (OMP) algorithm is used to utilize the new redundant dictionary. The performance of the proposed method is evaluated by simulation. The results demonstrate that the proposed method accurately estimates DOA in low signal-to-noise ratio (SNR).