Direction-of-Arrival Estimation Via Real-Valued Sparse Representation

Abstract

Sparse representation direction-of-arrival (DOA) estimation methods exhibit many advantages over other DOA estimation methods. However, they suffer from a high computational complexity. This letter describes a real-valued sparse representation method through utilizing a unitary transformation that can convert complex-valued manifold matrices of uniform linear arrays (ULAs) into real ones. Due to this transformation, the computational complexity is decreased by a factor of at least four. The letter also shows that the proposed method has a better noise suppression because of exploiting an additional real structure. Therefore, it outperforms the original method, especially when signal-to-noise ratio (SNR) is low. Simulation results verify the performance improvement of the proposed method.