DOA Estimation Method Based on Maximum Likelihood for Nest Array Via Sparse Representation

The performance of the direction of arrival (DOA) estimation method based on sparse representation can be degraded by the grid error. A new DOA estimation method based on maximum likelihood for nest array is proposed in this paper. By the vectorization operator and the denoising processing, we build a new sparse model which has a wider aperture and can obtain better performance. The grids near the true DOAs are roughly obtained by the estimation of spatial power spectrum estimation, then it is refined by one-dimension searching method. Simulation results indicate the proposed method outperforms the existing methods with a higher accuracy and detection possibility, especially in lower signal-to-noise (SNR).