DOA Estimation Method Based on Maximum Likelihood for Nest Array Via Sparse Representation
Yonghong Zhao, Jing Xin, Sijie Wu · 2021 CIE International Conference on Radar (Radar) · 2021
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).