A Coherent DOA Estimation in Alpha Noise
Wenchao He, Liyan Li, Xuhao Lv · 2022
Direction of arrival estimation (DOA) of coherent sources is one of the important research in the fields of signal processing, especially in alpha noise which do not have a probability density of closed-form expression. Combining with the Fractional low order moment (FLOM) and subspace smoothing technique (SS), a framework which applicable to Sparse methods was proposed to deal with coherent sources in alpha noise. In order to improve the performance of the estimation, the subspace fitting technique (WSF) was proposed. In order to improve the computation speed of sparse recovery algorithm, combining with unitary transformation method, a sparse recovery model is proposed. Compared with the current algorithm, the proposed algorithm has obvious advantages in root mean square error and estimation success rate.