%0 Journal Article
%A CAO Kai-jun
%A NING Fang-li
%A WEI Juan
%T DOA Estimation Algorithm for Sparse Representation Under Non-Stationary Noise
%D 2020
%R 10.13190/j.jbupt.2019-049
%J Journal of Beijing University of Posts and Telecommunications
%P 116-121
%V 43
%N 1
%X In order to improve the direction of arrival (DOA) estimation accuracy of the far-field non-coherent narrow-band signal in non-stationary noise environment, an improved DOA estimation algorithm based on sparse reconstruction is proposed. Firstly, the class differential covariance algorithm is used to construct the difference matrix to suppress the influence of non-stationary noise. Then the sparse representation model and the weight function is constructed based on the basic principle of estimation of signal parameters via rotational invariance technique algorithm. Finally, the DOA estimation is realized by solving the model with weighted <em>l</em><sub>1</sub> norm. Simulation shows that, compared with the traditional covariance difference algorithm, the noise covariance matrix estimation algorithm, the rank trace minimization algorithm, the sparse reconstruction algorithm, the proposed algorithm can not only suppress the influence of non-stationary noise effectively, but also has strong robustness and high estimation accuracy under low signal noise ratio and low snapshot number.
%U https://journal.bupt.edu.cn/EN/10.13190/j.jbupt.2019-049