A Generalized Noise Reconstruction Framework for DOA Estimation in Received Data Domain

Abstract

<p>The performance of direction-of-arrival (DOA) estimation is severely affected by noise and clutter, and conventional methods fail to simultaneously cope with different situations because of the difficulties to predict noise and clutter. In order to solve this problem, a generalized robust framework for noise reconstruction in the received data domain is proposed to enhance DOA estimation performance. First, based on the Doppler information of the source, an approximate noise difference is obtained and, based on its cumulative sum, a coarse estimation of the received domain noise is then calculated. In particular, the optimal initial value is obtained using the generalized pattern search algorithm, where the objective function, constructed with the distance between the normalized Capon spatial spectrum peaks and the desired spatial spectrum peaks, is minimized. Then, exact reconstruction of the received data-domain noise is realized by a new cumulative sum formed using the solution from the previous step. Finally, using the denoised data, the spatial spectrum is obtained via the Capon algorithm. The effectiveness of the proposed framework is verified by simulations, both in terms of accuracy of DOA estimation and effectiveness in suppressing sidelobe and pseudo-peaks, for different cases, including white Gaussian noise, non-uniform noise, colored noise, impulsive noise, and K-distribution sea clutter. The relevant codes are available online: https://github.com/CJYLostviews/Robust-Noise-Reconstruction/</p>