DOA Estimation by jointly exploiting L1-SVD and spatial smoothing in coherent environment
Jingchao Zhang, MuHeng Li, Longxin Bai, Liyan Qiao · 2024
The L1-SVD is widely used to solve direction of arrival (DOA) estimation problem in sparse manner. However, due to the influence of the coherent environment often caused by multipath propagation in practical applications, the noise immunity and estimation accuracy of the traditional L1-SVD algorithm deteriorate. In this paper, to improve its performance in correlated environment, we propose a new method called L1-SSD. We introduce spatial smoothing processing into the singular value decomposition (SVD) process and complete the DOA estimation by using the new spatial smoothing decomposition (SSD) with$l_{1}$-norm minimization. The hardware experimental results in real coherent environment verify that the L1-SSD algorithm can have higher estimation accuracy and better noise immunity than the traditional L1-SVD algorithm with slightly faster computation speed.