The DOA estimation of moving targets mixed with stationary targets
Chuan Wan, Yubing Han, Weixing Sheng, Xiaofeng Ma, Renli Zhang · 2017
In many cases for direction of arrival (DOA) estimation, moving targets which are the signals of interest, exist with stationary targets simultaneously. To obtain the DOAs of moving targets while eliminating the stationary signals, a new method based on multiple signal classification (MUSIC) for uniform linear array (ULA) is presented in this paper. The signal and noise subspaces are given by singular value decomposition (SVD) of the processed covariance matrix which is a non-positive definite matrix and includes the information only about moving targets. It is well known that source number estimation is needed in subspace-based methods. However, the traditional methods based on information theoretic criteria couldn't work well due to the special distribution of the singular values even with high signal-to-noise ratio (SNR). Thus according to the property of singular values of the processed covariance matrix, we give a relative robust approach to estimate the number of moving sources. Several simulation examples are provided to show the performance and effectiveness of the proposed method.