DOA Estimation via Sparse Signal Recovery in 4-D Linear Antenna Arrays With Optimized Time Sequences

Abstract

A novel direction of arrival (DOA) estimation method for four-dimensional (4-D) linear arrays with optimized time sequences using the sparse signal recovery is proposed in this paper. By establishing the sparse signal recovery model applied to DOA estimation of 4-D linear arrays, it is found that the time sequences have great influence on sparse signal recovery. Thus mutual coherence and covariance matrix of noise are introduced to evaluate its influence quantificationally. The differential evolutionary (DE) algorithm is then used for the optimization of time sequences such that the capability of sparse signal recovery is improved and the noise after time modulation is close to Gaussian white noise. It can be found that the unidirectional phase center motion (UPCM) scheme is an excellent candidate by the optimization of an 8-element 4-D linear array. By comparison with the previous methods, simulated results demonstrate that the proposed method has distinct advantages over other methods in probability of resolution and estimation accuracy, especially for the cases where the number of snapshots is small and the SNR is low. Furthermore, an S band 4-D linear array with eight elements is designed and measured to demonstrate the performance of DOA estimation by the proposed method.