Fast and efficient DOA estimation method for signals with known waveforms using nonuniform linear arrays

作     者：Gu, Jian-Feng Zhu, Wei-Ping Swamy, M. N. S. 

作者机构：Ecole Polytech Dept Elect Engn Montreal PQ H3C 3A7 Canada Concordia Univ Dept Elect & Comp Engn Montreal PQ H3G 1M8 Canada 

出 版 物：《SIGNAL PROCESSING》 (信号处理)

年 卷 期：2015年第114卷

页      面：265-276页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 

主　　题：DOA estimation Known waveform Sparse linear array Maximum likelihood problem Regression analysis 

摘      要：In this paper, a new approach is proposed to estimate the direction of arrival (DOA) of multiple non-coherent source signals with known waveforms but unknown gains based on a nonuniform linear sensor array. Unlike some previous methods, which estimate the DOA using spatial signatures of the signals with known waveforms, the proposed method first uses the known waveforms and mutually independent sensor measurement noises to establish a maximum likelihood estimation problem corresponding to multiple linear regression models, each containing the DOA and the gain information of all the source signals. Then, regression analysis is performed to estimate the coefficients of each linear regression model, and the well-known generalized least squares is used to obtain the estimates of the angles and gains from the estimated regression coefficients. The proposed method does not require a search over a large region of the parameter space, which is normally needed in ML-based DOA estimation methods. The effect of correlated sources on the performance of the parameter estimation is also studied. It is shown that the DOA and gain estimates are asymptotically optimal as the sources, tend to be uncorrelated. Finally, simulation results that demonstrate the estimation performance of the proposed method are given. (C) 2015 Elsevier B.V. All rights reserved.