Single-Channel Compressive Sensing for DOA Estimation via Sensing Model Optimization
Single-Channel Compressive Sensing for DOA Estimation via Sensing Model Optimization作者机构：Nanjing University of Science and Technology Nanjing China
出 版 物：《International Journal of Communications, Network and System Sciences》 (通讯、网络与系统学国际期刊（英文）)
年 卷 期：2017年第10卷第5期
页 面：191-201页
学科分类：0810[工学-信息与通信工程] 08[工学] 081001[工学-通信与信息系统]
主 题：Compressive Sensing Direction-of-Arrival Estimation Single-Channel Mismatching Error
摘 要：The performance of multi-channel Compressive Sensing (CS)-based Direction-of-Arrival (DOA) estimation algorithm degrades when the gains between Radio Frequency (RF) channels are inconsistent, and when target angle information mismatches with system sensing model. To solve these problems, a novel single-channel CS-based DOA estimation algorithm via sensing model optimization is proposed. Firstly, a DOA sparse sensing model using single-channel array considering the sensing model mismatch is established. Secondly, a new single-channel CS-based DOA estimation algorithm is presented. The basic idea behind the proposed algorithm is to iteratively solve two CS optimizations with respect to target angle information vector and sensing model quantization error vector, respectively. In addition, it avoids the loss of DOA estimation performance caused by the inconsistent gain between RF channels. Finally, simulation results are presented to verify the efficacy of the proposed algorithm.
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