Spatial Parameter Identification for MIMO Systems in the Presence of Non-Gaussian Interference

作     者：Zhang, Junlin Shi, Zihui Chen, Yunfei Liu, Mingqian 

作者机构：Xidian Univ State Key Lab Integrated Serv Networks Xian 710071 Peoples R China Univ Durham Dept Engn Durham DH1 3LE England 

出 版 物：《REMOTE SENSING》 (遥感)

年 卷 期：2024年第16卷第7期

页      面：1243页

核心收录：

学科分类：0830[工学-环境科学与工程（可授工学、理学、农学学位）] 1002[医学-临床医学] 070801[理学-固体地球物理学] 07[理学] 08[工学] 0708[理学-地球物理学] 0816[工学-测绘科学与技术] 

基　　金：National Natural Science Foundation of China 

主　　题：direction of arrival generalized multi-antenna time-frequency distribution multiple-input multiple-output systems number of transmit antennas 

摘      要：Reliable identification of spatial parameters for multiple-input multiple-output (MIMO) systems, such as the number of transmit antennas (NTA) and the direction of arrival (DOA), is a prerequisite for MIMO signal separation and detection. Most existing parameter estimation methods for MIMO systems only consider a single parameter in Gaussian noise. This paper develops a reliable identification scheme based on generalized multi-antenna time-frequency distribution (GMTFD) for MIMO systems with non-Gaussian interference and Gaussian noise. First, a new generalized correlation matrix is introduced to construct a generalized MTFD matrix. Then, the covariance matrix based on time-frequency distribution (CM-TF) is characterized by using the diagonal entries from the auto-source signal components and the non-diagonal entries from the cross-source signal components in the generalized MTFD matrix. Finally, by making use of the CM-TF, the Gerschgorin disk criterion is modified to estimate NTA, and the multiple signal classification (MUSIC) is exploited to estimate DOA for MIMO system. Simulation results indicate that the proposed scheme based on GMTFD has good robustness to non-Gaussian interference without prior information and that it can achieve high estimation accuracy and resolution at low and medium signal-to-noise ratios (SNRs).