Enhanced DOD and DOA estimations in coprime MIMO radar: Modified matrix pencil method

作     者：Ahmad, Mushtaq Zhang, Xiaofei Ali, Farman Lai, Xin 

作者机构：Nanjing Univ Aeronaut & Astronaut NUAA Coll Elect & Informat Engn Nanjing 210016 Peoples R China NUAA Minist Ind & Informat Technol Key Lab Dynam Cognit Syst Electromagnet Spectrum S Nanjing Peoples R China 

出 版 物：《DIGITAL SIGNAL PROCESSING》 (Digital Signal Process Rev J)

年 卷 期：2025年第159卷

核心收录：

学科分类：0808[工学-电气工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 

基　　金：National Science Foundation of China (NSF) [62371227, 62371225, 61601167] Open Research Fund of NUAA [kfjj20170412] Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space NUAA, Ministry of Industry and Information Technology in China [KF20181915] 

主　　题：Coprime array DOD and DOA estimation MIMO radar Coherent targets Uncorrelated targets Array interpolation Modified metrix pencil 

摘      要：Recent research indicates that coprime multiple-input multiple-output (MIMO) radar systems enhance target detection and parameter estimation capabilities due to their unique array configurations. However, despite these advantages, effectively managing scenarios with both coherent and uncorrelated targets requires a delicate balance between computational efficiency and performance accuracy. In this paper, we propose an innovative approach for the joint estimation of the direction of departure (DOD) and direction of arrival (DOA) in coprime MIMO radar systems capable of effectively handling both coherent and uncorrelated targets. We first construct an extended virtual uniform rectangular array (URA) by employing array interpolation, which enhances the system s resolution capabilities. Next, we apply a low-rank structured matrix recovery technique to tackle inherent rank deficiency issues in coherent targets. This approach allows us to estimate the parameters of these targets accurately. We use the full-rank covariance matrix to directly apply the modified matrix pencil (MMP) method for estimating DOD and DOA. This dual-faceted approach automatically pairs estimated parameters without separating processing paths for coherent and uncorrelated targets. Comprehensive simulations indicate the effectiveness of our proposed algorithm in managing mixed target scenarios. It achieves high estimation accuracy and resolution while maintaining computational efficiency.