Sparse-based direction finding in MIMO radar with mutual coupling

Abstract

In this study, an estimation problem for target directions in the multiple-input and multiple-output (MIMO) radar system with unknown mutual coupling is considered. To exploit the target sparsity in the spatial domain, a compressed sensing-based method using multiple measure vectors is proposed to reconstruct the sparse targets and estimate the target directions and scattering coefficients. Additionally, we also propose an iterative method to estimate the mutual coupling matrices after obtaining the target information, where the sub-gradients are derived theoretically to update the mutual coupling matrices. Simulation results show that compared with the exiting methods, the better estimation performance for both target directions and mutual coupling matrices can be achieved by the proposed method.

Keywords

• MIMO radar
• compressed sensing
• MIMO communication
• image reconstruction
• matrix algebra
• iterative methods
• direction-of-arrival estimation
• multiple-input
• multiple-output
• unknown mutual coupling
• target sparsity
• compressed sensing-based method
• multiple measure vectors
• sparse targets
• target directions
• mutual coupling matrices
• target information
• estimation performance
• sparse-based direction finding
• MIMO radar
• estimation problem