Minimum Redundancy Planar Coarrays for High-Resolution MIMO Radar Imaging

This paper presents a minimum redundancy planar coarray design for high-resolution MIMO radar imaging. By leveraging sparse antenna configurations, the proposed approach enhances angular resolution while minimizing redundant spacings in the virtual array. A joint range-Doppler estimator is developed based on a four-dimensional transmit-receive signal model, facilitating multi-target localization in azimuth and elevation. To minimize the spatial sampling requirements, a combinatorial formulation is introduced for designing planar MIMO minimum redundancy arrays, ensuring a continuous coarray structure with fewer physical elements and exploiting filled coarray locations with FFT-based angle spectra for markedly enhanced computational efficiency over adaptive techniques and sparse recovery methods. Numerical simulations demonstrate that the proposed coarray-based MIMO radar achieves superior resolution compared to conventional filled arrays while effectively suppressing grating lobes. This work provides a cost-efficient solution for highprecision radar imaging applications.