Enhanced Multitarget Detection With Optimal Sparse MIMO Radar Architecture by Polynomial Interpolation Method

Multi-target detection is an important scientific proposition for millimeter-wave multiple-input multiple-output (MIMO) radar systems. Due to the short wavelength at millimeter-wave bands, multi-channel MIMO arrays are typically realized with very dense element spacing (often on the order of λ/2), which corresponds to only millimeter-level physical separation. It increases near-field interaction and parasitic coupling through the feed or package, making mutual coupling between adjacent channels severe and deteriorating the sensing performance. However, conventional decoupling methods unavoidably increase system hardware complexity, rendering them incompatible with compact sensing platforms. As a result, sparse MIMO radar supposes to be an efficient solution. Meanwhile, the non-uniform virtual co-array generated by sparse configurations typically contains missing lags, defined as holes, leading to incomplete virtual-aperture measurements and may degrade DOA resolution and multi-target separability. Conventional used interpolation-based methods utilize the convex optimization algorithm to fill in the holes, which significantly elevates computational complexity. In this paper, we proposed an enhanced multi-target detection approach using optimal sparse millimeter-wave radar architecture and polynomial interpolation method to reduce mutual coupling among different sensing channels. In this system, a lightweight sparse MIMO radar array configuration is proposed firstly. Then, the polynomial interpolation method is introduced to achieve DOF enhancement with lower computational and hardware complexity than traditional convex-optimization-based methods. Finally, the proposed approach is experimentally validated through multi-target detection scenarios, successfully identifying 8(6) targets using a 5(4) sensing channels. Simulation and experimental results demonstrate the superiority of the proposed sparse MIMO radar architecture over multi-target detection performance and computational complexity, offering a practical solution for diverse MIMO radar sensing platforms.