Element Configuration Optimization of Hybrid Distributed PA-MIMO Radar System Based on Target Detection

Abstract

This paper establishes a hybrid distributed Phased-Array Multiple-Input Multiple-Output (PA-MIMO) radar system model, which combines coherent processing gain and spatial diversity gain to synergistically improve the target detection performance. We derive a Likelihood Ratio Test (LRT) detector based on the Neyman-Pearson (NP) criterion for the hybrid distributed PA-MIMO radar system. The coherent processing gain and spatial diversity gain are jointly optimized by implementing subarray-level and array element–level optimal configurations at the transceiver and transmitter ends. Moreover, a Quantum Particle Swarm Optimization-based Stochastic Rounding (SR-QPSO) algorithm is proposed for the integer programming-based configuration model. This algorithm ensures that the optimal array-element configuration strategy is obtained with less iteration and achieves the joint optimization of subarray and array-element levels. Finally, simulations verify that the proposed optimal configuration offers substantial improvements compared to other typical radar systems, with a detection probability of 0.98 and an effective range of 1166.3 km, as well as a considerably improved detection performance.

Keywords

• radar resource optimization
• target detection
• array element configuration
• pa-mimo radar
• coherent gain
• space diversity gain