Optimal Configuration of Array Elements for Hybrid Distributed PA-MIMO Radar System Based on Target Detection

Abstract

Abstract How to utilize limited system resources budget to maximize the effectiveness potential of the entire system through optimal allocation has always been a hot issue in radar resource management. This paper establishes a hybrid distributed phased array multiple-input and multiple-output (PA-MIMO) radar system model. It combines coherent processing gain and spatial diversity gain to synergistically improve the target detection performance of the radar system. For the hybrid distributed PA-MIMO radar system, we derive a likelihood ratio (LRT) detector based on the Neyman-Pearson (NP) criterion. The coherent processing gain and spatial diversity gain are jointly optimized by implementing subarray-level and array element-level optimal configuration at both transceiver and transmitter ends. Moreover, a quantum particle swarm optimization-based stochastic rounding (SR-QPSO) solution algorithm is proposed for the integer planning-based configuration model. And the optimal array element configuration strategy is guaranteed to be obtained with fewer iterations and realize the joint optimization between subarray and array levels. Finally, numerical simulations are carried out using three typical optimization problems to demonstrate the effectiveness of the optimal configuration of the hybrid distributed PA-MIMO radar system.