UAVs-Borne MIMO Radars Layout Optimization Based on Clustered Signal Integration

This paper considers the layout problem for the unmanned aerial vehicles (UAVs)-borne multi-input multi-output (MIMO) radar system in the situation of signal integration to improve the detection probability and radar effective coverage area (ECA). Because of the coherent constraints between UAV node echo signals, the signals can only be integrated coherently when the distances between nodes are relatively short; otherwise, the signals must be integrated incoherently. Thus, we propose a system model of the clustered UAV MIMO radar based on hybrid integration for the varying distances between the nodes. The model groups the system’s nodes into clusters, where the distance between nodes within the same cluster is small and the distance between nodes from different clusters is larger. A clustering criterion and an approximation of the ECA solution calculation are also included in the model. Then, we propose an optimization solution for radar node placement based on Cuckoo search-particle swarm optimization (CS-PSO). Finally, compared to CS-based, PSO-based, and random deployment methods, the simulation results examine the feasibility and effectiveness of the proposed method.