Intelligent Resource Management and Optimization of Clustered UAV Airborne SAR System

This paper proposes a resource management method of clustered UAV airborne SAR system based on the advanced genetic algorithm (GA). The clustered UAVs is taken as a Multiple Input Multiple Output (MIMO) system for SAR imaging. The imaging result is improved by fusing the images of different UAV nodes from diverse observation angles. By considering spatial configuration of UAV nodes, the transmitting power and frequency band allocation, the system resource management is optimally scheduled for providing a satisfied image fusion results using the niching GA method. From numerical results, the proposed method can offer more features for image fusion when detecting the cloaking target.