Joint Trajectory and Power Optimization for UAV-SAR based ISAC System

Integrated Sensing and Communication (ISAC) for unmanned aerial vehicles (UAVs) has emerged as a promising paradigm for next-generation wireless systems. In this paper, we address the joint problem of resource allocation and trajectory planning for a UAV platform that integrates synthetic aperture radar (SAR) imaging and communication capabilities. The UAV operates at a fixed altitude, performing high-resolution SAR imaging of designated target areas in spotlight mode while simultaneously transmitting the collected data to a ground data center in real time. Given that the total energy consumption significantly impacts the overall performance of the UAV-SAR based ISAC system, we reformulate the trajectory planning task as a non-convex optimization problem focused on selecting optimal entry points into predefined sensing areas, with the objective of minimizing the UAV’s total energy expenditure. To solve this challenging problem, we propose an efficient optimization algorithm that achieves a high-quality suboptimal solution. Extensive simulations validate the effectiveness of the proposed hybrid algorithm, which incorporates Genetic Algorithm (GA) for speed planning. It achieves faster convergence than the conventional GA-ACO method and outperforms Particle Swarm Optimization (PSO) with 3.74% reduction in total system energy consumption.