Design and Optimization of UAV-Aided ISAC System for Efficient Search and Rescue

Unmanned aerial vehicles (UAVs) are increasingly playing an active role across various industry sectors. Sensing is one of the key prospects, enabling Integrated Sensing and Communication (ISAC)-aided UAVs to operate more effectively in complex situations, particularly in time-critical applications such as search and rescue. This paper proposes a unified design framework for UAV-borne ISAC systems. We first develop a comprehensive propagation model that accounts for both communication links and radar echoes. Then, to address the nonconvexity of jointly optimizing beamforming and power allocation for maximizing target detection probability under transmit power and per-user Signal-to-Interference-plus-Noise Ratio (SINR) constraints, we proposed a semidefinite relaxation (SDR)-based method to reformulate the problem into a convex approximation. Slack variables and penalty factors were introduced to achieve a flexible trade-off between sensing and communication objectives. Numerical results demonstrate that the proposed joint trajectory and beamforming optimization method enabled UAV-borne ISAC platforms to reach a moderate balance between user communication rates and Signal-to-Noise Ratio (SNR) for sensing along the predetermined searching path.