Optimizing Multi-UAV 3D Deployment for Energy-Efficient Sensing over Uneven Terrains

In this work, we present a terrain-aware 3D multi-unmanned aerial vehicles (UAV) cooperative spectrum sensing (CSS) framework that jointly optimizes UAV placement and antenna orientation to maximize detection probability while minimizing hover energy. A bounding volume hierarchy (BVH)-based adaptive scheme is proposed for efficient line-of-sight (LoS) evaluation, and a hierarchical genetic algorithm (GA)–particle swarm optimization (PSO) approch is adopted to address the inherently non-convex bi-objective problem, achieving a balanced exploration of the search space while ensuring LoS connectivity and energy efficiency. Monte Carlo simulations using real terrain data demonstrate up to 37.02% improvement in detection probability and 48.90% reduction in hover energy compared to PSO-only baselines, confirming the practicality and effectiveness of the proposed framework for uneven terrain environments.