Low-Detectability UAV Trajectory Optimization in Complex Mountainous Environments

Abstract

Unmanned Aerial Vehicles (UAVs) have been widely adopted in civil, military and industrial application fields owing to their advantages of flexible maneuverability, controllable costs and zero casualty risk, and are expanding to the field of low-altitude precise operations. Their operational reliability and efficiency in complex environments are becoming increasingly critical. In the scenario of UAV penetrating operations in complex terrain, the defense side needs to optimize the layout and deployment strategy of detection equipment relying on the existing low-altitude detection system, and the operation platform needs to plan an optimized path to avoid multi-source detection and safely cross complex terrain. This is the core technical bottleneck to solve the UAV operational safety and the improvement of low-altitude defense efficiency in complex environments. This paper conducts research from a two-way antagonistic perspective: from the perspective of the defense side, a radar anti-UAV detection probability calculation model is constructed, the radar detection probability is solved through multi-constraint conditions, and the evolution law of cumulative detection probability under time-varying detection probability is analyzed by using Markov chain; from the perspective of the operation platform, an improved A* trajectory planning algorithm is proposed to realize path planning with the minimum radar detection probability under multiple constraints. Simulation results demonstrate that trajectory optimization can reduce the joint radar detection probability to 0%. This validates the effectiveness of the proposed model for UAV concealed operations in complex mountainous terrain.