基于航迹规划的无人机地形辅助导航

A terrain-aided navigation method based on track planning is proposed in this paper to improve the poor adaptability and real-time performance of unmanned aerial vehicle (UAV) terrain-aided navigation based on terrain contour matching. To solve the problem of terrain matching being highly dependent on terrain, the area that UAVs must approach is divided into blocks, and the terrain standard deviation of each block is calculated. The flat terrain area and the terrain undulating area are then selected based on the terrain standard deviation, while the flight track planning algorithm is used to plan the route for UAV in the area with large terrain undulating. The idea of distribution estimation is introduced on the basis of the particle swarm optimization (PSO) algorithm with the aim of addressing the time-consuming problem of traditional traversal search elevation matching algorithms. This proposed solution can form the optimized PSO algorithm for terrain contour matching and enhance global optimization ability. The simulation results show that the optimized PSO reduced the matching time by 2 / 3. Furthermore, the terrain-aided navigation based on track planning improved matching accuracy by 6 / 7.