A Multi-Objective Optimization Method based on Dimensionality Reduction Mapping for Path Planning of a HALE UAV

Abstract

The high-altitude long-endurance (HALE) unmanned aerial vehicles (UAV) have long flight distance and wide range of path coverage, mainly used to perform reconnaissance and strike missions. The distances of such UAVs need to be considered in calculation of the deviation caused by the curvature of the Earth. To avoid negative effects of the distances to path planning, in this paper, we proposed a path planning method based on dimensionality reduction mapping. First, we use Gauss positive projection to project the route data and the threat information from the geodetic coordinates to the Gauss plane coordinates to perform dimensionality reduction mapping. Then, we use multi-objective optimization Dijkstra algorithm to obtain the optimal path with minimum total cost. Finally, Gauss inverse projection is applied to restore the optimal path at the geodetic coordinate system, providing the navigation information for HALE UAV. The simulation results have demonstrated that the method is suitable for calculating a path with large latitude and longitude range, and can be effectively used for path planning of a HALE UAV.