A Path Planning Method for a Low Observable UAV in Radar Field

In this paper we propose a two-step method for the problem of path planning for a low observable unmanned air vehicle in a radar field. In the first step, we convert the problem into a constrained shortest path problem defined on a directed network graph and then we apply an efficient graph search algorithm for solving it. We implement a probabilistic cost function for the path, assuming an anisotropic vehicle radar cross section. The length of the path is constrained by the maximum range of the vehicle. In the second step, the initial polygonal path is refined using B-Splines. We take the vehicle maneuvering limits into account for the smoothed path.