Implementation and Analysis of Pattern Propagation Factor Based Radar Model for Path Planning

Various path planning algorithms assume space as free and obstacles, and it is widely used in the robotic field. In examples of flight objects, space cannot be simply divided as free and obstacles because a risk exposure factor in the sky is dramatically changed based on radar sites and earth terrain. Previous researchers did not consider the risk exposure or used simple radar model to estimate the risk exposure. In this paper, a radar model based on pattern propagation factor is implemented to estimate the risk exposure. The model can simulate effects of terrain masking, 3D radar cross-section, refraction, and radar multipath, and compared paths with deterministic (Dijkstra’s algorithm), evolutionary (Discrete Genetic Algorithm), and Voronoi path planning methods.