A Particle Swarm Optimization Algorithm for Least Visual Path Problem in Raster Terrain

Least visible path analysis is a basic function in terrain visibility analysis. However, existing least visible path planning is constrained to least-cost path computing on a cost surface got from visibility information of all the terrain points on digital elevation model. This kind of method ignores the overlapped part of the adjacent points´ view sheds. This paper discussed the least visual path problem and proposed a particle swarm optimization algorithm using the amalgamation of view shed to find an optimal covert path. The experimental results show that the new method produces more accurate least visible paths than the traditional one does.