Effective 3-D Path Planning for UAV in Presence of Threat Netting

In this paper, an improved ant colony algorithm is proposed to solve the 3-D path planning problem for UAVs in presence of threat netting. In consideration of the maneuverability constraints of low-altitude penetration UAVs, a safe flying surface is achieved with an integrated smoothing method act on the original terrain. Threat netting is formed with several radar units, and then an integrated cost model based on fuel consumption and threat probability is established after analyzing the influence that radar threat netting has upon path planning. To overcome the shortcomings of traditional ant colony algorithm such as searching too long and easily trapping into local optimum, distance information and threat probability are both integrated into state transition probability, and a modified pheromone concentration update method is also given. On facing sudden threats, a combination method of artificial potential field and ACO algorithm is adopted to conduct real-time planning. Simulation results show that the improved method solves the problems of traditional algorithm and obtains the optimized 3-D path in presence of radar threat netting, the real-time planning method is fast and accurate which can ensure UAV safety.