Route planning method for UAV in unknown environment based on improved SAS algorithm

Unmanned aerial vehicle (UAV) real-time target tracking in an unknown environment can be considered as a route planning problem. Aiming at this problem, this paper proposes a three-dimensional (3D) route planning method based on an improved sparse A* search(SAS) algorithm. This method improves the evaluation function. The actual cost in the evaluation function of the SAS algorithm is removed, and the threat information in the mission environment is constructed as part of the evaluation function to guide the UAV to move away from the threat area. The planned trajectory in this method takes into account the updating of real-time environmental information and can achieve real-time trajectory planning. Furthermore, the filtering effect of singer model, current "statistical" model, and interactive multi-model (IMM) algorithm are compared and the current "statistical" model is finally chosen as the maneuvering target tracking model.