UAV Path Replanning Based on BeiDou Short Message Communication Function

In this paper, we study the unmanned aerial vehicle (UAV) path replanning problem based on BeiDou short messages which can provide reliable position information in environments with weak Global Navigation Satellite System (GNSS) signals. First, we analyze the error characteristics of the inertial navigation system (INS) with the BeiDou short message communication function as its auxiliary source, and establish the UAV position uncertainty model. Then, the path replanning problem for the UAV with the BeiDou short message communication function is rigorously formulated, which takes the path length, path safety, energy consumption, and position uncertainty into account. To solve this path replanning problem, we propose a particle swarm optimization-based improved interfered fluid dynamical system (PSO-IIFDS) algorithm. Simulation results show that the proposed replanning method can significantly improve the task success rate, which corroborates the effectiveness of our design.