Multi UAV Trajectory Tracking Optimization Method Based on Fuzzy Graph Convolution Neural Network

Multi-UAV coordinated trajectory tracking is the most popular research problem at present. It is necessary to optimize and adjust the combined course of multiple UAVs and the motion trajectory of UAVs in real-time, and constantly pursue the dynamic optimal configuration between multiple UAVs and targets to improve and stabilize the positioning accuracy. Given the shortcomings of traditional centralized optimization methods, this paper proposes an advanced fuzzy graph convolution neural network model (FGTT). Because of the multi unmanned multi-source target and the irregular geometric structure, the graph convolution neural network can better optimize and process the trajectory tracking optimization method in non-European space. Several groups of verification show that this method can achieve higher tracking accuracy faster than traditional methods, The stability and accuracy of location and tracking are improved.