AntiGPS spoofing method for UAV based on LSTM-KF model - Yang SUN; Chunjie CAO; Junxiao LAI; Tianjiao YU (网络与信息安全学报)
A detection method of anti GPS deception of UAV was proposed for the problem that GPS signal of UAV was easy to be interfered and deceived,which combined deep learning and Kalman filter.The dynamic model of UAV flight was predicted from the flight state of UAV by using long short-term memory network,and the dynamic adjustment of Kalman filter and dynamic model was used to identify GPS deception.In order to resist the interference of GPS deception signal,this method did not need to increase the hardware overhead of the receiver,and was easy to realize.The experimental results show that the method has higher accuracy and lower false alarm rate for the recognition of GPS signals,and can effectively enhance the UAV's ability to resist GPS deception interference.