Chinese Journal of Network and Information Security ›› 2020, Vol. 6 ›› Issue (5): 80-88.doi: 10.11959/j.issn.2096-109x.2020069

• Papers • Previous Articles     Next Articles

AntiGPS spoofing method for UAV based on LSTM-KF model

Yang SUN1,2,3,Chunjie CAO1,2,3(),Junxiao LAI1,2,Tianjiao YU1,2   

  1. 1 Key Laboratory of Internet Information Retrieval of Hainan Province,Haikou 570228,China
    2 College of Computer and cyberspace security,Hainan University,Haikou 570228,China
    3 China State Key Laboratory of Marine Resource Utilization in South China Sea,Haikou 570228,China
  • Revised:2020-03-31 Online:2020-10-15 Published:2020-10-19
  • Supported by:
    The National Natural Science Foundation of China(61661019);The State Key Program of National Natural Science Foundation of China(U19B2044);Key Project of Education Teaching Reform Research in Higher Education Institutions in Hainan Province(Hnjg2017ZD-1)

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Abstract:

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.

Key words: UAV, GPS, anti spoofing, long short-term memory network, Kalman filter

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