AntiGPS spoofing method for UAV based on LSTM-KF model

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...

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Main Authors: Yang SUN, Chunjie CAO, Junxiao LAI, Tianjiao YU
Format: Article
Language:English
Published: POSTS&TELECOM PRESS Co., LTD 2020-10-01
Series:网络与信息安全学报
Subjects:
Online Access:http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2020069
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author Yang SUN
Chunjie CAO
Junxiao LAI
Tianjiao YU
author_facet Yang SUN
Chunjie CAO
Junxiao LAI
Tianjiao YU
author_sort Yang SUN
collection DOAJ
description 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.
format Article
id doaj-art-01958a67fddd4786a85f464dc84f7888
institution DOAJ
issn 2096-109X
language English
publishDate 2020-10-01
publisher POSTS&TELECOM PRESS Co., LTD
record_format Article
series 网络与信息安全学报
spelling doaj-art-01958a67fddd4786a85f464dc84f78882025-08-20T02:42:29ZengPOSTS&TELECOM PRESS Co., LTD网络与信息安全学报2096-109X2020-10-016808859560966AntiGPS spoofing method for UAV based on LSTM-KF modelYang SUNChunjie CAOJunxiao LAITianjiao YUA 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.http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2020069UAVGPSanti spoofinglong short-term memory networkKalman filter
spellingShingle Yang SUN
Chunjie CAO
Junxiao LAI
Tianjiao YU
AntiGPS spoofing method for UAV based on LSTM-KF model
网络与信息安全学报
UAV
GPS
anti spoofing
long short-term memory network
Kalman filter
title AntiGPS spoofing method for UAV based on LSTM-KF model
title_full AntiGPS spoofing method for UAV based on LSTM-KF model
title_fullStr AntiGPS spoofing method for UAV based on LSTM-KF model
title_full_unstemmed AntiGPS spoofing method for UAV based on LSTM-KF model
title_short AntiGPS spoofing method for UAV based on LSTM-KF model
title_sort antigps spoofing method for uav based on lstm kf model
topic UAV
GPS
anti spoofing
long short-term memory network
Kalman filter
url http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2020069
work_keys_str_mv AT yangsun antigpsspoofingmethodforuavbasedonlstmkfmodel
AT chunjiecao antigpsspoofingmethodforuavbasedonlstmkfmodel
AT junxiaolai antigpsspoofingmethodforuavbasedonlstmkfmodel
AT tianjiaoyu antigpsspoofingmethodforuavbasedonlstmkfmodel