AntiGPS spoofing method for UAV based on LSTM-KF model

Yang SUN; Chunjie CAO; Junxiao LAI; Tianjiao YU

doi:10.11959/j.issn.2096-109x.2020069

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AntiGPS spoofing method for UAV based on LSTM-KF model

Papers | 更新时间：2024-06-03

- AntiGPS spoofing method for UAV based on LSTM-KF model
- Chinese Journal of Network and Information Security Vol. 6, Issue 5, Pages: 80-88(2020)
- 作者机构：
  
  1. 海南省Internet信息检索重点实验室，海南海口 570228
  2. 海南大学计算机与网络空间安全学院，海南海口 570228
  3. 南海海洋资源利用国家重点实验室，海南海口570228
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-109x.2020069
  CLC： TP393
- Online First：2020-10，
  
  Published：15 October 2020
- 稿件说明：
移动端阅览
Yang SUN, Chunjie CAO, Junxiao LAI, et al. AntiGPS spoofing method for UAV based on LSTM-KF model[J]. Chinese Journal of Network and Information Security, 2020, 6(5): 80-88.
DOI：

Yang SUN, Chunjie CAO, Junxiao LAI, et al. AntiGPS spoofing method for UAV based on LSTM-KF model[J]. Chinese Journal of Network and Information Security, 2020, 6(5): 80-88. DOI： 10.11959/j.issn.2096-109x.2020069.

摘要

针对无人机 GPS 信号易受干扰、易欺骗的问题，提出一种结合深度学习和卡尔曼滤波的无人机抗GPS欺骗的检测方法，该方法通过使用长短期记忆网络从无人机飞行状态中预测得到无人机飞行的动力学模型，并利用卡尔曼滤波结合动力学模型进行动态调整来识别GPS欺骗，从而达到抵御GPS欺骗信号干扰的目的，同时该方法无须增加接收器的硬件开销，且易于实现。实验结果证明，相比同类方法，该方法对于识别GPS信号具有更高的准确率和更低的误报率，可有效增强无人机抗GPS欺骗干扰的能力。

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.

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Keywords

references

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