Synchronous GPS Spoofing Identification Based on K-means Clustering

WANG Yiwei; LU Yin; KOU Yanhong; LAN Xiaoyang; HUANG Zhigang

doi:10.11999/JEIT230837

Volume 45 Issue 11

Nov. 2023

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Article Navigation > Journal of Electronics & Information Technology > 2023 > 45(11): 4137-4149

WANG Yiwei, LU Yin, KOU Yanhong, LAN Xiaoyang, HUANG Zhigang. Synchronous GPS Spoofing Identification Based on K-means Clustering[J]. Journal of Electronics & Information Technology, 2023, 45(11): 4137-4149. doi: 10.11999/JEIT230837

Citation:

WANG Yiwei, LU Yin, KOU Yanhong, LAN Xiaoyang, HUANG Zhigang. Synchronous GPS Spoofing Identification Based on K-means Clustering[J]. Journal of Electronics & Information Technology, 2023, 45(11): 4137-4149. doi: 10.11999/JEIT230837

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Synchronous GPS Spoofing Identification Based on K-means Clustering

doi: 10.11999/JEIT230837

1.
School of Electronics and Information Engineering, Beihang University, Beijing 100083, China
2.
Laboratory of Science and Technology on Marine Navigation and Control, Tianjin 300131, China

Funds: The Open Fund of Laboratory of Science and Technology on Marine Navigation and Control (2022010102)

Received Date: 2023-08-02
Rev Recd Date: 2023-10-30

Available Online: 2023-11-04

Publish Date: 2023-11-28

Abstract

Abstract

To solve the problem of distinguishing highly-concealed synchronous spoofing signals from authentic signals inside a GPS receiver, a spoofing identification method based on clustering analysis of multiple characteristics is proposed. The procedure of baseband anti-spoofing processing is summarized. On the basis of spoofing detection and signal parameter estimation, the Code-Carrier Doppler frequency Coherence (CCDC), relative amplitude, and carrier-to-noise ratio variation characteristics are extracted as the spoofing identification characteristics at the signal processing level. At the information processing level, the pseudo-range residual corresponding to the combination of different signal components and the receiver clock variation before and after the spoofing attack are calculated. Then the K-means clustering is used to identify the spoofing signal combining these characteristics. The semi-physical experiment based on Radio Frequency (RF) signal sampling and playback and the processing results of our anti-spoofing software receiver demonstrate that the proposed method can identify synchronous spoofing timely and accurately, thus guiding the receiver to mitigate the effects of spoofing and recover correct navigation solutions.
- GPS,
- Synchronous spoofing,
- Anti-spoofing,
- Interference identification,
- K-means clustering

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References(24)

References

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