Train satellite positioning unsupervised deception detection method based on zero deception sample

By employing an unsupervised deception detection method based on zero-deception samples and utilizing a diffusion reconstruction network to learn the time-series graph of satellite signal features, the problems of hardware dependence and data scarcity in existing technologies are solved, achieving efficient and reliable deception detection for train positioning.

CN121069426AActive Publication Date: 2025-12-05BEIJING JIAOTONG UNIV
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Patent Information

Application Number
CN202511144931.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-08-15
Publication Date
2025-12-05
Estimated Expiration
2045-08-15

AI Technical Summary

Technical Problem

Existing deception interference detection methods require the introduction of additional hardware in the railway field, increasing system complexity and cost. At the same time, due to the scarcity of real deception interference data, they suffer from insufficient generalization ability and poor reliability, making it difficult to meet the actual needs of train positioning.

Method used

An unsupervised deception detection method based on zero-deception samples is adopted. By constructing training and validation datasets that do not contain deception interference, a diffusion reconstruction network is used to learn the time series graph of satellite signal features to detect deception attacks in real time. The reconstruction error is quantified by mean square error and structural similarity index to determine the deception attack.

Benefits of technology

This technology improves the reliability of train satellite positioning and the accuracy of spoofing detection without requiring additional hardware, thus ensuring the reliability and real-time protection capabilities of train BeiDou positioning.

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Abstract

The invention provides a train satellite positioning unsupervised deception detection method based on a zero deception sample. The method comprises the following steps: extracting satellite signal related statistical features, constructing a satellite signal feature sequence diagram by taking time as a dimension, and generating a label-free zero-cheating training feature sample set, a label-free zero-cheating verification feature sample set and a test feature sample set by utilizing the satellite signal feature sequence diagram; training the diffusion reconstruction network by using the label-free'zero-cheating 'training feature sample set, and verifying the diffusion reconstruction network by using the verification feature sample set and the test feature sample set to obtain a trained diffusion reconstruction network; inputting the signal characteristic time sequence diagram of the train in the in-transit operation process into the diffusion reconstruction network, calculating a reconstruction error index value, and judging whether the train is subjected to spoofing attack or not based on the reconstruction error index value. According to the invention, real-time detection of deception signals in the train operation process is realized, and effective support is provided for interference protection of a train positioning system.
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