Jamming Identification for GNSS-based Train Localization based on Singular Value Decomposition

Train localization based on the Global Navigation Satellite System (GNSS) is an important feature of the novel train control systems. Considering the complicated railway operation conditions, jamming signals from the environment may pose a severe threat to the GNSS-based train localization. Therefore, the accurate detection and perception of GNSS jamming will play a significant role in ensuring the safe operation of the trains. In this paper, a jamming identification method for GNSS-based train localization using singular value decomposition (SVD) is proposed. By extracting feature values from the singular value sequence, and modeling the mapping relationship between the feature values and the jamming characteristics, the discrimination of jamming characteristics, including the type and the power of the jamming signal, is achieved. A satellite signal-level test platform with the jamming signal injection capability is built to verify the proposed solution. Results of the tests demonstrate the jamming recognition performance of the proposed solution under the Continuous Wave Interference (CWI), Linear Frequency Modulation (LFM) and the Band-limited White Noise (BLWN) jamming conditions.