WANG Ershen, YANG Di, WANG Chuanyun, et al., “Optimized Fault Detection Algorithm Aided by BDS Baseband Signal for Train Positioning,” Chinese Journal of Electronics, vol. 29, no. 1, pp. 34-40, 2020, doi: 10.1049/cje.2019.09.004
Citation: WANG Ershen, YANG Di, WANG Chuanyun, et al., “Optimized Fault Detection Algorithm Aided by BDS Baseband Signal for Train Positioning,” Chinese Journal of Electronics, vol. 29, no. 1, pp. 34-40, 2020, doi: 10.1049/cje.2019.09.004

Optimized Fault Detection Algorithm Aided by BDS Baseband Signal for Train Positioning

doi: 10.1049/cje.2019.09.004
Funds:  This work is supported by the National Natural Science Foundation of China (No.61571309, No.61703287), Liaoning Baiqianwan Talents Program (No.04021407), Natural Science Foundation of Liaoning Province (No.2019-MS-251), Scientific Study Project for Liaoning Province Ministry of Education(No.L201705, No.L201716), and Liaoning Excellent Talents in University (No.LR2016069).
  • Received Date: 2019-04-01
  • Rev Recd Date: 2019-11-26
  • Publish Date: 2020-01-10
  • The satellite navigation integrity monitoring technology is closely related to the reliability of train positioning. It is of great significance to study satellite navigation Receiver autonomous integrity monitoring (RAIM) algorithm suitable for train positioning. Some existing conventional RAIM algorithms do not consider the influence of satellite navigation signal on algorithms performance. Aiming at the influence of satellite navigation signal on the propagation processes, such as shadow and multipath effects, the fault detection algorithm based on BeiDou navigation satellite system (BDS) baseband signal is proposed. The innovation parameters contained in the satellite navigation baseband signal are combined into the covariance matrix to set up a new test statistics of RAIM. A new fault detection algorithm based on optimized BDS baseband signal is discussed. And combined with weighted least square method, the noise power balance factor is established to realize satellite fault detection. Experimental results show that the proposed algorithm can improve the monitoring performance of train satellite positioning integrity, and lay the foundation for meeting the railway industry's security requirements for positioning services.
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