Journal
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
Volume -, Issue -, Pages -Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TITS.2023.3317786
Keywords
Kalman filters; Predictive models; Covariance matrices; Measurement uncertainty; Intelligent transportation systems; 5G mobile communication; White noise; Extended Kalman filter; train positioning; Taylor higher-order expansion terms
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Ko et al. recently proposed a high-speed railway positioning scheme based on an improved Kalman filter using 5G NR signals. However, our research has shown serious design flaws in the proposed filtering principles, rendering the algorithm infeasible.
Recently, Ko et al. (2022) proposed a high-speed railway positioning scheme based on an improved Kalman filter using 5G NR signals. Although the proposal was promising, our research and analysis have revealed that the method has serious design flaws in the proposed filtering principles, rendering the algorithm infeasible. Specifically, the flaws are related to the computation and usability of high-order terms in the prediction error after Taylor expansion and prediction error derivation.
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