Improving and Interference Immunity of Railway Transport Control Systems

The modern vector of the development of railway transportation logistics puts as the main goals forward uninterrupted and timely delivery of freights to destinations, reducing the time of freight cars turnover, optimizing the process of passengers conveyance. An important role in the implementation of this strategy in the railway sector is assigned to centralized traffic control systems and supervisory control systems. These systems regulates the movement of trains, increase train-handling capacity, and ensure safe and uninterrupted operation of railways. A transmission and reception of information in such systems occurs under simultaneous impact of several interference. Some of the interference are random, and some of them are described by deterministic functions of time. The effect of interference on the receiving device leads to errors in discrimination of information signals and in interpreting of information messages. The average probability Pₑₘ of discrimination error is an objective indicator of the interference immunity of the reception. In this paper, we consider the case of discrimination of three information signals. The interference is the sum of the deterministic sinusoidal and impulse components, as well as Gaussian noise with a uniform spectrum. The discrimination is made by joint parameters estimation of information signals and deterministic interference based on the minimum mean square error criterion. The authors evaluated the potential lower limit for Pₑₘ. It is shown that in a wide range of signal and interference parameters, the potential interference immunity is several orders of magnitude better than the boundary value, which is determined by the requirements for the functional safety of railway control systems.

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    • © Springer Nature Switzerland AG 2020. The contents of this paper reflect the views of the authors and do not necessarily reflect the official views or policies of the Transportation Research Board or the National Academy of Sciences.
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    Springer International Publishing

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  • Authors:
    • Ananieva, Olha
    • Babaiev, Mykhailo
    • Blyndiuk, Vasyl
    • Davidenko, Mykhailo
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  • Publication Date: 2020-1

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  • English

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  • Accession Number: 01874313
  • Record Type: Publication
  • ISBN: 9783030396879
  • Files: TRIS
  • Created Date: Feb 23 2023 9:31AM