Abstract

In the context of railway safety, it is crucial to know the positions of all trains moving along the infrastructure. In this contribution, we present an algorithm that extracts the positions of moving trains for a given point in time from Distributed Acoustic Sensing (DAS) signals. These signals are obtained by injecting light pulses into an optical fiber close to the railway tracks and measuring the Rayleigh backscatter. We show that the vibrations of moving objects can be identified and tracked in real-time yielding train positions every second. To speed up the algorithm, we describe how the calculations can partly be based on graphical processing units. The tracking quality is assessed by counting the inaccurate and lost train tracks for two different types of cable installations.

Highlights

  • Railway safety is an ever-increasing issue, as traffic demand increases world wide with railways playing an important role

  • We investigate advanced signal processing of the Distributed Acoustic Sensing (DAS) data received from the so-called optical interrogator device for accurate train tracking

  • We will present the signal processing methods used for train tracking, i.e., we will describe in detail how to process the raw measurement data to obtain train trajectories

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Summary

Introduction

Railway safety is an ever-increasing issue, as traffic demand increases world wide with railways playing an important role. This is especially true in the light of the urgent need for the decarbonization of traffic. The accurate tracking of a train’s real position on the track is the basis for all modern railway safety concepts. There is only one train allowed to operate at a time, which is sufficient to prevent collisions of trains. The disadvantage of this concept is a reduced efficiency in the use of the available track infrastructure because long portions of the track stay unused. Reliable, and redundant train tracking technology is an important basis for these novel concepts

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