2014
DOI: 10.1109/tits.2014.2349353
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Performance Evaluation of GNSS for Train Localization

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Cited by 34 publications
(29 citation statements)
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“…Inside the GNSS community, system performances are qualified by four criteria: availability, continuity, accuracy and integrity. These performances, mainly driven by aeronautics and specified by the ICAO, do not have direct correspondence to railway requirement criteria, usually qualified in terms of reliability, availability, maintainability and safety (RAMS) as represented by [28] on figure 4. A particular example concerns the "integrity" word.…”
Section: A How To Qualify Required Gnss Performances In the Railwaymentioning
confidence: 99%
“…Inside the GNSS community, system performances are qualified by four criteria: availability, continuity, accuracy and integrity. These performances, mainly driven by aeronautics and specified by the ICAO, do not have direct correspondence to railway requirement criteria, usually qualified in terms of reliability, availability, maintainability and safety (RAMS) as represented by [28] on figure 4. A particular example concerns the "integrity" word.…”
Section: A How To Qualify Required Gnss Performances In the Railwaymentioning
confidence: 99%
“…The normalized earth field corresponds to the (unknown) position of factory calibration. The signal of the magnitude indicates the resulting magnetic fields by superposition as described in (2). The cabin sensor shows a significant attenuation compared to the bogie signal.…”
Section: Magnetic Data Setmentioning
confidence: 99%
“…Global Navigation Satellite System (GNSS) position measurements are useful for train localization, but satellite geometry or reception can be poor or not available parts of the railway environment. A stand-alone GNSS receiver cannot fulfill the requirements for safety-of-life train localization, in particular in parallel track scenarios and in tunnels [2]. Therefore, onboard train localization is often addressed by multisensor approaches as in [1,3,4].…”
Section: Introductionmentioning
confidence: 99%
“…In railway system applications, the SF-based localization method was first introduced in [6] using linear Kalman filter (KF) framework. Various SF-based localization methods were subsequently developed using such methods as extended Kalman filter (EKF) [7] and its combination with GNSS [8]- [10], map matching [11], probabilistic weighted fusion [12], visual-aided odometry [13], particle filtering [14] and probabilistic data fusion [15]. See e.g.…”
Section: Introductionmentioning
confidence: 99%