Assessment of particle filter and Kalman filter for estimating velocity using odometery system

Purpose - The purpose of this paper is to propose multisensory integration for train positioning application, to support recent automatic train control systems and also moving block signaling systems.Design methodology approach - Reducing the cost and at the same time improving the reliability and a...

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Vydané v:Sensor review Ročník 30; číslo 3; s. 204 - 209
Hlavní autori: Khodadadi, A., Mirabadi, A., Moshiri, B.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Bradford Emerald Group Publishing Limited 29.06.2010
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ISSN:0260-2288, 1758-6828
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Shrnutí:Purpose - The purpose of this paper is to propose multisensory integration for train positioning application, to support recent automatic train control systems and also moving block signaling systems.Design methodology approach - Reducing the cost and at the same time improving the reliability and accuracy of the overall positioning system, are primary goals of the researches going on in this field.Findings - This paper designs and evaluates two different algorithms of Kalman filtering (KF) and particle filtering (PF), on a set of low cost positioning systems, as tachometers, Doppler radar and balises.Originality value - This paper's research outcomes introduce considerable improvements upon the results when compared to the current utilization of the stand-alone tachometer and Doppler radar sensors, and slight improvements in comparison with the KF algorithm, and also upon results in recent publications on the subject.
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ISSN:0260-2288
1758-6828
DOI:10.1108/02602281011051380