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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| Published in: | Sensor review Vol. 30; no. 3; pp. 204 - 209 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Bradford
Emerald Group Publishing Limited
29.06.2010
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| ISSN: | 0260-2288, 1758-6828 |
| Online Access: | Get full text |
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| Abstract | 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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| AbstractList | 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. [PUBLICATION ABSTRACT] 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. 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. Designmethodologyapproach 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. Originalityvalue This paper's research outcomes introduce considerable improvements upon the results when compared to the current utilization of the standalone tachometer and Doppler radar sensors, and slight improvements in comparison with the KF algorithm, and also upon results in recent publications on the subject. |
| Author | Moshiri, B. Khodadadi, A. Mirabadi, A. |
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| Keywords | Trains Data analysis Railway engineering Particle size measurement Velocity Programming and algorithm theory |
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| SubjectTerms | Algorithms Bias Computer programming Data analysis Design engineering Doppler effect Doppler radar Engineering Estimating Filtering Measurement Noise Particle size measurement Programming and algorithm theory Railway engineering Sensors Signal processing Studies Tachometers Trains Velocity |
| Title | Assessment of particle filter and Kalman filter for estimating velocity using odometery system |
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