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

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.

Citation

Khodadadi, A., Mirabadi, A. and Moshiri, B. (2010), "Assessment of particle filter and Kalman filter for estimating velocity using odometery system", Sensor Review, Vol. 30 No. 3, pp. 204-209. https://doi.org/10.1108/02602281011051380