THE SQUARE-ROOT UNSCENTED INFORMATION FILTER FOR STATE ESTIMATION AND SENSOR FUSION

Guoliang Liu, Florentin Wörgötter, Irene Markelić

Abstract

This paper presents a new recursive Bayesian estimation method, which is the square-root unscented information filter (SRUIF). The unscented information filter (UIF) has been introduced recently for nonlinear system estimation and sensor fusion. In the UIF framework, a number of sigma points are sampled from the probability distribution of the prior state by the unscented transform and then propagated through the nonlinear dynamic function and measurement function. The new state is estimated from the propagated sigma points. In this way, the UIF can achieve higher estimation accuracies and faster convergence rates than the extended information filter (EIF). As the extension of the original UIF, we propose to use the square-root of the covariance in the SRUIF instead of the full covariance in the UIF for estimation. The new SRUIF has better numerical properties than the original UIF, e.g., improved numerical accuracy, double order precision and preservation of symmetry.

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Paper Citation


in Harvard Style

Liu G., Wörgötter F. and Markelić I. (2012). THE SQUARE-ROOT UNSCENTED INFORMATION FILTER FOR STATE ESTIMATION AND SENSOR FUSION . In Proceedings of the 1st International Conference on Sensor Networks - Volume 1: SENSORNETS, ISBN 978-989-8565-01-3, pages 169-173. DOI: 10.5220/0003839101690173


in Bibtex Style

@conference{sensornets12,
author={Guoliang Liu and Florentin Wörgötter and Irene Markelić},
title={THE SQUARE-ROOT UNSCENTED INFORMATION FILTER FOR STATE ESTIMATION AND SENSOR FUSION},
booktitle={Proceedings of the 1st International Conference on Sensor Networks - Volume 1: SENSORNETS,},
year={2012},
pages={169-173},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003839101690173},
isbn={978-989-8565-01-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 1st International Conference on Sensor Networks - Volume 1: SENSORNETS,
TI - THE SQUARE-ROOT UNSCENTED INFORMATION FILTER FOR STATE ESTIMATION AND SENSOR FUSION
SN - 978-989-8565-01-3
AU - Liu G.
AU - Wörgötter F.
AU - Markelić I.
PY - 2012
SP - 169
EP - 173
DO - 10.5220/0003839101690173