FUSION PREDICTORS FOR DISCRETE-TIME LINEAR SYSTEMS WITH MULTISENSOR ENVIRONMENT

Ha Ryong Song, Vladimir Shin

Abstract

New fusion predictors for linear dynamic systems with different types of observations are proposed. The fusion predictors are formed by summing of the local Kalman filters/predictors with matrix weights depending only on time instants. The relationship between them and the optimal predictor is discussed. High accuracy and computational efficiency of the fusion predictors are demonstrated on the first-order Markov process and the damper harmonic oscillator motion with multisensor environment.

References

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Paper Citation


in Harvard Style

Ryong Song H. and Shin V. (2007). FUSION PREDICTORS FOR DISCRETE-TIME LINEAR SYSTEMS WITH MULTISENSOR ENVIRONMENT . In Proceedings of the Second International Conference on Signal Processing and Multimedia Applications - Volume 1: SIGMAP, (ICETE 2007) ISBN 978-989-8111-13-5, pages 119-124. DOI: 10.5220/0002131201190124


in Bibtex Style

@conference{sigmap07,
author={Ha Ryong Song and Vladimir Shin},
title={FUSION PREDICTORS FOR DISCRETE-TIME LINEAR SYSTEMS WITH MULTISENSOR ENVIRONMENT},
booktitle={Proceedings of the Second International Conference on Signal Processing and Multimedia Applications - Volume 1: SIGMAP, (ICETE 2007)},
year={2007},
pages={119-124},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002131201190124},
isbn={978-989-8111-13-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Second International Conference on Signal Processing and Multimedia Applications - Volume 1: SIGMAP, (ICETE 2007)
TI - FUSION PREDICTORS FOR DISCRETE-TIME LINEAR SYSTEMS WITH MULTISENSOR ENVIRONMENT
SN - 978-989-8111-13-5
AU - Ryong Song H.
AU - Shin V.
PY - 2007
SP - 119
EP - 124
DO - 10.5220/0002131201190124