A New Covariance-assignment State Estimator in the Presence of Intermittent Observation Losses

Sangho Ko, Seungeun Kang, Jihyoung Cha

Abstract

This paper introduces an improved linear state estimator which directly assigns the error covariance in an environment where the measured data are intermittently missing. Since this new estimator uses an additional information indicating whether each observation is successfully measured, represented as a bernoulli random variable in the measurement equation, it naturally outperforms the previous type of covariance-assignment estimators which do not rely upon such information. This fact is proved by comparing the magnitude of the state error covariances via the monotonicity of the Riccati difference equation, and demonstrated using a numerical example.

References

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Paper Citation


in Harvard Style

Ko S., Kang S. and Cha J. (2014). A New Covariance-assignment State Estimator in the Presence of Intermittent Observation Losses . In Proceedings of the 3rd International Conference on Sensor Networks - Volume 1: SENSORNETS, ISBN 978-989-758-001-7, pages 279-284. DOI: 10.5220/0004673902790284


in Bibtex Style

@conference{sensornets14,
author={Sangho Ko and Seungeun Kang and Jihyoung Cha},
title={A New Covariance-assignment State Estimator in the Presence of Intermittent Observation Losses},
booktitle={Proceedings of the 3rd International Conference on Sensor Networks - Volume 1: SENSORNETS,},
year={2014},
pages={279-284},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004673902790284},
isbn={978-989-758-001-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 3rd International Conference on Sensor Networks - Volume 1: SENSORNETS,
TI - A New Covariance-assignment State Estimator in the Presence of Intermittent Observation Losses
SN - 978-989-758-001-7
AU - Ko S.
AU - Kang S.
AU - Cha J.
PY - 2014
SP - 279
EP - 284
DO - 10.5220/0004673902790284