The effect of sensor health on state estimation

Ling Shi; Michael Epstein; Richard M. Murray

doi:10.1109/cdc.2006.377482

The effect of sensor health on state estimation

Ling Shi^*, Michael Epstein, Richard M. Murray

^*Corresponding author for this work

Research output: Chapter in Book/Conference Proceeding/Report › Conference Paper published in a book › peer-review

2 Citations (Scopus)

Abstract

In this paper, we consider the problem of state estimation using the standard Kalman filter recursions which takes account of the available sensor health information. Given a stochastic description of the sensor health, we are able to show that the expected error covariance converges to a unique value for all initial values, while the available previous work only showed the upper bound of the expected error covariance converges. Our approach provides both theoretical value to the analysis as well as the potential to get tighter upper bound. Our results provide a criterion of evaluating the sensor measurement. In the multisensor fusion problem, depending on the system error tolerance levels, it can then be determined whether to fuse a particular sensor measurement or not. Examples and simulations are provided to assist the theory.

Original language	English
Title of host publication	Proceedings of the 45th IEEE Conference on Decision and Control 2006, CDC
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	3315-3320
Number of pages	6
ISBN (Print)	1424401712, 9781424401710
DOIs	https://doi.org/10.1109/cdc.2006.377482
Publication status	Published - 2006
Externally published	Yes
Event	45th IEEE Conference on Decision and Control 2006, CDC - San Diego, CA, United States Duration: 13 Dec 2006 → 15 Dec 2006

Publication series

Name	Proceedings of the IEEE Conference on Decision and Control
ISSN (Print)	0743-1546
ISSN (Electronic)	2576-2370

Conference

Conference	45th IEEE Conference on Decision and Control 2006, CDC
Country/Territory	United States
City	San Diego, CA
Period	13/12/06 → 15/12/06

Access to Document

10.1109/cdc.2006.377482

Cite this

@inproceedings{4e1b75a2875f422da2e0ad78a11b1a9f,

title = "The effect of sensor health on state estimation",

abstract = "In this paper, we consider the problem of state estimation using the standard Kalman filter recursions which takes account of the available sensor health information. Given a stochastic description of the sensor health, we are able to show that the expected error covariance converges to a unique value for all initial values, while the available previous work only showed the upper bound of the expected error covariance converges. Our approach provides both theoretical value to the analysis as well as the potential to get tighter upper bound. Our results provide a criterion of evaluating the sensor measurement. In the multisensor fusion problem, depending on the system error tolerance levels, it can then be determined whether to fuse a particular sensor measurement or not. Examples and simulations are provided to assist the theory.",

author = "Ling Shi and Michael Epstein and Murray, \{Richard M.\}",

year = "2006",

doi = "10.1109/cdc.2006.377482",

language = "English",

isbn = "1424401712",

series = "Proceedings of the IEEE Conference on Decision and Control",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "3315--3320",

booktitle = "Proceedings of the 45th IEEE Conference on Decision and Control 2006, CDC",

note = "45th IEEE Conference on Decision and Control 2006, CDC ; Conference date: 13-12-2006 Through 15-12-2006",

}

Shi, L, Epstein, M & Murray, RM 2006, The effect of sensor health on state estimation. in Proceedings of the 45th IEEE Conference on Decision and Control 2006, CDC., 4177794, Proceedings of the IEEE Conference on Decision and Control, Institute of Electrical and Electronics Engineers Inc., pp. 3315-3320, 45th IEEE Conference on Decision and Control 2006, CDC, San Diego, CA, United States, 13/12/06. https://doi.org/10.1109/cdc.2006.377482

The effect of sensor health on state estimation. / Shi, Ling; Epstein, Michael; Murray, Richard M.
Proceedings of the 45th IEEE Conference on Decision and Control 2006, CDC. Institute of Electrical and Electronics Engineers Inc., 2006. p. 3315-3320 4177794 (Proceedings of the IEEE Conference on Decision and Control).

Research output: Chapter in Book/Conference Proceeding/Report › Conference Paper published in a book › peer-review

TY - GEN

T1 - The effect of sensor health on state estimation

AU - Shi, Ling

AU - Epstein, Michael

AU - Murray, Richard M.

PY - 2006

Y1 - 2006

N2 - In this paper, we consider the problem of state estimation using the standard Kalman filter recursions which takes account of the available sensor health information. Given a stochastic description of the sensor health, we are able to show that the expected error covariance converges to a unique value for all initial values, while the available previous work only showed the upper bound of the expected error covariance converges. Our approach provides both theoretical value to the analysis as well as the potential to get tighter upper bound. Our results provide a criterion of evaluating the sensor measurement. In the multisensor fusion problem, depending on the system error tolerance levels, it can then be determined whether to fuse a particular sensor measurement or not. Examples and simulations are provided to assist the theory.

AB - In this paper, we consider the problem of state estimation using the standard Kalman filter recursions which takes account of the available sensor health information. Given a stochastic description of the sensor health, we are able to show that the expected error covariance converges to a unique value for all initial values, while the available previous work only showed the upper bound of the expected error covariance converges. Our approach provides both theoretical value to the analysis as well as the potential to get tighter upper bound. Our results provide a criterion of evaluating the sensor measurement. In the multisensor fusion problem, depending on the system error tolerance levels, it can then be determined whether to fuse a particular sensor measurement or not. Examples and simulations are provided to assist the theory.

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UR - https://openalex.org/W2114126144

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M3 - Conference Paper published in a book

SN - 1424401712

SN - 9781424401710

T3 - Proceedings of the IEEE Conference on Decision and Control

SP - 3315

EP - 3320

BT - Proceedings of the 45th IEEE Conference on Decision and Control 2006, CDC

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 45th IEEE Conference on Decision and Control 2006, CDC

Y2 - 13 December 2006 through 15 December 2006

ER -

The effect of sensor health on state estimation

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