Incorporation of Time Delayed Measurements in a Discrete-time Kalman Filter

Thomas Dall Larsen; Nils Axel Andersen; Ole Ravn; Niels Kjølstad Poulsen

doi:10.1109/CDC.1998.761918

Incorporation of Time Delayed Measurements in a Discrete-time Kalman Filter

Thomas Dall Larsen, Nils Axel Andersen, Ole Ravn, Niels Kjølstad Poulsen

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Abstract

In many practical systems there is a delay in some of the sensor devices, for instance vision measurements that may have a long processing time. How to fuse these measurements in a Kalman filter is not a trivial problem if the computational delay is critical. Depending on how much time there is at hand, the designer has to make trade offs between optimality and computational burden of the filter. In this paper various methods in the literature along with a new method proposed by the authors will be presented and compared. The new method is based on “extrapolating” the measurement to present time using past and present estimates of the Kalman filter and calculating an optimal gain for this extrapolated measurement

Original language	English
Title of host publication	Decision and Control, 1998. Proceedings of the 37th IEEE Conference on
Volume	4
Publisher	IEEE
Publication date	1998
Pages	3972-3977
ISBN (Print)	0-7803-4394-8
DOIs	https://doi.org/10.1109/CDC.1998.761918
Publication status	Published - 1998
Event	37th IEEE Conference on Decision and Control - Tampa, FL, United States Duration: 16 Dec 1998 → 18 Dec 1998 Conference number: 37 http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6103

Conference

Conference	37th IEEE Conference on Decision and Control
Number	37
Country/Territory	United States
City	Tampa, FL
Period	16/12/1998 → 18/12/1998
Internet address	http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6103

Bibliographical note

Copyright: 1998 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE

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title = "Incorporation of Time Delayed Measurements in a Discrete-time Kalman Filter",

abstract = "In many practical systems there is a delay in some of the sensor devices, for instance vision measurements that may have a long processing time. How to fuse these measurements in a Kalman filter is not a trivial problem if the computational delay is critical. Depending on how much time there is at hand, the designer has to make trade offs between optimality and computational burden of the filter. In this paper various methods in the literature along with a new method proposed by the authors will be presented and compared. The new method is based on “extrapolating” the measurement to present time using past and present estimates of the Kalman filter and calculating an optimal gain for this extrapolated measurement",

author = "Larsen, \{Thomas Dall\} and Andersen, \{Nils Axel\} and Ole Ravn and Poulsen, \{Niels Kj{\o}lstad\}",

note = "Copyright: 1998 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE; 37th IEEE Conference on Decision and Control, CDC ; Conference date: 16-12-1998 Through 18-12-1998",

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AU - Andersen, Nils Axel

AU - Ravn, Ole

AU - Poulsen, Niels Kjølstad

N1 - Conference code: 37

PY - 1998

Y1 - 1998

N2 - In many practical systems there is a delay in some of the sensor devices, for instance vision measurements that may have a long processing time. How to fuse these measurements in a Kalman filter is not a trivial problem if the computational delay is critical. Depending on how much time there is at hand, the designer has to make trade offs between optimality and computational burden of the filter. In this paper various methods in the literature along with a new method proposed by the authors will be presented and compared. The new method is based on “extrapolating” the measurement to present time using past and present estimates of the Kalman filter and calculating an optimal gain for this extrapolated measurement

AB - In many practical systems there is a delay in some of the sensor devices, for instance vision measurements that may have a long processing time. How to fuse these measurements in a Kalman filter is not a trivial problem if the computational delay is critical. Depending on how much time there is at hand, the designer has to make trade offs between optimality and computational burden of the filter. In this paper various methods in the literature along with a new method proposed by the authors will be presented and compared. The new method is based on “extrapolating” the measurement to present time using past and present estimates of the Kalman filter and calculating an optimal gain for this extrapolated measurement

U2 - 10.1109/CDC.1998.761918

DO - 10.1109/CDC.1998.761918

M3 - Article in proceedings

SN - 0-7803-4394-8

VL - 4

SP - 3972

EP - 3977

BT - Decision and Control, 1998. Proceedings of the 37th IEEE Conference on

PB - IEEE

T2 - 37th IEEE Conference on Decision and Control

Y2 - 16 December 1998 through 18 December 1998

ER -

Incorporation of Time Delayed Measurements in a Discrete-time Kalman Filter

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