HKUST Library Institutional Repository Banner

HKUST Institutional Repository >
Electronic and Computer Engineering  >
ECE Journal/Magazine Articles >

Please use this identifier to cite or link to this item: http://hdl.handle.net/1783.1/6708
Title: Kalman filtering over graphs : theory and applications
Authors: Shi, Ling
Keywords: Kalman filter
Discrete-time systems
Issue Date: Sep-2009
Citation: IEEE Transactions on Automatic Control, vol. 54, no. 9, September 2009, p. 2230-2234
Abstract: In this technical note we consider the problem of distributed discrete-time state estimation over sensor networks. Given a graph that represents the sensor communications, we derive the optimal estimation algorithm at each sensor.We further provide a closed-form expression for the steady-state error covariance matrices when the communication graph reduces to a directed tree. We then apply the developed theoretical tools to compare the performance of two sensor trees and convert a random packet-delay model to a random packet-dropping model. Examples are provided throughout the technical note to support the theory.
Rights: © 2009 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. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
URI: http://hdl.handle.net/1783.1/6708
Appears in Collections:ECE Journal/Magazine Articles

Files in This Item:

File Description SizeFormat
Kalman2.pdf325KbAdobe PDFView/Open

Find published version via OpenURL Link Resolver

All items in this Repository are protected by copyright, with all rights reserved.