Optimal sensor power scheduling for state estimation of Gauss–Markov systems over a packet-dropping network

We consider sensor power scheduling for estimating the state of a general high-order Gauss-Markov system. A sensor decides whether to use a high or low transmission power to communicate its local state estimate or raw measurement data with a remote estimator over a packet-dropping network. We constr...

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Main Authors: Shi, Ling, Xie, Lihua
其他作者: School of Electrical and Electronic Engineering
格式: Article
語言:English
出版: 2013
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在線閱讀:https://hdl.handle.net/10356/99383
http://hdl.handle.net/10220/13511
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機構: Nanyang Technological University
語言: English
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spelling sg-ntu-dr.10356-993832020-03-07T14:02:43Z Optimal sensor power scheduling for state estimation of Gauss–Markov systems over a packet-dropping network Shi, Ling Xie, Lihua School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering We consider sensor power scheduling for estimating the state of a general high-order Gauss-Markov system. A sensor decides whether to use a high or low transmission power to communicate its local state estimate or raw measurement data with a remote estimator over a packet-dropping network. We construct the optimal sensor power schedule which minimizes the expected terminal estimation error covariance at the remote estimator under the constraint that the high transmission power can only be used m <; T + 1 times, given the time-horizon from k = 0 to k = T. We also discuss how to extend the result to cases involving multiple power levels scheduling. Simulation examples are the provided to demonstrate the results. 2013-09-18T01:09:55Z 2019-12-06T20:06:39Z 2013-09-18T01:09:55Z 2019-12-06T20:06:39Z 2012 2012 Journal Article Shi, L., & Xie, L., (2012). Optimal sensor power scheduling for state estimation of Gauss–Markov systems over a packet-dropping network. IEEE transactions on signal processing, 60(5), 2701-2705. 1053-587X https://hdl.handle.net/10356/99383 http://hdl.handle.net/10220/13511 10.1109/TSP.2012.2184536 en IEEE transactions on signal processing © 2012 IEEE
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering
spellingShingle DRNTU::Engineering::Electrical and electronic engineering
Shi, Ling
Xie, Lihua
Optimal sensor power scheduling for state estimation of Gauss–Markov systems over a packet-dropping network
description We consider sensor power scheduling for estimating the state of a general high-order Gauss-Markov system. A sensor decides whether to use a high or low transmission power to communicate its local state estimate or raw measurement data with a remote estimator over a packet-dropping network. We construct the optimal sensor power schedule which minimizes the expected terminal estimation error covariance at the remote estimator under the constraint that the high transmission power can only be used m <; T + 1 times, given the time-horizon from k = 0 to k = T. We also discuss how to extend the result to cases involving multiple power levels scheduling. Simulation examples are the provided to demonstrate the results.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Shi, Ling
Xie, Lihua
format Article
author Shi, Ling
Xie, Lihua
author_sort Shi, Ling
title Optimal sensor power scheduling for state estimation of Gauss–Markov systems over a packet-dropping network
title_short Optimal sensor power scheduling for state estimation of Gauss–Markov systems over a packet-dropping network
title_full Optimal sensor power scheduling for state estimation of Gauss–Markov systems over a packet-dropping network
title_fullStr Optimal sensor power scheduling for state estimation of Gauss–Markov systems over a packet-dropping network
title_full_unstemmed Optimal sensor power scheduling for state estimation of Gauss–Markov systems over a packet-dropping network
title_sort optimal sensor power scheduling for state estimation of gauss–markov systems over a packet-dropping network
publishDate 2013
url https://hdl.handle.net/10356/99383
http://hdl.handle.net/10220/13511
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