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Quickest Change Detection With Observation Scheduling
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0001-9940-5929
2017 (English)In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 62, no 6, 2635-2647 p.Article in journal (Refereed) Published
Abstract [en]

The quickest change detection problem is to detect an abrupt change event as quickly as possible subject to constraints on false detection. Unlike the classical problem, where the decision maker can access only one sequence of observations, in this paper, the decision maker chooses one of two different sequences of observations at each time instant. The information quality and sampling cost of the two sequences of observations are different. We present an asymptotically optimal joint design of observation scheduling policy and stopping time such that the detection delay is minimized subject to constraints on both average run length to false alarm (ARLFA) and average cost per sample. The observation scheduling policy has a threshold structure and the detection scheme is a variant of the cumulative sum test where the detection statistic stochastically crosses the threshold that is used to switch observation modes. We further study the decentralized case in a multi-channel setting. We show that if each sensor uses the proposed observation scheduling policy locally and the fusion center uses the Nsum algorithm, by which the center declares the change when the sum of the sensors' local detection statistics crosses a certain threshold, the detection delay is asymptotically minimized for any possible combination of the affected sensors subject to constraints on both global ARLFA and average cost per sample at each sensor node. Numerical examples are given to illustrate the main results.

Place, publisher, year, edition, pages
IEEE, 2017. Vol. 62, no 6, 2635-2647 p.
Keyword [en]
CuSum, minimax, multi-channel, observation scheduling, quickest change detection, sensor networks
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-210486DOI: 10.1109/TAC.2016.2609998ISI: 000402733600003OAI: oai:DiVA.org:kth-210486DiVA: diva2:1120074
Funder
Knut and Alice Wallenberg FoundationSwedish Foundation for Strategic Research Swedish Research Council
Note

QC 20170705

Available from: 2017-07-05 Created: 2017-07-05 Last updated: 2017-07-05Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
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  • Other locale
More languages
Output format
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