Sensor selection for passive sensor networks in dynamic environment: A dynamic data-driven approach

Yue Li, Devesh K. Jha, Asok Ray, Thomas A. Wettergren

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

This paper addresses the sensor selection problem in a passive sensor network under dynamically varying environment. It is assumed that sensors in the same local area share similar dynamic environmental characteristics but only a few may have events within their respective sensing radii. The main challenge is to select sensors for separation in two categories: (i) those sensors whose outputs contain combined information of event and dynamic environment and (ii) those sensors whose outputs contain the environment information only. The criteria for sensor selection is made based on the entropy rate measurements of the standard Probabilistic Finite State Automata (PFSA) constructed from sensor time series and cross D-Markov machines constructed from combined time series of a sensor and the first (i.e., dominant) principal component representing the dominant linear mode in the ensemble of related sensor data within the network. The proposed method is applied to experimental data collected from a small local passive sensor network for target detection under dynamic environments, where characteristics of environmental signal is similar to the target signal in the sense of time scale and texture.

Original languageEnglish (US)
Title of host publication2016 American Control Conference, ACC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4924-4929
Number of pages6
ISBN (Electronic)9781467386821
DOIs
StatePublished - Jul 28 2016
Event2016 American Control Conference, ACC 2016 - Boston, United States
Duration: Jul 6 2016Jul 8 2016

Publication series

NameProceedings of the American Control Conference
Volume2016-July
ISSN (Print)0743-1619

Other

Other2016 American Control Conference, ACC 2016
CountryUnited States
CityBoston
Period7/6/167/8/16

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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