An approximate dynamic programming based non-myopic sensor selection method for target tracking

Engin Masazade, Ruixin Niu, Pramod K. Varshney

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

12 Scopus citations

Abstract

In this paper, we study the non-myopic sensor selection problem for target tracking in wireless sensor networks based on quantized sensor data. Using the conditional posterior Cramér-Rao lower bound (C-PCRLB) as a sensor selection metric, we formulate and solve a non-myopic sensor selection problem using an approximate dynamic programming (A-DP) algorithm. Given a constraint on the total number of selected sensors allowed while observing the target over a time window, simulation results show that the proposed non-myopic sensor selection scheme based on A-DP is computationally very efficient and yields better tracking performance than the myopic sensor selection scheme.

Original languageEnglish (US)
Title of host publication2012 46th Annual Conference on Information Sciences and Systems, CISS 2012
DOIs
StatePublished - Nov 12 2012
Event2012 46th Annual Conference on Information Sciences and Systems, CISS 2012 - Princeton, NJ, United States
Duration: Mar 21 2012Mar 23 2012

Publication series

Name2012 46th Annual Conference on Information Sciences and Systems, CISS 2012

Other

Other2012 46th Annual Conference on Information Sciences and Systems, CISS 2012
CountryUnited States
CityPrinceton, NJ
Period3/21/123/23/12

ASJC Scopus subject areas

  • Information Systems

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