The use of particle filtering with the unscented transform to schedule sensors multiple steps ahead

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

13 Scopus citations

Abstract

In a multisensor network, sensor scheduling can be used to minimize the cost of resources and improve system performance. In this paper, we propose multisensor scheduling algorithm using a particle filter and the unscented transform for a target tracking application. Under the constraint that only one sensor may be used at each time step, we predict the expected cost multiple steps ahead. We achieve this using several sets of particles for each sequence of sensors and then choose the sequence that minimizes the predicted cost. An advantage of the proposed algorithm is that it can incorporate arbitrary cost functions. Monte Carlo simulations, using squared error as the cost function, demonstrate the improved target tracking performance achieved with sensor scheduling.

Original languageEnglish (US)
Title of host publicationICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2
StatePublished - 2004
EventProceedings - IEEE International Conference on Acoustics, Speech, and Signal Processing - Montreal, Que, Canada
Duration: May 17 2004May 21 2004

Other

OtherProceedings - IEEE International Conference on Acoustics, Speech, and Signal Processing
CountryCanada
CityMontreal, Que
Period5/17/045/21/04

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Signal Processing
  • Acoustics and Ultrasonics

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    Chhetri, A. S., Morrell, D., & Papandreou-Suppappola, A. (2004). The use of particle filtering with the unscented transform to schedule sensors multiple steps ahead. In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings (Vol. 2)