Efficient search strategies for non-myopic sensor scheduling in target tracking

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

17 Scopus citations

Abstract

We propose two tree pruning algorithms to reduce the computational complexity of non-myopic sensor scheduling for target tracking. We consider a mobile bearings-only sensor that chooses from a finite set of possible moves at each time epoch. The scheduling objective is to select the sequence of sensor moves to minimize a tracking cost over M > 1 future time epochs. Tracking is performed with a particle filter, and expected future costs are calculated using an unscented transform with the particle filter. Simulation shows that the two algorithms significantly reduce the time and memory requirements compared to exhaustive search.

Original languageEnglish (US)
Title of host publicationConference Record - Asilomar Conference on Signals, Systems and Computers
EditorsM.B. Matthews
Pages2106-2110
Number of pages5
Volume2
StatePublished - 2004
EventConference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers - Pacific Grove, CA, United States
Duration: Nov 7 2004Nov 10 2004

Other

OtherConference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers
CountryUnited States
CityPacific Grove, CA
Period11/7/0411/10/04

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Chhetri, A. S., Morrell, D., & Papandreou-Suppappola, A. (2004). Efficient search strategies for non-myopic sensor scheduling in target tracking. In M. B. Matthews (Ed.), Conference Record - Asilomar Conference on Signals, Systems and Computers (Vol. 2, pp. 2106-2110)