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Volumn 19, Issue 2, 2008, Pages

A lightweight target-tracking scheme using wireless sensor network

Author keywords

Improved particle filter; Localization; Target tracking; Wireless sensor network

Indexed keywords

ALGORITHMS; COMPUTER SIMULATION; MARKOV PROCESSES; MONTE CARLO METHODS; WIRELESS SENSOR NETWORKS;

EID: 42549158000     PISSN: 09570233     EISSN: 13616501     Source Type: Journal    
DOI: 10.1088/0957-0233/19/2/025104     Document Type: Article
Times cited : (21)

References (13)
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  • 3
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  • 4
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    • Dynamic sensor collaboration via sequential Monte Carlo
    • Guo D and Wang X 2004 Dynamic sensor collaboration via sequential Monte Carlo IEEE J. Sel. Areas Commun. 22 1037-47
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    • Guo, D.1    Wang, X.2
  • 6
    • 4844228284 scopus 로고    scopus 로고
    • Distributed target classification and tracking in sensor networks
    • Brook R, Ramanathan P and Sayeed A 2003 Distributed target classification and tracking in sensor networks Proc. IEEE 91 1163-71
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    • Brook, R.1    Ramanathan, P.2    Sayeed, A.3
  • 7
    • 33744915783 scopus 로고    scopus 로고
    • Distributed particle filter with GMM approximation for multiple target localization and tracking in wireless sensor network
    • Sheng X and Hu Y H 2005 Distributed particle filter with GMM approximation for multiple target localization and tracking in wireless sensor network Proc. 4th Int. Symp. Information Processing in Sensor Networks (Los Angeles, CA) pp 181-8
    • (2005) Proc. 4th Int. Symp. Information Processing in Sensor Networks , pp. 181-188
    • Sheng, X.1    Hu, Y.H.2
  • 8
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    • Distributed and energy-efficient target localization and tracking in wireless sensor networks
    • Lee J et al 2006 Distributed and energy-efficient target localization and tracking in wireless sensor networks Comput. Commun. 29 2494-505
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  • 10
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    • Maximum likelihood multiple-source localization using acoustic energy measurements with wireless sensor networks
    • Sheng X and Hu Y H 2005 Maximum likelihood multiple-source localization using acoustic energy measurements with wireless sensor networks IEEE Trans. Signal Process. 53 44-53
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    • Sheng, X.1    Hu, Y.H.2
  • 11
    • 0036475447 scopus 로고    scopus 로고
    • A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking
    • Arulampalam M S, Maskell S, Gordon N and Clapp T 2002 A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking IEEE Trans. Signal Process. 50 174-88
    • (2002) IEEE Trans. Signal Process. , vol.50 , Issue.2 , pp. 174-188
    • Arulampalam, M.S.1    Maskell, S.2    Gordon, N.3    Clapp, T.4
  • 12
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    • An introduction to MCMC for machine learning
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.