NDLI: Particle filter adaptation for distributed sensors via set membership

Content Provider	IEEE Xplore Digital Library
Author	Farahmand, S. Roumeliotis, S.I. Giannakis, G.B.
Copyright Year	2010
Description	Author affiliation: CS Dept., Univ. of Minnesota, 200 Union Street SE, Minneapolis, 55455, USA (Roumeliotis, S.I.) \|\| ECE Dept., Univ. of Minnesota, 200 Union Street SE, Minneapolis, 55455, USA (Farahmand, S.; Giannakis, G.B.)
Abstract	A distributed set-membership-constrained particle filter (SMCPF) is developed for decentralized tracking applications using wireless sensor networks. Unlike existing PF alternatives, SMC-PF offers reduced overhead for inter-sensor communications because it requires only particle weights to be exchanged among sensors, instead of raw measurements or parameters of a Gaussian mixture model. SMC-PF relies on a novel distributed adaptation scheme based on successive set intersections that can afford reduced number of particles without sacrificing performance. Conditions are provided to quantify the variance reduction of the SMC-PF-based state estimator. Simulations corroborate the ability of the SMCPF to considerably outperform the bootstrap PF for a fixed number of particles.
Starting Page	3374
Ending Page	3377
File Size	188714
Page Count	4
File Format	PDF
ISBN	9781424442959
ISSN	15206149
DOI	10.1109/ICASSP.2010.5496001
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-03-14
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Particle filters Target tracking Wireless sensor networks State estimation Noise measurement Yield estimation Government Particle tracking Particle measurements Filtering adaptation particle filtering set-membership distributed
Content Type	Text
Resource Type	Article

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