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Blending Sensor Scheduling Strategy with Particle Filter to Track a Smart Target

By Bin LIU, Chunlin JI, Yangyang ZHANG and Chengpeng HAO

Abstract

We discuss blending sensor scheduling strategies with particle filtering (PF) methods to deal with the prob-lem of tracking a ‘smart’ target, that is, a target being able to be aware it is being tracked and act in a manner that makes the future track more difficult. We concern here how to accurately track the target with a care on concealing the observer to a possible extent. We propose a PF method, which is tailored to mix a sensor scheduling technique, called covariance control, within its framework. A Rao-blackwellised unscented Kal-man filter (UKF) is used to produce proposal distributions for the PF method, making it more robust and computationally efficient. We show that the proposed method can balance the tracking filter performance with the observer’s concealment

Topics: Particle Filter, Sensor Scheduling, Smart Target, Tracking, LCC:Electronic computers. Computer science, LCC:QA75.5-76.95, LCC:Instruments and machines, LCC:QA71-90, LCC:Mathematics, LCC:QA1-939, LCC:Science, LCC:Q, DOAJ:Computer Science, DOAJ:Technology and Engineering
Publisher: Scientific Research Publishing
Year: 2009
DOI identifier: 10.4236/wsn.2009.14037
OAI identifier: oai:doaj.org/article:079c64b9defe4427bf424859b46e75ff
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