Performance Investigation on Constraint Sufficient Statistics Distributed Particle Filter

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Authors
  1. Yu, J.Y.
  2. Rabbat, M.
  3. Coates, M.
  4. Blouin, S.
Corporate Authors
Defence Research and Development Canada, Atlantic Research Centre, Halifax NS (CAN)
Abstract
The constraint sufficient statistics distributed particle filter is a novel and effective solution for bearings-only single target tracking. The algorithm achieves a significant reduction in communication overhead by factorizing the likelihood function without suffering a major decrease in accuracy. However, the algorithm has some limitations which we discuss and explore in this paper. In particular, the algorithm has a bias induced via the approximate likelihood calculation, depending on the geometry of the sensors relative to the target.
Report Number
DRDC-RDDC-2015-P039 — External Literature
Date of publication
01 May 2015
Number of Pages
6
DSTKIM No
CA040749
CANDIS No
801814
Format(s):
Electronic Document(PDF)

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