Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/25199
Title: A biological inspired improvement strategy for Particle Filters
Authors: Zhong, J
Fung, Y
Keywords: Optimisation
Particle filtering (numerical methods)
State estimation
Issue Date: 2009
Publisher: IEEE
Source: IEEE International Conference on Industrial Technology, 2009 : ICIT 2009, 10-13 Feb. 2009, Gippsland, VIC, p. 1-6 How to cite?
Abstract: Particle filters (PF) is a model estimation technique based on simulation. But two problems, namely particle impoverishment and sample size dependency, frequently occur during the particle updating stage and these problems will reduce the accuracy of the estimation results. In order to avoid these problems, ant colony optimization is incorporated into the generic particle filter before the updating stage. After the optimization, particle samples will move closer to their local highest posterior density function and better estimation results can be produced.
URI: http://hdl.handle.net/10397/25199
ISBN: 978-1-4244-3506-7
978-1-4244-3507-4 (E-ISBN)
DOI: 10.1109/ICIT.2009.4939539
Appears in Collections:Conference Paper

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