An adaptive optimized strategy for particle filter
Particle filter has been widely applied into many fields in recent years. Combined with the deficiency analysis of particle filter, an adaptive optimized strategy for particle filter is proposed. This adaptive optimized strategy includes two parts. One is an improved hybrid proposal distribution wit...
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Published in | 2012 24th Chinese Control and Decision Conference (CCDC) pp. 3936 - 3940 |
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Main Authors | , , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
01.05.2012
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Subjects | |
Online Access | Get full text |
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Summary: | Particle filter has been widely applied into many fields in recent years. Combined with the deficiency analysis of particle filter, an adaptive optimized strategy for particle filter is proposed. This adaptive optimized strategy includes two parts. One is an improved hybrid proposal distribution with adaptive parameter optimization for particle filter. Based on the performance analysis of different proposal distribution, a hybrid proposal distribution with adaptive annealing parameter optimization is utilized to consider current information of the latest observed measurement. The other is an adaptive resampling strategy based on diversity guidance. An adaptive resampling step in particle filter is tuned based on two diversity measures and an improved partial stratified resampling strategy is presented based on the weights optimal idea. With the simulation program, the performance of the proposed strategy is evaluated and its validity is verified. |
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ISBN: | 9781457720734 1457720736 |
ISSN: | 1948-9439 1948-9447 |
DOI: | 10.1109/CCDC.2012.6243105 |