Random weighting estimation for systematic error of observation model in dynamic vehicle navigation
Random weighting estimation for systematic error of observation model in dynamic vehicle navigation
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Author / Creator
Publisher
Bucheon / Seoul: Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers
Journal title
Language
English
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Publication information
Publisher
Bucheon / Seoul: Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers
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Scope and Contents
Contents
The Kalman filter requires kinematic and observation models not contain any systematic error. Otherwise, the resultant navigation solution will be biased or even divergent. In order to overcome this limitation, this paper presents a new random weighting method to estimate the systematic error of observation model in dynamic vehicle navigation. This...
Alternative Titles
Full title
Random weighting estimation for systematic error of observation model in dynamic vehicle navigation
Authors, Artists and Contributors
Author / Creator
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Primary Identifiers
Record Identifier
TN_cdi_nrf_kci_oai_kci_go_kr_ARTI_129493
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_nrf_kci_oai_kci_go_kr_ARTI_129493
Other Identifiers
ISSN
1598-6446
E-ISSN
2005-4092
DOI
10.1007/s12555-014-0333-8
