An Enhanced Adaptive Unscented Kalman Filter for Vehicle State Estimation

Accurate vehicle state information is crucial for safe driving and dynamic control of vehicles. Vehicle state estimation under unknown noise conditions is an important research topic. A state estimation method based on enhanced adaptive unscented Kalman filter (EAUKF) is proposed to solve vehicle es...

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Vydáno v:	IEEE transactions on instrumentation and measurement Ročník 71; s. 1 - 12
Hlavní autoři:	Zhang, Yingjie, Li, Ming, Zhang, Ying, Hu, Zuolei, Sun, Qingshuai, Lu, Biliang
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Accuracy Adaptive algorithms Adaptive modulation factor Algorithms Attenuation Dynamic control enhanced adaptive unscented Kalman filter (EAUKF) Force Kalman filters longitudinal dynamics modeling Mathematical models Roads safe driving and dynamic control State estimation State variable Tires Vehicle dynamics vehicle state estimation Wheels
ISSN:	0018-9456, 1557-9662
On-line přístup:	Získat plný text
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