DocumentCode
1794938
Title
A navigation algorithm aided by multi-motion constraints of vehicle based on unified model
Author
Xinxi Zhang ; Meifeng Guo ; Rong Zhang ; Luna Mi ; Mingliang Song ; Yongjian Zhang
Author_Institution
Dept. of Precision Instrum., Tsinghua Univ., Beijing, China
fYear
2014
fDate
8-10 Aug. 2014
Firstpage
749
Lastpage
755
Abstract
Precision of vehicle navigation can be significantly improved by adding motion constraints. How to model multi-motion constraints and choose appropriate motion constraint according to vehicle mobility need to be solved in practical usage. This article established a unified state error model and deduced a measurement model for several common vehicle motion constraints, like ZUPT, MCA and HDR, used the Kalman Filter and feedback correction. This article also proposed a mobility detection algorithm and a constraint control strategy to avoid the invalid motion constraints, the constraint control strategy could be adaptively applied according to the mobility. Simulation result stated that this algorithm could adaptively apply multi-motion constraints based on mobility detection. And, navigation precision was improved nearly two orders of magnitude except the heading angle. As the algorithm is simple and adaptive, it is of practical value in vehicle navigation.
Keywords
Kalman filters; inertial navigation; motion control; road traffic control; road vehicles; HDR; Kalman filter; MCA; ZUPT; constraint control strategy; feedback correction; measurement model; mobility detection algorithm; multimotion constraint; navigation precision; unified state error model; vehicle mobility; vehicle motion constraint; vehicle navigation algorithm; Equations; Kalman filters; Mathematical model; Motion measurement; Navigation; Noise; Vehicles; HDR; Kalman Filter; MCA; Mobility Detection; ZUPT;
fLanguage
English
Publisher
ieee
Conference_Titel
Guidance, Navigation and Control Conference (CGNCC), 2014 IEEE Chinese
Conference_Location
Yantai
Print_ISBN
978-1-4799-4700-3
Type
conf
DOI
10.1109/CGNCC.2014.7007305
Filename
7007305
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