Adaptive square-root CKF with application to DR/LBL integrated heading estimation for HOV

CORC > 沈阳自动化研究所 > 中国科学院沈阳自动化研究所 > 水下机器人研究室

	Adaptive square-root CKF with application to DR/LBL integrated heading estimation for HOV
	Liu KZ(刘开周); Liu B(刘本); Wang YY(王艳艳); Zhao Y(赵洋); Cui SG(崔胜国); Feng XS(封锡盛)
	2015
会议名称	27th Chinese Control and Decision Conference, CCDC 2015
会议日期	May 23-25, 2015
会议地点	Qingdao, China
关键词	DR/LBL Heading Estimation maximum a posterior Human Occupied Vehicle Adaptive Square-root Cubature Kalman filter
页码	1851-1855
中文摘要	Dead Reckoning (DR) and Long Base Line (LBL) are a modern method in navigation of Human Occupied Vehicles (HOV). However, the accuracy of DR system would degrade sharply, and due to the obvious error drifts of each unit involved in DR. LBL has the disadvantage of low update frequency. To improve the heading estimation of DR/LBL, this paper proposes an innovative method which could adjust state error variance matrix Q in real time dynamically. Square-root Cubature Kalman filter (SR-CKF) is used to simulate the convergence of the dynamic model of DR. And, Sage-Husa maximum a posterior (MAP) is employed in filtering progress. The simulation results of the adaptive SR-CKF and CKF are compared, which show that the method proposed in this paper can obtain a fairly accurate heading estimation.
收录类别	EI ; CPCI（ISTP）
产权排序	1
会议录	Proceedings of the 2015 27th Chinese Control and Decision Conference, CCDC 2015
会议录出版者	IEEE
会议录出版地	Piscataway, NJ, USA
语种	英语
ISBN号	978-1-4799-7016-2
WOS记录号	WOS:000375232903035
内容类型	会议论文
源URL	[http://ir.sia.cn/handle/173321/17188]
专题	沈阳自动化研究所_水下机器人研究室
推荐引用方式 GB/T 7714	Liu KZ,Liu B,Wang YY,et al. Adaptive square-root CKF with application to DR/LBL integrated heading estimation for HOV[C]. 见:27th Chinese Control and Decision Conference, CCDC 2015. Qingdao, China. May 23-25, 2015.