Adaptive square-root CKF with application to DR/LBL integrated heading estimation for HOV
文献类型：会议论文
| 作者 | 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)
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| 出版日期 | 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 |
| 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. |
入库方式： OAI收割
来源：沈阳自动化研究所
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