| The research on sea-bottom terrain tracking by AUV based on least squares method and Extended Kalman Filter | |
Xu HL(徐红丽) ; Chen G(陈巩); Jia QY(贾庆勇); Cao S(曹帅); Jiang M(蒋敏)
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| 作者部门 | 海洋信息技术装备中心 |
| 会议名称 | OCEANS 2016 - Shanghai |
| 会议日期 | April 10-13, 2016 |
| 会议地点 | Shanghai, China |
| 会议录名称 | OCEANS 2016 - Shanghai |
| 出版者 | IEEE |
| 出版地 | Piscataway, NJ, USA |
| 2016 | |
| 页码 | 1-4 |
| 收录类别 | EI ; CPCI（ISTP） |
| EI收录号 | 20162902613092 |
| WOS记录号 | WOS:000386521800068 |
| 产权排序 | 1 |
| ISSN号 | 0197-7385 |
| ISBN号 | 978-1-4673-9724-7 |
| 关键词 | Auv Slope Estimate Bottom-following Ekf |
| 摘要 | This paper studies the problem of undersea bottom-following through using the Autonomous Underwater Vehicle(AUV) equipped with Altimeter and Depth gauge. We can improve the ability of AUV to perceive the information of the seabed by using the Extended Kalman Filter(EKF) to complete the information fusion of data comes from Altimeter and Depth gauge. The seabed terrain slope is estimated by the least square method and then the trend of the seabed terrain can be predicted, which improve the ability of the AUV to track the seabed terrain. In the end, the seabed terrain tracking algorithm was verified by Matlab simulation, and the experimental results showed that the proposed method was effective. |
| 语种 | 英语 |
| 引用统计 | |
| 文献类型 | 会议论文 |
| 条目标识符 | http://ir.sia.cn/handle/173321/18761 |
| 专题 | 海洋信息技术装备中心 |
| 通讯作者 | Chen G(陈巩) |
| 作者单位 | State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China |
| 推荐引用方式 GB/T 7714 | Xu HL,Chen G,Jia QY,et al. The research on sea-bottom terrain tracking by AUV based on least squares method and Extended Kalman Filter[C]. Piscataway, NJ, USA:IEEE,2016:1-4. |
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| The research on sea-（294KB） | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 | ||
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