A novel self-adapting filter based navigation algorithm for autonomous underwater vehicles
文献类型：期刊论文
| 作者 | Xu CH(徐春晖)2 ; Shao G(邵刚)2; Wang Y(王轶群)2; Liu J(刘健)2; Qu DK(曲道奎)1,2; Wu CD(吴成东)3; Xu, Chenglong1,2,3
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| 刊名 | Ocean Engineering
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| 出版日期 | 2019 |
| 卷号 | 187页码:1-12 |
| 关键词 | Autonomous underwater vehicle Ultra short baseline Condition-adaptive Confidence measure operator Integrated navigation system |
| ISSN号 | 0029-8018 |
| 产权排序 | 1 |
| 通讯作者 | Xu, Chenglong(xurobot@stumail.neu.edu.cn) |
| 英文摘要 | This paper presents a novel approach to the design of globally asymptotically stable position and assessment of an USBL-aided integrated navigation based on Condition-adaptive gain Extended Kalman Filter (CAEKF) for the deep water Autonomous Underwater Vehicles (AUVs) subject to uncertainties (e.g., loss of USBL signal, irregular and gross positioning error). Due to the influence of underwater observation conditions, positioning gross error will often appear when exploiting USBL to assist AUV navigation in ocean exploration. Aiming at this kind of problem a method of adding the conditional constraints and confidence assessment to EKF was put forward to filter the positioning value of USBL, and which can make the filtering result more robust and smooth. In addition, in order to reduce positioning error for the deep water vehicle online, an integrated navigation system is constructed by adding the acoustic navigation. Finally, the long voyage of the sea-trials data acquired in suitable sea trials performed in the South China Sea verifying the robustness and practicability of the proposed methodology, a very effective trade-off between accuracy and computational load has been achieved, and which demonstrated that the proposed algorithm outperforms standard navigation algorithms and other classical filtering approaches. |
| WOS关键词 | TRAJECTORY TRACKING ; AUV NAVIGATION ; ROBUST |
| 资助项目 | National Key R&D Program of China[2017YFC03 06800] |
| WOS研究方向 | Engineering ; Oceanography |
| 语种 | 英语 |
| WOS记录号 | WOS:000487564700007 |
| 资助机构 | National Key R&D Program of China (No. 2017YFC03 06800) |
| 源URL | [http://ir.sia.cn/handle/173321/25316]  |
| 专题 | 沈阳自动化研究所_水下机器人研究室 |
| 作者单位 | 1.Shenyang SIASUN Robot & Automation Co., LTD, Shenyang, China 2.State Key Laboratory of Robotics, Shenyang Institute of Automation, CAS, Shenyang, China 3.Robot Science and Engineering, Northeastern University, Shenyang, China |
| 推荐引用方式 GB/T 7714 | Xu CH,Shao G,Wang Y,et al. A novel self-adapting filter based navigation algorithm for autonomous underwater vehicles[J]. Ocean Engineering,2019,187:1-12. |
| APA | Xu CH.,Shao G.,Wang Y.,Liu J.,Qu DK.,...&Xu, Chenglong.(2019).A novel self-adapting filter based navigation algorithm for autonomous underwater vehicles.Ocean Engineering,187,1-12. |
| MLA | Xu CH,et al."A novel self-adapting filter based navigation algorithm for autonomous underwater vehicles".Ocean Engineering 187(2019):1-12. |
入库方式： OAI收割
来源：沈阳自动化研究所
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