自主式水下航行器水下回收融合引导技术方案及算法

赵蕊; 许建

doi:10.19693/j.issn.1673-3185.02318

自主式水下航行器水下回收融合引导技术方案及算法

doi: 10.19693/j.issn.1673-3185.02318

赵蕊,
许建

中国舰船研究设计中心，湖北武汉 430064

详细信息

作者简介:
赵蕊，女，1981年生，硕士，高级工程师

许建，男，1963年生，博士，研究员，博士生导师

通信作者:
赵蕊

中图分类号: U664.82
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- 被引次数: 0
出版历程
- 收稿日期: 2021-03-17
- 修回日期: 2021-04-02
- 网络出版日期: 2022-02-23
- 刊出日期: 2022-03-02

Fusion guiding technology solution and algorithm for underwater docking of autonomous underwater vehicles

ZHAO Rui,
XU Jian

China Ship Development and Design Center, Wuhan 430064, China

自主式水下航行器水下回收融合引导技术方案及算法由赵蕊，等创作，采用知识共享署名4.0国际许可协议进行许可。

摘要

摘要: 目的为解决母艇携载的自主式水下航行器（AUV）在水下自主回收和对接的问题，基于惯导（INS）、声学超短基线定位（USBL）、光学等信号引导的多源数据融合，提出一种面向移动平台的AUV水下回收对接引导方法。方法为此，设计融合多传感器信息的扩展联邦卡尔曼滤波器，采用分散滤波并再经信息融合方法以提高滤波精度。分别以INS和USBL及光学探测信号作为子滤波器的输入信息，结合AUV水下回收对接过程中的5个阶段分别建立运动方程，最终得到适用于移动平台搭载的AUV水下对接引导系统的多源数据融合导航算法。结果仿真结果表明，所提方法具有可行性、系统鲁棒性和控制精度，结论可满足母艇水下回收作业对接的工程要求，以及作为AUV水下自主回收操作的技术参考。
- 自主式水下航行器 /
- 水下对接 /
- 多源数据融合算法 /
- 声学定位 /
- 光学定位
Abstract: Objective To address the problem of underwater autonomous vehicles (AUVs) docking with parent vessels in recovery operations, a mobile platform-oriented AUV underwater guiding solution is proposed on the basis of multi-sources information fusion, including inertial, acoustic and optical signals. Methods A federated extended Kalman filter integrating multi-sensors information is designed to improve filtering accuracy through decentralized filtering and information fusion. Motion equations are also established by combining the five AUV docking stages, in which the signals detected by the inertial navigation system (INS), acoustic ultra-short baseline (USBL) and optical guiding system are applied separately as inputs of sub-filters, resulting in a fusion guiding algorithm adapted to AUV underwater docking systems. Results Simulation experiments demonstrate that the guiding process based on multi-source information fusion is feasible and possesses robust performance and adequate control and steering accuracy. Conclusions The proposed fusion guiding solution meets the engineering requirements of underwater docking operations. The results of this study can provide technical references for the underwater docking of AUVs.
- autonomous underwater vehicle /
- underwater docking /
- multi-sources information fusion algorithm /
- acoustic localization /
- optical localization

HTML全文

图 1 AUV回收作业对接引导的全过程

Figure 1. Whole process of guiding AUV docking in recovery operation

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图 2 AUV与移动目标实现对接的系统总体框架

Figure 2. General framework of implementation for AUV docking system with mobile platform

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图 3 多速率联邦扩展卡尔曼滤波器总体框架

Figure 3. General framework of federate extended Kalman filter with multi-rates

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图 4 多速率联邦扩展卡尔曼滤波数据处理流程

Figure 4. Data processing flow of federate extended Kalman filter with multi-rates

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图 5 导航坐标系和载体坐标系定义

Figure 5. Definitions of navigation and body coordinate system

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图 6 AUV回收对接的3种航行轨迹

Figure 6. Three trajectories of AUV docking in recovery operation

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图 7 AUV回收对接在不同轨迹下滤波估计的相对位置与真实值对比

Figure 7. Comparison of filter estimated relative position and true value for different trajectories of AUV docking in recovery operation

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