自主式水下航行器水下回收融合引导技术方案及算法  

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

作　　者：赵蕊[1] 许建[1] ZHAO Rui;XU Jian(China Ship Development and Design Center,Wuhan 430064,China)

机构地区：[1]中国舰船研究设计中心,湖北武汉430064

出　　处：《中国舰船研究》2022年第1期212-220,共9页Chinese Journal of Ship Research

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。[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.

关 键 词：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 

分 类 号：U664.82[交通运输工程—船舶及航道工程]