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移动USBL测距辅助的UUV协同导航定位方法
引用本文:王银涛,贾晓宝,崔荣鑫,严卫生.移动USBL测距辅助的UUV协同导航定位方法[J].控制理论与应用,2022,39(11):2057-2064.
作者姓名:王银涛  贾晓宝  崔荣鑫  严卫生
作者单位:西北工业大学,中国航空工业集团公司洛阳电光设备研究所,西北工业大学,西北工业大学
基金项目:国家自然科学基金项目(U2141238)资助.
摘    要:针对无人水下航行器(UUV) 导航精度受惯性导航(INS) 影响较大的问题, 本文提出一种基于无人水面船 (USV)携带超短基线(USBL)对UUV进行移动式辅助导航定位的方法. 文中以USV上高精度INS和全球导航卫星系 统(GNSS)组合后的导航结果作为基准, 利用USBL测量得到的USV和UUV相对位置和姿态信息, 结合UUV的INS误 差方程, 建立了UUV协同导航系统的状态方程和观测方程, 并基于自适应卡尔曼滤波方法对UUV状态进行滤波估 计. 仿真和湖上实验结果表明, 文中所提方法可有效提升UUV导航精度.

关 键 词:无人水下航行器    无人水面船    自适应卡尔曼滤波    组合导航系统
收稿时间:2021/11/30 0:00:00
修稿时间:2023/2/13 0:00:00

Cooperative UUV navigation and positioning assisted by mobile USBL distance measurement
WANG Yin-tao,JIA Xiao-bao,CUI Rong-xin and YAN Wei-sheng.Cooperative UUV navigation and positioning assisted by mobile USBL distance measurement[J].Control Theory & Applications,2022,39(11):2057-2064.
Authors:WANG Yin-tao  JIA Xiao-bao  CUI Rong-xin and YAN Wei-sheng
Affiliation:Northwestern Polytechnical University,Luoyang Electro-Optical Equipment Research Institute of Aviation Industry Corporation of China,Northwestern Polytechnical University,Northwestern Polytechnical University
Abstract:The navigation accuracy of unmanned underwater vehicles (UUV) can be easily affected by inertial navigation systems (INS), which may cause severe consequences to the UUV system. To solve the above problem, this paper introduces a mobile navigation and positioning method for the UUVs by using an unmanned surface vehicle (USV)-assisted ultra short base line (USBL) system. Firstly, based on the highly accurate navigation results from the integration of INS and global navigation satellite system (GNSS) in the USV, the relative positions and attitudes are measured using USBL. Secondly, the state-space model and the observation model of the UUV-aided cooperative navigation system are then established by fusing INS error dynamics of the UUV. Thirdly, an estimation and filter scheme based on adaptive Kalman filters is used for obtaining the accurate estimates of the UUV states. Simulation and experimental results show that the proposed algorithm can effectively increase the UUV navigation and positioning accuracy.
Keywords:unmanned underwater vehicles  unmanned surface vehicles  adaptive Kalman filter  integrated navigation systems
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