Navigation system of uuv using multi-sensor fusion-based EKF

被引:0
|
作者
Park Y.-S. [1 ]
Choi W.-S. [1 ]
Han S.-I. [1 ]
Lee J.-M. [1 ]
机构
[1] Department of Electronic and Electric and Computer Engineering, Pusan National University
来源
Lee, Jang-Myung (jmlee@pusan.ac.kr) | 1600年 / Institute of Control, Robotics and Systems卷 / 22期
关键词
EKF (Extended Kalman Filter); IMU/DVL; Kalman filter; Localization of underwater; Sensor fusion;
D O I
10.5302/J.ICROS.2016.15.0213
中图分类号
学科分类号
摘要
This paper proposes a navigation system with a robust localization method for an underwater unmanned vehicle. For robust localization with IMU (Inertial Measurement Unit), a DVL (Doppler Velocity Log), and depth sensors, the EKF (Extended Kalman Filter) has been utilized to fuse multiple nonlinear data. Note that the GPS (Global Positioning System), which can obtain the absolute coordinates of the vehicle, cannot be used in the water. Additionally, the DVL has been used for measuring the relative velocity of the underwater vehicle. The DVL sensor measures the velocity of an object by using Doppler effects, which cause sound frequency changes from the relative velocity between a sound source and an observer. When the vehicle is moving, the motion trajectory to a target position can be recorded by the sensors attached to the vehicle. The performance of the proposed navigation system has been verified through real experiments in which an underwater unmanned vehicle reached a target position by using an IMU as a primary sensor and a DVL as the secondary sensor. © ICROS 2016.
引用
收藏
页码:562 / 569
页数:7
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