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http://dx.doi.org/10.5302/J.ICROS.2016.15.0213

Navigation System of UUV Using Multi-Sensor Fusion-Based EKF  

Park, Young-Sik (Department of Electronic and Electric and Computer Engineering, Pusan National University)
Choi, Won-Seok (Department of Electronic and Electric and Computer Engineering, Pusan National University)
Han, Seong-Ik (Department of Electronic and Electric and Computer Engineering, Pusan National University)
Lee, Jang-Myung (Department of Electronic and Electric and Computer Engineering, Pusan National University)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.22, no.7, 2016 , pp. 562-569 More about this Journal
Abstract
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.
Keywords
EKF (Extended Kalman Filter); Kalman filter; localization of underwater; sensor fusion; IMU/DVL;
Citations & Related Records
Times Cited By KSCI : 7  (Citation Analysis)
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