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
相关论文
共 20 条
  • [1] Choi Y.H., Kim K.J., Robust path tracking control for autonomous underwater vehicle with variable speed, Korea Intelligent Information System Society, 20, 4, pp. 476-482, (2010)
  • [2] Lee K.S., Yoon H.B., Improvement of position estimation based on the multi sensor fusion in underwater unmanned vehicles, Korea Intelligent Information System Society, 21, 2, pp. 178-185, (2011)
  • [3] Fossen T.I., Guidance and Control of Ocean Vehicles, (1994)
  • [4] Larsen M., High performance Doppler-inertial navigationexperimental results, OCEANS 2000 MTS/IEEE Conference and Exhibition, 2, pp. 1149-1456, (2000)
  • [5] McEwen R., Thomas H., Weber D., Psota F., Performance of an AUV navigation system at arctic latitudes, IEEE Journal of Oceanic Engineering, 30, 2, pp. 443-454, (2005)
  • [6] Kussat N.H., Chadwell C.D., Zimmerman R., Absolute positioning of an autonomous underwater vehicle using GPS and acoustic measurements, IEEE Journal of Oceanic Engineering, 30, 1, pp. 153-164, (2005)
  • [7] Hong H.S., Yoon U.T., The design of in-motion alignment system for the sdins of an underwater vehicle, Institute of Control Robotics and Systems, 3, 1, pp. 164-169, (2000)
  • [8] Kim S.P., "Understanding of Kalmanfilter (Using MATLAB),", (2010)
  • [9] Jeong J.Y., Kim H.S., A study on the GPS/INS integration and GPS compensation algorithm based on the particle filter, Journal of The Institute of Electronics Engineers of Korea, 50, 6, pp. 267-275, (2013)
  • [10] Jeon C.W., Lee J.G., The error analysis of the attitude computation algorithm for the SDINS, The Korean Society for Aeronautical and Space Sciences, 15, 2, pp. 50-58, (1988)
12