NDLI: Research on the navigation system of a class of underwater vehicle based on USBL

Content Provider	IEEE Xplore Digital Library
Author	Kaizhou Liu Jing Li Wei Guo Puqiang Zhu Junbao Zeng Xiaohui Wang
Copyright Year	2011
Description	Author affiliation: Robotics State Key Laboratory, Shenyang Institute of Automation, CAS, Liaoning China (Kaizhou Liu; Jing Li; Wei Guo; Puqiang Zhu; Junbao Zeng; Xiaohui Wang)
Abstract	This paper presents a novel unscented Kalman filter (UKF) used for navigation of Human Occupied Vehicle (HOV) based directly on the nonlinear sensor readings of an Ultra-short Baseline (USBL), a Doppler Velocity Log (DVL), a fiber optic gyrometer and a depth sensor. The HOV motion and the USBL observations are highly non-linear processes which contain unknown noise. A UKF is therefore chosen as a suitable data fusion technique. For the low rate positional measurements of USBL and the drift error of the DVL, the presented UKF fuses the information from these sensors to produce a more accurate estimate of three-dimensional position, orientation (heading), and velocity of the HOV. MATLAB simulations conducted with respect to the data obtained from previous sea trial illustrate the effectiveness of our proposed method.
Starting Page	1
Ending Page	6
File Size	743708
Page Count	6
File Format	PDF
ISBN	9781457714276
e-ISBN	9780933957398
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-09-19
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	MTS
Subject Keyword	Sea measurements Covariance matrix Vehicles Kalman filters Sonar navigation Acoustic measurements unscented Kalman filter (UKF) Human Occupied Vehicle (HOV) underwater vehicle navigation system
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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