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Development and Performance Validation of a Navigation System for an Underwater Vehicle

Published online by Cambridge University Press:  26 January 2016

R. Ramesh ,
V. Bala Naga Jyothi ,
N. Vedachalam ,
G.A. Ramadass  and
M.A. Atmanand
R. Ramesh*
Affiliation:
(National Institute of Ocean Technology, Ministry of Earth Sciences, Chennai, India)
V. Bala Naga Jyothi
Affiliation:
(National Institute of Ocean Technology, Ministry of Earth Sciences, Chennai, India)
N. Vedachalam
Affiliation:
(National Institute of Ocean Technology, Ministry of Earth Sciences, Chennai, India)
G.A. Ramadass
Affiliation:
(National Institute of Ocean Technology, Ministry of Earth Sciences, Chennai, India)
M.A. Atmanand
Affiliation:
(National Institute of Ocean Technology, Ministry of Earth Sciences, Chennai, India)
*
(E-mail: rramesh@niot.res.in)
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Abstract

Underwater position data is a key requirement for the navigation and control of unmanned underwater vehicles. The proposed navigation scheme can be used in any vessel or boat for any shallow water vehicle. This paper presents the position estimation algorithm developed for shallow water Remotely Operated Vehicles (ROVs) using attitude data and Doppler Velocity Log data with the initial position from the Global Positioning System (GPS). The navigational sensors are identified using the in-house developed simulation tool in MATLAB, based on the requirement of a position accuracy of less than 5%. The navigation system is built using the identified sensors, Kalman filter and navigation algorithm, developed in LabVIEW software. The developed system is tested and validated for position estimation, with an emulator consisting of a GPS-aided fibre optic gyro-based inertial navigation system as a reference, and it is found that the developed navigation system has a position error of less than 5%.

Keywords

EmulatorDoppler Velocity LogPosition estimationRemotely Operated Vehicle
Type
Research Article
Information
The Journal of Navigation , Volume 69 , Issue 5 , September 2016 , pp. 1097 - 1113
Copyright
Copyright © The Royal Institute of Navigation 2016 

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