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A Low Complexity Integrated Navigation System for Underwater Vehicles

Published online by Cambridge University Press:  09 May 2018

Mehdi Emami  and
Mohammad Reza Taban
Mehdi Emami
Affiliation:
(Department of Electrical Engineering, Yazd University, Yazd, Iran)
Mohammad Reza Taban*
Affiliation:
(Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan 84156-83111, Iran)
*
(E-mail: [email protected])
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Abstract

This paper proposes a simplified algorithm for reducing the computational load of the conventional underwater integrated navigation system. The system usually comprises a three-dimensional accelerometer, a three-dimensional gyroscope, a three-dimensional Doppler Velocity Log (DVL) and a data fusion algorithm, such as a Kalman Filter (KF). Since the expected variations of roll, pitch and depth are small, these quantities are assumed to be constant, and the proposed system is designed in a two-dimensional form. Due to the low speed of the vehicle, the nonlinear dynamic equation of the velocity can be simplified in a linear form. We also simplify the conventional KF in order to avoid matrix multiplications and matrix inversions. The performance of the designed system is evaluated in a sea trial by an Autonomous Underwater Vehicle (AUV). The results show that the proposed system can significantly reduce the computational load of the conventional integrated navigation system without a significant reduction in position and velocity accuracy.

Keywords

DVLIntegrated navigation systemKalman filterInertial Navigation System (INS)Computational burden
Type
Research Article
Information
The Journal of Navigation , Volume 71 , Issue 5 , September 2018 , pp. 1161 - 1177
Copyright
Copyright © The Royal Institute of Navigation 2018 

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