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A Triangle Matching Algorithm for Gravity-aided Navigation for Underwater Vehicles

Published online by Cambridge University Press:  17 October 2013

Zhenli Yang ,
Zhuangsheng Zhu  and
Weigao Zhao
Zhenli Yang*
Affiliation:
(Key Laboratory of Fundamental Science for National Defense-Novel Inertial Instrument & Navigation System Technology, Beihang University, Beijing, China)
Zhuangsheng Zhu
Affiliation:
(Key Laboratory of Fundamental Science for National Defense-Novel Inertial Instrument & Navigation System Technology, Beihang University, Beijing, China)
Weigao Zhao
Affiliation:
(Key Laboratory of Fundamental Science for National Defense-Novel Inertial Instrument & Navigation System Technology, Beihang University, Beijing, China)
*
(E-mail: 617188138@qq.com)
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Abstract

In this paper, a triangle matching algorithm using local gravity field maps is proposed to bound the drift errors inherent in Strapdown Inertial Navigation Systems (SINS) in gravity-aided navigation. This triangle matching algorithm has two main stages, the first is the initial matching stage, which has a coarse phase and a fine phase to address the large unknown initial errors made by INS, and the other is the tracking matching stage, which mainly aims at tracking the matching solution with the vehicle running in real time. Simulations were carried out using data for the Bohai Sea and South China Sea areas, to assess the effects of different initial errors on the matching solutions. Finally some experiments were carried out to evaluate the proposed algorithm. The results show that the triangle matching algorithm has some compelling advantages, such as a capability to address the large unknown initial errors made by INS, and good real-time quality of matching the gravity measurements with the local gravity maps.

Keywords

Gravity-aided navigationINS navigationTriangle matching algorithm
Type
Research Article
Information
The Journal of Navigation , Volume 67 , Issue 2 , March 2014 , pp. 227 - 247
Copyright
Copyright © The Royal Institute of Navigation 2013 

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