Gravity gradiometry positioning system based on neuro-fuzzy modeling

被引：0

作者：

Rahmati S. ^{[1
]}

Kianfar K. ^{[2
]}

Kalat A.A. ^{[3
]}

机构：

[1] University of Birjand, Birjand

[2] Ghadr Research Centre, Imam Hoseyn University, Tehran

[3] Shahrood University of Technology, Shahrood

来源：

Gyroscopy and Navigation | 2015年 / 6卷 / 1期

关键词：

Fuzzy Rule; Inertial Navigation System; Gravity Gradient; Rough Terrain; Shuffle Frog Leaping Algorithm;

D O I：

10.1134/S2075108715010101

中图分类号：

学科分类号：

摘要：

This paper proposes a novel method for position determination by using neuro-fuzzy modeling and gravity gradient instrument data, which also can serve as a navigation aid to inertial navigation system using a Kalman filter. Since great majority of changes in gravity gradients are due to terrain, terrain elevation data are just used to model the gravity gradients at test location. To demonstrate the potential performance of this method, two cases including rough and smooth terrain are investigated, and impressive navigation accuracy is produced. Also the suitability of the proposed method for the use in different altitudes is compared. © 2015, Pleiades Publishing, Ltd.

引用

页码：16 / 24

页数：8

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