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30810

Fusion of Low-Cost MEMS IMU/GPS Integrated Navigation System

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Last updated: 04 Jan 2025

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Abstract

In this paper, the multi-sensor data fusion technique based on fuzzy clustering is used to fuse the data from low cost MEMS IMUs to build an INS model. Using this model, the inertial navigation data PVA is extracted. The navigation data PVA is integrated with the GPS data using Kalman filters to build an accurate navigation system of an UAV. Simulation results show that the method can achieve higher accuracy solutions with low cost IMU sensors and improve the performance of
integrated navigation system.

DOI

10.21608/iceeng.2012.30810

Keywords

Data fusion, fuzzy, data clustering, Inertial Navigation system (INS), Global Navigation system(GPS), Kalman Filter(KF), andINS/GPS Integration

Authors

First Name

A.

Last Name

Abosekeen

MiddleName

D.

Affiliation

Master Student,M.T.C, Egyptian Air Forces.

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Orcid

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First Name

A.

Last Name

Abdalla

MiddleName

E.

Affiliation

Assoc. Prof, Dean of M.T.C,M.T.C, Egyptian Air Forces.

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Volume

8

Article Issue

8th International Conference on Electrical Engineering ICEENG 2012

Related Issue

5272

Issue Date

2012-05-01

Receive Date

2019-04-28

Publish Date

2012-05-01

Page Start

1

Page End

23

Print ISSN

2636-4433

Online ISSN

2636-4441

Article File

ICEENG_Volume 8_Issue 8th International Conference on Electrical Engineering ICE….pdf

PDF . 834.2kB

Link

https://iceeng.journals.ekb.eg/article_30810.html

Detail API

https://iceeng.journals.ekb.eg/service?article_code=30810

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Original Article

Type Code

833

Publication Type

Journal

Publication Title

The International Conference on Electrical Engineering

Publication Link

https://iceeng.journals.ekb.eg/

MainTitle

Fusion of Low-Cost MEMS IMU/GPS Integrated Navigation System

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Article

Created At

22 Jan 2023