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Estimation of GPS Position Using Iterative Least Squares and Extended Kalman Filter

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Last updated: 25 Dec 2024

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Abstract

Global Positioning System (GPS) is being used in aviation, nautical navigation and the orientation ashore. Further, it is used in land surveying and other applications where the determination of the exact position is required. Although GPS is known as a precise positioning system, there are several error sources which are categorized into three main groups including errors related to satellites, propagation and GPS receivers. In this paper we focus on the estimation of the receiver coordinates of a fixed point based on pseudorange measurements of a single GPS receiver. The estimation of the unknowns is achieved by introducing an Extended Kalman Filter (EKF) and Iterative Least Square (ILS) that processes. Kalman filter is the method most often used nowadays. It is based on some assumptions and if all the assumptions are met it can offer optimal estimation and prediction. The EKF not only works well in practice, but also it is theoretically attractive because it has been shown that it is the filter that minimizes the variance of the estimation mean square error.

DOI

10.21608/erjm.2014.66880

Authors

First Name

M. I.

Last Name

Doma

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Affiliation

1. Civil Engineering Department, Faculty of Engineering, Menoufia University ,Egypt

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Orcid

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First Name

A. T.

Last Name

Sedeek

MiddleName

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Affiliation

Civil Engineering Department, Faculty of Engineering, Delta University, Egypt

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Volume

37

Article Issue

1

Related Issue

10097

Issue Date

2014-01-01

Receive Date

2019-12-30

Publish Date

2014-01-01

Page Start

115

Page End

121

Print ISSN

1110-1180

Online ISSN

3009-6944

Link

https://erjm.journals.ekb.eg/article_66880.html

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https://erjm.journals.ekb.eg/service?article_code=66880

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12

Type

Original Article

Type Code

1,118

Publication Type

Journal

Publication Title

ERJ. Engineering Research Journal

Publication Link

https://erjm.journals.ekb.eg/

MainTitle

Estimation of GPS Position Using Iterative Least Squares and Extended Kalman Filter

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Article

Created At

22 Jan 2023