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195739

GNSS Cycle Slip Detection and Estimation Using LSTM-based Autoencoder Model.

Article

Last updated: 04 Jan 2025

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Subjects

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Tags

Public Works Engineering

Abstract

Global Navigation Satellite Systems (GNSSs) are used in many navigation and positioning applications. Unfortunately, a GNSS signal may suffer from some errors, such as cycle slips, which deteriorate the positioning solution. A cycle slip is defined as a sudden jump by an integer number of cycles in the GNSS carrier phase observations. Signal blockage or/and high troposphere activities are the most common causes for GNSSs' cycle slips. Therefore, cycle slips should be detected and corrected to determine reliable positioning estimations. A new approach for cycle slip detection and repair is proposed based on a master-rover phase-difference with a deep Long Short-Term Memory (LSTM) neural network model; our SlipNet model can classify defective data where a cycle slip has occurred and then predict the exact epoch where the cycle slip(s) occurred. The proposed SlipNet network would be the first end-to-end learning framework to solve the integer ambiguity problem in GNSS measurements with high performance results, %99.7 detection and localization accuracy, and 0.045 MAE for slip estimation and recovery. These results are on par with the latest classical cycle slip detection methods of cycle slip detection and correction.

DOI

10.21608/bfemu.2021.195739

Keywords

GNSS, Cycle Slip, Slip Net, LSTM, Autoencoder

Authors

First Name

Ahmed

Last Name

Ragheb

MiddleName

E.

Affiliation

Associate professor of Surveying and Geodesy., Public Works Department., Ain Shams University., Faculty of Engineering., Cairo., Egypt.

Email

aragheb@eng.asu.edu.eg

City

-

Orcid

-

First Name

Ahmed

Last Name

Zekry

MiddleName

-

Affiliation

Department of Electrical and Computer Engineering, Queen’s University, Kingston, Canada

Email

amar@queensu.ca

City

-

Orcid

-

First Name

Mohamed

Last Name

Elhabiby

MiddleName

-

Affiliation

Associate professor., Public Works Departmen.t, Faculty of Engineering., Ain Shams University

Email

mmelhabiby@eng.asu.edu.eg

City

Cairo

Orcid

-

Volume

46

Article Issue

2

Related Issue

23998

Issue Date

2021-06-01

Receive Date

2021-04-30

Publish Date

2021-09-22

Page Start

31

Page End

40

Print ISSN

1110-0923

Online ISSN

2735-4202

Article File

BFEMU_Volume 46_Issue 2_Pages 31-40.pdf

PDF . 1.4MB

Link

https://bfemu.journals.ekb.eg/article_195739.html

Detail API

https://bfemu.journals.ekb.eg/service?article_code=195739

Order

15

Type

Research Studies

Type Code

1,205

Publication Type

Journal

Publication Title

MEJ. Mansoura Engineering Journal

Publication Link

https://bfemu.journals.ekb.eg/

MainTitle

GNSS Cycle Slip Detection and Estimation Using LSTM-based Autoencoder Model.

Details

Type

Article

Created At

22 Jan 2023