Enhanced Deep Fusion Filter for Low-Cost INS/GPS Integration

A Master of Science thesis in Mechatronics Engineering by Mohamed Ismail Abdelghani entitled, “Enhanced Deep Fusion Filter for Low-Cost INS/GPS Integration”, submitted in April 2024. Thesis advisor is Dr. Mohammad Jaradat and thesis co-advisor is Dr. Mamoun Abdel-Hafez. Soft copy is available (Thesi...

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محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Abdelghani, Mohamed Ismail (author)
التنسيق: doctoralThesis
منشور في: 2024
الموضوعات:
الوصول للمادة أونلاين:https://hdl.handle.net/11073/25632
الوسوم: إضافة وسم
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author Abdelghani, Mohamed Ismail
author_facet Abdelghani, Mohamed Ismail
author_role author
dc.contributor.none.fl_str_mv Jaradat, Mohammad
Abdel-Hafez, Mamoun
dc.creator.none.fl_str_mv Abdelghani, Mohamed Ismail
dc.date.none.fl_str_mv 2024-09-26T07:52:06Z
2024-09-26T07:52:06Z
2024-04
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv 35.232-2024.39
https://hdl.handle.net/11073/25632
dc.language.none.fl_str_mv en_US
dc.subject.none.fl_str_mv Autonomous Navigation
Sensor Fusion
Artificial Intelligence
Kalman Filter
dc.title.none.fl_str_mv Enhanced Deep Fusion Filter for Low-Cost INS/GPS Integration
dc.type.none.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/doctoralThesis
description A Master of Science thesis in Mechatronics Engineering by Mohamed Ismail Abdelghani entitled, “Enhanced Deep Fusion Filter for Low-Cost INS/GPS Integration”, submitted in April 2024. Thesis advisor is Dr. Mohammad Jaradat and thesis co-advisor is Dr. Mamoun Abdel-Hafez. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).
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oai_identifier_str oai:repository.aus.edu:11073/25632
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spelling Enhanced Deep Fusion Filter for Low-Cost INS/GPS IntegrationAbdelghani, Mohamed IsmailAutonomous NavigationSensor FusionArtificial IntelligenceKalman FilterA Master of Science thesis in Mechatronics Engineering by Mohamed Ismail Abdelghani entitled, “Enhanced Deep Fusion Filter for Low-Cost INS/GPS Integration”, submitted in April 2024. Thesis advisor is Dr. Mohammad Jaradat and thesis co-advisor is Dr. Mamoun Abdel-Hafez. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).College of EngineeringMultidisciplinary ProgramsMaster of Science in Mechatronics Engineering (MSMTR)Jaradat, MohammadAbdel-Hafez, Mamoun2024-09-26T07:52:06Z2024-09-26T07:52:06Z2024-04info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdf35.232-2024.39https://hdl.handle.net/11073/25632en_USoai:repository.aus.edu:11073/256322025-06-26T12:20:44Z
spellingShingle Enhanced Deep Fusion Filter for Low-Cost INS/GPS Integration
Abdelghani, Mohamed Ismail
Autonomous Navigation
Sensor Fusion
Artificial Intelligence
Kalman Filter
status_str publishedVersion
title Enhanced Deep Fusion Filter for Low-Cost INS/GPS Integration
title_full Enhanced Deep Fusion Filter for Low-Cost INS/GPS Integration
title_fullStr Enhanced Deep Fusion Filter for Low-Cost INS/GPS Integration
title_full_unstemmed Enhanced Deep Fusion Filter for Low-Cost INS/GPS Integration
title_short Enhanced Deep Fusion Filter for Low-Cost INS/GPS Integration
title_sort Enhanced Deep Fusion Filter for Low-Cost INS/GPS Integration
topic Autonomous Navigation
Sensor Fusion
Artificial Intelligence
Kalman Filter
url https://hdl.handle.net/11073/25632