A Comprehensive Survey on the Integrity of Localization Systems
This survey extends and refines the existing definitions of integrity and protection level in localization systems (localization as a broad term, i.e., not limited to GNSS-based localization). In our definition, we study integrity from two aspects: quality and quantity. Unlike existing reviews, this...
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MDPI AG
2025-01-01
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| Online Access: | https://www.mdpi.com/1424-8220/25/2/358 |
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| author | Elias Maharmeh Zayed Alsayed Fawzi Nashashibi |
| author_facet | Elias Maharmeh Zayed Alsayed Fawzi Nashashibi |
| author_sort | Elias Maharmeh |
| collection | DOAJ |
| description | This survey extends and refines the existing definitions of integrity and protection level in localization systems (localization as a broad term, i.e., not limited to GNSS-based localization). In our definition, we study integrity from two aspects: quality and quantity. Unlike existing reviews, this survey examines integrity methods covering various localization techniques and sensors. We classify localization techniques as optimization-based, fusion-based, and SLAM-based. A new classification of integrity methods is introduced, evaluating their applications, effectiveness, and limitations. Comparative tables summarize strengths and gaps across key criteria, such as algorithms, evaluation methods, sensor data, and more. The survey presents a general probabilistic model addressing diverse error types in localization systems. Findings reveal a significant research imbalance: 73.3% of surveyed papers focus on GNSS-based methods, while only 26.7% explore non-GNSS approaches like fusion, optimization, or SLAM, with few addressing protection level calculations. Robust modeling is highlighted as a promising integrity method, combining quantification and qualification to address critical gaps. This approach offers a unified framework for improving localization system reliability and safety. This survey provides key insights for developing more robust localization systems, contributing to safer and more efficient autonomous operations. |
| format | Article |
| id | doaj-art-b3ae33922e8c4c589f71ef5499186c5b |
| institution | Kabale University |
| issn | 1424-8220 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
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| series | Sensors |
| spelling | doaj-art-b3ae33922e8c4c589f71ef5499186c5b2025-01-24T13:48:38ZengMDPI AGSensors1424-82202025-01-0125235810.3390/s25020358A Comprehensive Survey on the Integrity of Localization SystemsElias Maharmeh0Zayed Alsayed1Fawzi Nashashibi2Valeo Mobility Tech Center (VMTC), 6 Rue Daniel Costantini, 94000 Créteil, FranceValeo Mobility Tech Center (VMTC), 6 Rue Daniel Costantini, 94000 Créteil, FranceInria-ASTRA Team, 48 Rue Barrault, 75013 Paris, FranceThis survey extends and refines the existing definitions of integrity and protection level in localization systems (localization as a broad term, i.e., not limited to GNSS-based localization). In our definition, we study integrity from two aspects: quality and quantity. Unlike existing reviews, this survey examines integrity methods covering various localization techniques and sensors. We classify localization techniques as optimization-based, fusion-based, and SLAM-based. A new classification of integrity methods is introduced, evaluating their applications, effectiveness, and limitations. Comparative tables summarize strengths and gaps across key criteria, such as algorithms, evaluation methods, sensor data, and more. The survey presents a general probabilistic model addressing diverse error types in localization systems. Findings reveal a significant research imbalance: 73.3% of surveyed papers focus on GNSS-based methods, while only 26.7% explore non-GNSS approaches like fusion, optimization, or SLAM, with few addressing protection level calculations. Robust modeling is highlighted as a promising integrity method, combining quantification and qualification to address critical gaps. This approach offers a unified framework for improving localization system reliability and safety. This survey provides key insights for developing more robust localization systems, contributing to safer and more efficient autonomous operations.https://www.mdpi.com/1424-8220/25/2/358integrityprotection levellocalizationSLAMfault/outlier detectionrobust optimization |
| spellingShingle | Elias Maharmeh Zayed Alsayed Fawzi Nashashibi A Comprehensive Survey on the Integrity of Localization Systems Sensors integrity protection level localization SLAM fault/outlier detection robust optimization |
| title | A Comprehensive Survey on the Integrity of Localization Systems |
| title_full | A Comprehensive Survey on the Integrity of Localization Systems |
| title_fullStr | A Comprehensive Survey on the Integrity of Localization Systems |
| title_full_unstemmed | A Comprehensive Survey on the Integrity of Localization Systems |
| title_short | A Comprehensive Survey on the Integrity of Localization Systems |
| title_sort | comprehensive survey on the integrity of localization systems |
| topic | integrity protection level localization SLAM fault/outlier detection robust optimization |
| url | https://www.mdpi.com/1424-8220/25/2/358 |
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