Data-Driven Analysis of PNT Resilience: Insights and Lessons from Jammertest 2024 Vehicular Data

dc.contributor.authorYliaho, Jaakko
dc.contributor.authorVälisuo, Petri
dc.contributor.authorAhmadi, Elham
dc.contributor.authorSelvan, Kannan
dc.contributor.authorElsanhoury, Mahmoud
dc.contributor.authorKuusniemi, Heidi
dc.contributor.departmentfi=Digital Economy|en=Digital Economy|
dc.contributor.orcidhttps://orcid.org/0000-0002-7508-1701
dc.contributor.orcidhttps://orcid.org/0000-0002-9195-4613
dc.date.accessioned2026-01-20T10:51:00Z
dc.date.issued2025
dc.description.abstractInterference in Global Navigation Satellite Systems (GNSS), and the related mitigation approaches, has long been a researched topic. However, the need to test equipment, algorithms and necessary sensor fusion under real interference has been very much needed, but the opportunities to do so have been available only for a chosen few. In the recent few years, Norwegian authorities have provided a week-long GNSS interference testing opportunity to the GNSS community. Jammertest is open for research institutions, commercial actors, military and other authorities. The organizers provide a totally unique event without a participation fee, and they encourage to openly publish and disseminate the results. This paper documents the experiments done during Jammertest 2024, describes the dataset collected, provides some insight into the research done with the collected data and finally promises to openly publish the collected dataset for others to use. The dataset contains mostly interference data collected while in motion. The test equipment used was mounted in and on a test vehicle.en
dc.description.notification© 2025 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
dc.description.reviewstatusfi=vertaisarvioitu|en=peerReviewed|
dc.embargo.lift2027-06-12
dc.embargo.terms2027-06-12
dc.format.pagerange398-403
dc.identifier.citationYliaho, J., Välisuo, P., Ahmadi, E., Selvan, K., Elsanhoury, M., & Kuusniemi, H. (2025). Data-Driven Analysis of PNT Resilience: Insights and Lessons from Jammertest 2024 Vehicular Data. In 2025 IEEE/ION Position, Location and Navigation Symposium (PLANS), 398-403. IEEE. https://doi.org/10.1109/plans61210.2025.11028414
dc.identifier.isbn979-8-3315-2317-6
dc.identifier.urihttps://osuva.uwasa.fi/handle/11111/19667
dc.identifier.urnURN:NBN:fi-fe202601205154
dc.language.isoen
dc.publisherIEEE
dc.relation.conferenceIEEE/ION Position, Location and Navigation Symposium (PLANS)
dc.relation.doihttps://doi.org/10.1109/plans61210.2025.11028414
dc.relation.funderSuomen Akatemiafi
dc.relation.funderAcademy of Finlanden
dc.relation.grantnumber359847
dc.relation.isbn979-8-3315-2318-3
dc.relation.ispartof2025 IEEE/ION Position, Location and Navigation Symposium (PLANS)
dc.relation.ispartofjournalIEEE/ION Position Location and Navigation Symposium
dc.relation.issn2153-3598
dc.relation.issn2153-358X
dc.relation.urlhttps://doi.org/10.1109/plans61210.2025.11028414
dc.relation.urlhttps://urn.fi/URN:NBN:fi-fe202601205154
dc.source.identifierWOS:001560101700048
dc.source.identifier2-s2.0-105009237007
dc.source.identifier7b3147fc-1718-471f-a77c-9de7a523091a
dc.source.metadataSoleCRIS
dc.subjectPositioning
dc.subjectGNSS interference
dc.subjectjamming
dc.subjectspoofing
dc.subjectJammertest
dc.subjectexperimental data
dc.subjectvehicular navigation
dc.subjectsensor fusion
dc.subject.disciplinefi=Tietotekniikka tekn|en=Information Technology tech|
dc.subject.disciplinefi=Automaatiotekniikka|en=Automation Technology|
dc.subject.disciplinefi=Tietotekniikka tekn|en=Information Technology tech|
dc.subject.disciplinefi=Tietotekniikka tekn|en=Information Technology tech|
dc.subject.disciplinefi=Tietotekniikka tekn|en=Information Technology tech|
dc.subject.disciplinefi=Tietotekniikka tekn|en=Information Technology tech|
dc.titleData-Driven Analysis of PNT Resilience: Insights and Lessons from Jammertest 2024 Vehicular Data
dc.type.okmfi=A4 Vertaisarvioitu artikkeli konferenssijulkaisussa|en=A4 Article in conference proceedings (peer-reviewed)|
dc.type.publicationarticle
dc.type.versionacceptedVersion

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