Публікація: Artificial neural networks for hybrid inertial-satellite navigation systems: challenges, tasks and recent research
| dc.contributor.author | Lashchenko, O. L. | |
| dc.date.accessioned | 2025-10-09T07:43:57Z | |
| dc.date.issued | 2025 | |
| dc.description.abstract | This paper addresses the problem of unreliable or falsified GNSS signals and presents advanced methodologies for their detection. The focus has been made on the integration of machine learning techniques, particularly Artificial Neural Networks (ANNs) into hybrid navigation systems to model temporal and spatial anomalies in GNSS data, enabling the system to distinguish between authentic and corrupted signals. | |
| dc.identifier.citation | Lashchenko O. L. Artificial neural networks for hybrid inertial-satellite navigation systems: challenges, tasks and recent research [Electronic resours] / O. L. Lashchenko ; thesis supervisor V. B. Uspenskyi // An Innovative Model of Research Projects Aimed at the Integration of Ukraine into the European Scientific Space : book of abstr. an Annual Intern. PhD Conf., April 24, 2025 / National Technical University "Kharkiv Polytechnic Institute". – Electronic text data. – Kharkiv : NTU "KhPI", 2025. – P. 146-147. | |
| dc.identifier.uri | https://repository.kpi.kharkov.ua/handle/KhPI-Press/93844 | |
| dc.language.iso | en | |
| dc.publisher | National Technical University "Kharkiv Polytechnic Institute" | |
| dc.subject | GNSS | |
| dc.subject | inertial navigation | |
| dc.subject | artificial neural networks | |
| dc.title | Artificial neural networks for hybrid inertial-satellite navigation systems: challenges, tasks and recent research | |
| dc.type | Article | |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | c03ebf2f-4c62-4ffb-82eb-8a2151d24d4e | |
| relation.isAuthorOfPublication.latestForDiscovery | c03ebf2f-4c62-4ffb-82eb-8a2151d24d4e |
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