Publication:
Artificial neural networks for hybrid inertial-satellite navigation systems: challenges, tasks and recent research

Loading...
Thumbnail Image

Date

ORCID

DOI

Journal Title

Journal ISSN

Volume Title

Publisher

National Technical University "Kharkiv Polytechnic Institute"

Research Projects

Organizational Units

Journal Issue

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.

Description

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.

Related resource link

Endorsement

Review

Supplemented By

Referenced By