A systematic review of machine learning techniques for GNSS use cases
A Siemuri, K Selvan, H Kuusniemi… - … on Aerospace and …, 2022 - ieeexplore.ieee.org
In terms of the availability and accuracy of positioning, navigation, and timing (PNT), the
traditional Global Navigation Satellite System (GNSS) algorithms and models perform well …
traditional Global Navigation Satellite System (GNSS) algorithms and models perform well …
Machine learning utilization in GNSS—Use cases, challenges and future applications
A Siemuri, H Kuusniemi, MS Elmusrati… - … on Localization and …, 2021 - ieeexplore.ieee.org
The algorithms and models of traditional global navigation satellite systems (GNSSs)
perform very well in terms of the availability and accuracy of positioning, navigation and …
perform very well in terms of the availability and accuracy of positioning, navigation and …
Deep neural network correlators for GNSS multipath mitigation
Machine learning and, more precisely, data-driven models are providing solutions where
physics-based models are intractable. This article discusses the use of deep learning …
physics-based models are intractable. This article discusses the use of deep learning …
A Multi-Input Convolutional Neural Networks Model for Earthquake Precursor Detection Based on Ionospheric Total Electron Content
Earthquakes occur all around the world, causing varying degrees of damage and
destruction. Earthquakes are by their very nature a sudden phenomenon and predicting …
destruction. Earthquakes are by their very nature a sudden phenomenon and predicting …
Deep learning of GNSS acquisition
Signal acquisition is a crucial step in Global Navigation Satellite System (GNSS) receivers,
which is typically solved by maximizing the so-called Cross-Ambiguity Function (CAF) as a …
which is typically solved by maximizing the so-called Cross-Ambiguity Function (CAF) as a …
Detecting GNSS spoofing using deep learning
Abstract Global Navigation Satellite System (GNSS) is pervasively used in position,
navigation, and timing (PNT) applications. As a consequence, important assets have …
navigation, and timing (PNT) applications. As a consequence, important assets have …
Augmented physics-based machine learning for navigation and tracking
T Imbiriba, O Straka, J Duník… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
This article presents a survey of the use of artificial intelligence/machine learning (AI/ML)
techniques in navigation and tracking applications, with a focus on the dynamical models …
techniques in navigation and tracking applications, with a focus on the dynamical models …
[PDF][PDF] Detecting GNSS spoofing using deep learning
Abstract Global Navigation Satellite System (GNSS) is pervasively used in position,
navigation, and timing (PNT) applications. As a consequence, important assets have …
navigation, and timing (PNT) applications. As a consequence, important assets have …
An adaptive Butterworth spectral-based graph neural network for detecting ionospheric total electron content precursor prior to the Wenchuan earthquake on 12 May …
JW Lin - Geocarto International, 2022 - Taylor & Francis
Abstract In this study, Global Ionosphere Maps (GIMs) were used to detect all total electron
content (TEC) precursors prior to the M w 7.9 Wenchuan earthquake at 06: 28: 01 (UTC) on …
content (TEC) precursors prior to the M w 7.9 Wenchuan earthquake at 06: 28: 01 (UTC) on …
Deep Learning of GNSS Signal Detection
P Borhani-Darian - 2023 - search.proquest.com
Abstract Global Navigation Satellite Systems (GNSS) is the de facto technology for Position,
Navigation, and Timing (PNT) applications when it is available. GNSS relies on one or more …
Navigation, and Timing (PNT) applications when it is available. GNSS relies on one or more …