Survey on signal processing for GNSS under ionospheric scintillation: Detection, monitoring, and mitigation
Ionospheric scintillation is the physical phenomena affecting radio waves coming from the
space through the ionosphere. Such disturbance is caused by ionospheric electron-density …
space through the ionosphere. Such disturbance is caused by ionospheric electron-density …
New insights and best practices for the successful use of Empirical Mode Decomposition, Iterative Filtering and derived algorithms
Abstract Algorithms based on Empirical Mode Decomposition (EMD) and Iterative Filtering
(IF) are largely implemented for representing a signal as superposition of simpler well …
(IF) are largely implemented for representing a signal as superposition of simpler well …
Magnetospheric–ionospheric–lithospheric coupling model. 1: Observations during the 5 August 2018 Bayan Earthquake
The short-term prediction of earthquakes is an essential issue connected with human life
protection and related social and economic matters. Recent papers have provided some …
protection and related social and economic matters. Recent papers have provided some …
Disentangling ionospheric refraction and diffraction effects in GNSS raw phase through fast iterative filtering technique
We contribute to the debate on the identification of phase scintillation induced by the
ionosphere on the global navigation satellite system (GNSS) by introducing a phase …
ionosphere on the global navigation satellite system (GNSS) by introducing a phase …
From the Sun to Earth: Effects of the 25 August 2018 geomagnetic storm
On 25 August 2018 the interplanetary counterpart of the 20 August 2018 coronal mass
ejection (CME) hit Earth, giving rise to a strong G3 geomagnetic storm. We present a …
ejection (CME) hit Earth, giving rise to a strong G3 geomagnetic storm. We present a …
Iterative filtering as a direct method for the decomposition of nonstationary signals
A Cicone - Numerical Algorithms, 2020 - Springer
Abstract The Iterative Filtering method is a technique developed recently for the
decomposition and analysis of nonstationary and nonlinear signals. In this work, we propose …
decomposition and analysis of nonstationary and nonlinear signals. In this work, we propose …
ResNet-integrated very early bolt looseness monitoring based on intrinsic feature extraction of percussion sounds
Very early bolt looseness monitoring has been a challenge in the field of structural health
monitoring. The authors have conducted a further study of the previous researches, with the …
monitoring. The authors have conducted a further study of the previous researches, with the …
The variational kernel-based 1-D convolutional neural network for machinery fault diagnosis
One-dimensional convolutional neural network (1-D CNN) can be directly applied to process
temporal signals in the machinery fault diagnosis. However, it requires a large amount of …
temporal signals in the machinery fault diagnosis. However, it requires a large amount of …
Numerical analysis for iterative filtering with new efficient implementations based on FFT
The development of methods able to extract hidden features from non-stationary and non-
linear signals in a fast and reliable way is of high importance in many research fields. In this …
linear signals in a fast and reliable way is of high importance in many research fields. In this …
Multi-instrument detection in Europe of ionospheric disturbances caused by the 15 January 2022 eruption of the Hunga volcano
TGW Verhulst, D Altadill, V Barta… - Journal of Space …, 2022 - swsc-journal.org
The 15 January 2022 eruption of the Hunga volcano provides a unique opportunity to study
the reaction of the ionosphere to large explosive events. In particular, this event allows us to …
the reaction of the ionosphere to large explosive events. In particular, this event allows us to …