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 …

The global navigation satellite system-reflectometry (GNSS-R) field has experienced an
exponential growth as it is becoming relevant to many applications and has captivated the …

DEEP LEARNING FOR THE EARTH SCIENCES Explore this insightful treatment of deep
learning in the field of earth sciences, from four leading voices Deep learning is a …

In this paper, an effective schematic is developed for estimating soil moisture (SM) from
CYclone Global Navigation Satellite System (CYGNSS) data. Here, a three-layer model of …

A track of sea ice reflected Global Navigation Satellite System (GNSS) signal collected by
the TechDemoSat‐1 mission is processed to perform phase altimetry over sea ice. High …

In this letter, a scheme that uses convolutional neural networks (CNNs) is proposed for sea
ice detection and sea ice concentration (SIC) prediction from TechDemoSat-1 Global …

In this article, a retrieval algorithm based on the use of an artificial neural network (ANN) is
proposed for wind speed estimations from cyclone global navigation satellite system …

This study examines the potential of using bistatic radar reflections from the Global
Navigation Satellite System (GNSS) to classify sea ice types in the Arctic Ocean during the …

In this article, an effective schematic is developed for estimating sea ice thickness (SIT) from
the reflectivity (Γ) produced with TechDemoSat-1 (TDS-1) Global Navigation Satellite …

Knowledge of sea ice is critical for offshore oil and gas exploration, global shipping
industries, and climate change studies. During recent decades, Global Navigation Satellite …