GNSS Phase Scintillations

Publications

Correlation of Auroral Dynamics and GNSS Scintillation with an Autoencoder (NeurIPS ML4PS Workshop 2019)

Kara Lamb*, Garima Malhotra*, Athanasios Vlontzos*, Edward Wagstaff*, Atılım Günes Baydin, Anahita Bhiwandiwalla, Yarin Gal, Alfredo Kalaitzis, Anthony Reina, Asti Bhatt

^{_{(* indicates equal contribution)}}

Prediction of GNSS Phase Scintillations: A Machine Learning Approach (NeurIPS ML4PS Workshop 2019)

Kara Lamb*, Garima Malhotra*, Athanasios Vlontzos*, Edward Wagstaff*, Atılım Günes Baydin, Anahita Bhiwandiwalla, Yarin Gal, Alfredo Kalaitzis, Anthony Reina, Asti Bhatt

^{_{(* indicates equal contribution)}}

About the project

We undertook this work as part of the Living With Our Star challenge in 2019’s NASA Frontier Development Lab research programme. The overarching goal of the project was to improve the predictability of GNSS scintillations. GNSS is the generic term for a satellite navigation system. Signals from GNSS satellites are susceptible to interference caused by disturbances in the ionosphere, a region of the Earth’s upper atmosphere consisting of charged particles. These disturbances are known as scintillations. Current physical models are not capable of achieving the resolution necessary to predict these scintillations, and this project was an attempt to improve on predictive accuracy with a machine learning approach.