Video Imputation and Prediction Methods with Applications in Space Weather

Oregon Convention Center 

The total electron content (TEC) maps can be used to estimate the signal delay of GPS due to the ionospheric electron content between a receiver and a satellite. This delay can result in a GPS positioning error. Thus, it is crucial to monitor & forecast the TEC maps. However, the observed TEC maps have big patches of missingness in the ocean and scattered small areas on the land. In this talk, I first present extensions of existing matrix completion algorithms to achieve TEC map reconstruction, accounting for spatial smoothness and temporal consistency while preserving essential structures of the TEC maps. We show that our proposed method achieves better reconstructed TEC maps as compared to existing methods in the literature. Then, I present a new model for forecasting time series data distributed on a matrix-shaped spatial grid, using the historical spatiotemporal data and auxiliary vector-valued time series data. We model the matrix time series as an auto-regressive process, where a future matrix is jointly predicted by the historical values of the matrix time series and an auxiliary vector time series. Asymptotic results and numerical illustrations with TEC data will be given.