2019
Exploring Complex Time-series Representations for Riemannian Machine Learning of Radar Data
ICASSP 2019accepted
Classification of radar observations with machine learning tools is of primary importance for the identification of non-cooperative radar targets such as drones. These observations are made of complex-valued time series which possess a strong underlying structure. These signals can be processed thro…