Cyclic Imaging for All-Sky Interference Forecasting with Array Radio Telescopes

Abstract

Radio Frequency Interference (RFI) is threatening modern radio astronomy. A classic approach to mitigate its impact on astronomical data involves discarding the corrupted time and frequency data samples through a process called flagging and blanking. We propose the exploitation of the cyclostationary properties of the RFI signals to reliably detect and predict their locations within an array radio telescope field-of-view, and dynamically schedule the astronomical observations such as to minimize the probability of RFI data corruption.