Cyclic spatial filtering in radio astronomy: Application to LOFAR data

Radio astronomical observations are increasingly corrupted by radio frequency interference, and real-time filtering algorithms are becoming essential. New generations of radio telescopes will be based on antenna arrays providing the possibility of applying spatial filtering techniques. In this paper we compare the performance of two different approaches based on subspace decomposition of respectively the classical array correlation matrix and the cyclic array correlation matrix. This comparison is done through simulation on synthetic data and through simulations on real data acquired with the new generation low frequency array radio telescope LOFAR.