Radio Frequency Interference Excision Using Spectral Domain Statistics

A radio frequency interference (RFI) excision algorithm based on spectral domain statistics is proposed and implemented in software. The algorithm requires the use of two memory buffers, S1 and S2, in which the first two powers of M power spectral density (PSD) estimates, obtained via Fast Fourier Transform (FFT), are accumulated and used to form a Spectral Kurtosis (SK) estimator, M(MS2/S 1 − 1)/(M − 1), whose expected statistical variance is used to define a 3σ ' 3 √ 4/M RFI detection threshold. The performance of the algorithm is theoretically evaluated for different time domain RFI characteristics and signal to noise ratios, η. It is shown that only M ≥ 36(1 + 1/η) PSD estimates need to be accumulated in order to discriminate a monochromatic RFI signal against a gaussian background. The theoretical performance of the algorithm for intermittent RFI (RFI present in R out of M PSD estimates) is evaluated and shown to depend greatly on the duty cycle, d = R/M . The algorithm is most effective for d = 1/(4 + η), but cannot distinguish RFI from gaussian noise at any η when d = 0.5. The expected efficiency and robustness of the algorithm are tested using data from the newly designed FASR Subsystem Testbed (FST, Liu et al. 2007) radio interferometer operating at the Owens Valley Solar Array (OVSA, Gary & Hurford 1999). The ability of the algorithm to discriminate RFI against the temporally and spectrally complex radio emission produced during solar radio bursts is demonstrated. Subject headings: Sun: radio radiation; instrumentation: spectrographs; instrumentation: interferome-