摘要：We investigate the effectiveness of the statistical radio frequency interference (RFI) mitigation technique spectral kurtosis ($\widehat{{SK}}$) in the face of simulated realistic RFI signals. $\widehat{{SK}}\,$ estimates the kurtosis of a collection of M power values in a single channel and provides a detection metric that is able to discern between human-made RFI and incoherent astronomical signals of interest. We test the ability of $\widehat{{SK}}\,$ to flag signals with various representative modulation types, data rates, duty cycles, and carrier frequencies. We flag with various accumulation lengths M and implement multiscale $\widehat{{SK}}$, which combines information from adjacent time-frequency bins to mitigate weaknesses in single-scale $\widehat{{SK}}$. We find that signals with significant sidelobe emission from high data rates are harder to flag, as well as signals with a 50% effective duty cycle and weak signal-to-noise ratios. Multiscale $\widehat{{SK}}$ with at least one extra channel can detect both the center channel and sideband interference, flagging greater than 90% as long as the bin channel width is wider in frequency than the RFI.
