  We investigate the effectiveness of the statistical radio frequency
interference (RFI) mitigation technique spectral kurtosis (SK) in the face of
simulated realistic RFI signals. 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 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 multi-scale SK, which
combines information from adjacent time-frequency bins to mitigate weaknesses
in single-scale \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. Multi-scale SK with at
least one extra channel can detect both the center channel and side-band
interference, flagging greater than 90% as long as the bin channel width is
wider in frequency than the RFI.
