2021).Īs RFI encroaches more and more into radio bands of scientific interest, astronomical signals will increasingly be overlapped by harmful interference, so it is also important to devise and test RFI mitigation techniques that can detect and remove human-made signals without negatively impacting scientific data. Nonastronomical science such as radio sensing for meteorologic and geophysical services compete with RFI produced by ground-based transmitters or reflections of space-based transmitters (Andrews et al. 2019), and high-redshift H i and Epoch of Reionization surveys have to deal with air traffic radar, satellite TV/phone services, and FM radio broadcasts (Offringa et al. Galactic and extragalactic imaging in the lower half of the L band (1000–1400 MHz) suffer from imaging artifacts produced by GPS and communication satellite transmissions (Hess et al. While policy groups such as the International Telecommunication Union and other national organizations set standards for small protected radio astronomy bands scattered across the spectrum, astronomers are more often than not collecting data in unprotected bands that are rife with RFI. In the face of ever-increasing human-made radio frequency interference (RFI) and larger data sets, there exists a need for new techniques of automated RFI mitigation. Multiscale 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. 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. We flag with various accumulation lengths M and implement multiscale, which combines information from adjacent time-frequency bins to mitigate weaknesses in single-scale. We test the ability of to flag signals with various representative modulation types, data rates, duty cycles, and carrier frequencies. 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 investigate the effectiveness of the statistical radio frequency interference (RFI) mitigation technique spectral kurtosis ( ) in the face of simulated realistic RFI signals.