  Interfering signals such as Radio Frequency Interference from ubiquitous
satellite constellations are becoming an endemic problem in fields involving
physical observations of the electromagnetic spectrum. To address this we
propose a novel data cleaning methodology. Contamination is simultaneously
flagged and managed at the likelihood level. It is modeled in a Bayesian
fashion through a piecewise likelihood that is constrained by a Bernoulli prior
distribution. The techniques described in this paper can be implemented with
just a few lines of code.
