  CRUSH is an approach to data analysis under noise interference, developed
specifically for submillimeter imaging arrays. The method uses an iterated
sequence of statistical estimators to separate source and noise signals. Its
filtering properties are well-characterized and easily adjusted to preference.
Implementations are well-suited for parallel processing and its computing
requirements scale linearly with data size -- rendering it an attractive
approach for reducing the data volumes from future large arrays.
