Robust, Remote Reference, and Jackknife MT Data Processing

A new set of computational procedures are proposed for estimating the magnetotelluric response functions from time series of the natural source electromagnetic field variations. These combine the remote reference method, which is effective at minimizing bias errors caused by uncorrelated noise on all data channels, with robust processing, which can eliminate the influence of outliers and other departures from Gauss-Markov optimality on regression estimates. Robust processing uses iterative, data-adaptive weighting of the Fourier-transformed time series to produce response functions that are statistically consistent.