Abstract The spectral analysis of magnetotelluric (MT) data for impedance tensor estimation requires the stationarity of measured magnetic (H) and electric (E) fields. However, it is well known that noise biases time-domain tensor estimates obtained via an iterative search by a descent algorithm to determine the least-mean-square residual between measured and estimated E data obtained from H data. To limit the noise that slows down, or even prevents convergence, the steepest descent step size is based upon the statistics of the residual (Bayes' estimation). With respect to uncorrelated noise, the time-domain technique is more robust than frequency-domain techniques. Furthermore, the technique requires only short-time stationarity.The time-domain technique is applied to data sets (Lincoln Line sites) from the EMSLAB Juan de Fuca project (Electromagnetic Sounding of the Lithosphere and Asthenosphere Beneath the Juan de Fuca Plate), as well as to data from a southern Italian site. The results of EMSLAB data analysis are comparable to those obtained by robust remote reference processing where larger data sets were used.