Adaptive Prefiltering for Nonnegative Discrete Spectrum of Relaxations

Recent developments in the estimation of the discrete spectrum of relaxation frequencies (DSRFs) has opened doors to more robust subsurface target discrimination using electromagnetic induction measurements. In particular, a nonnegative least squares DSRF (NNLSQ-DSRF) estimation method has been shown to be robust and free from parameter tuning. In this letter, we propose an adaptive prefiltering process to complement the NNLSQ-DSRF where we attempt to linearly combine measurements and produce a filtered signal that is very likely to have a nonnegative DSRF, as well as an enhanced signal-to-noise ratio. Using synthetic and field data, we demonstrate that the proposed adaptive prefilter can effectively produce signals with nonnegative DSRFs.