Dispersion analysis of multi-modal waves based on the Reassigned Cross-S-Transform

The quantitative description of the propagation energy components in a signal is fundamental task processing. correct identification important because they carry information about medium which propagate. In this article, I introduce Reassigned Cross-S-Transform to estimate dispersion curves from time-varying signals, technique based on function maximization principles and time-frequency cross-correlation. RCST provides sharpened direct curve for multi-modal propagating waves. Furthermore, can be used with signals that are not synchronized same initial time. present examples studying degradation effects slowness due mode mixture reflected illustrate application artificially generated Ricker wavelets, real recordings seismic waves by an active source. Finally, using 2D numerical simulations wave through elastic layered medium, solve problem combining previously proposed extract Rayleigh signals.