Empirical Mode Decomposition (EMD) of Potential Field Data: Airborne Gravity Data As an Example

In this paper, we introduce a newly developed method to process potential field data as an alternative to Fourier and wavelet based techniques. This new method is called Empirical Mode Decomposition (EMD) and was developed by Dr. Norden E. Huang at the NASA Goddard Space Flight Center (Huang et al. 1998). The EMD method is different from Fourier and wavelet transforms because it handles nonlinear and nonstationary signals.

[1]  Turner Valley, Canada - a Case History in Contemporary Airborne Gravity , 2002 .

[2]  N. Huang,et al.  The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis , 1998, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[3]  Gabriel Rilling,et al.  Empirical mode decomposition as a filter bank , 2004, IEEE Signal Processing Letters.