Wavelet analysis of CHAMP flux gate magnetometer data

Abstract

Wavelet spectral analysis permits quantitative monitoring of the signal evolution by decomposing a time-series into a linear superposition of predefined mathematical waveforms, each with finite duration and narrow frequency content. Thus, the frequency range of the analyzing wavelets corresponds to the spectral content of time-series components. We present a wavelet analysis of 3 years of vector magnetic data from the CHAMP satellite mission. We have detected, identified and classified not only artificial noise sources (e.g. instrument problems and preprocessing errors) but also high frequency natural signals of external fields (e.g. F-region instabilities and pulsations). The results of this analysis will be used for: (a) consequent correction and flagging of the data, (b) derivation of a clean (undisturbed) dataset suitable for the purposes of crustal and main field modeling, and, (c) study of natural signals (e.g. F-region instabilities, pulsations) contained in the data. © 2005 Springer-Verlag Berlin Heidelberg.