Ten lectures on wavelets
Clear P-wave arrival of weak events and automatic onset determination using wavelet filter banks
Digital Signal Processing
New wavelet-based approach intended for the analysis of subtle features of complex natural signals
Pattern Recognition and Image Analysis
Two-dimensional autoregressive (2-D AR) model order estimation
IEEE Transactions on Signal Processing
| Hi-index | 0.00 |
In the present paper we will discuss a new wavelet-based approach aimed at processing and analyzing different features of complex geomagnetic signals. This approach makes it possible to automatically extract different kinds of disturbances in the Earth@?s magnetic field variations, which characterize solar activity and help to predict magnetic storms. In order to analyze geomagnetic signals wavelet packets are used in order to isolate local variations for quiet and perturbed periods and determine their intensity. Furthermore, a new automatic method of calculating the index of geomagnetic activity K is suggested on the basis of forming a quiet-day diurnal variation (Sq-curve). This method allows us to do calculations in the way that is closest to that developed by J. Bartels, who introduced the K-index in 1938. The results are compared with those obtained by INTERMAGNET and the original method of J. Bartels and the advantages of the suggested method are clearly demonstrated. For geomagnetic data collected in high-latitude regions of our planet it has become possible to reduce the error of estimating the K-index by 20% and unlike the technique used by INTERMAGNET here all the calculations can be done automatically. We will use geomagnetic signals that were kindly provided to us by the Institute of Cosmophysical Research and Radio Wave Propagation (Paratunka, Kamchatka region, Far East of Russia) for the period from January, 2002 till December, 2010.