Abstract
We introduce a new method for estimating the geomagnetic field. The method is based on a combination of a wavelet transform with radial basis neural networks. In the method, the recorded geomagnetic field variations are decomposed into different-scale components and the degree of disturbance of each component is estimated, enabling the conclusion about the field state. For the verification of the method, we used geomagnetic data from the "Paratunka" station (Paratunka, Kamchatka region, data registration is carried out by IKIR FEB RAS). Analysis of the spectral-temporal characteristics of geomagnetic field variations during periods of moderate and strong magnetic storms was performed. Weak perturbations were detected in the geomagnetic field before the storms. The obtained results have confirmed the effectiveness of the proposed method.
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