Abstract
This paper discusses the main aspects of geomagnetic data processing using the wavelet transform. The wavelet transform is shown to be efficient for automatic extraction of unperturbed level of the horizontal component of the Earth’s magnetic field. As a result, it becomes possible to significantly reduce the errors arising during automatic calculations of the local geomagnetic activity index (local K-index) in comparison with adaptive smoothing (KAsm is Adaptative Smoothing method) recommended by INTERMAGNET. It has been found that prior to magnetic storms, we can observe a weak rise of geomagnetic activity in different frequency bands connected with the development of an approaching storm.
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Oksana Mandrikova graduate of Taras Shevchenko Kiev State University, Department of Mechanics and Mathematics (Kiev, Ukraine, 1995). In 2003 she defended her PhD thesis and in 2009 doctoral thesis (at St. Petersburg Electrotechnical University, St. Petersburg, Russia) in the field of geophysical signal processing and earthquake prediction. Later she was granted the rank of full professor at Kamchatka Electrotechnical University (2009). At present, she is working in the Institute of Cosmophysical Researches and Radio Wave Propagation (Far Eastern Branch of the Russian Academy of Sciences, Petropavlovsk-Kamchatsky, Russia) as a leading researcher. Mandrikova also works as a lecturer in Kamchatka Technical University and teaches “Systems simulation,” “Databases,” “Intellectual information systems,” and “Mathematical models and methods in scientific research.” Her scientific work is connected with earthquake and magnetic storm prediction, discovering abnormal values in geophysical signals by neural networks and wavelet analysis, ionosphere measurements, ionospheric data acquisition, and applications of MATLAB in studies and research. She has significantly developed several applications of geophysical signal processing and Data Mining techniques (segmentation, classification, sequential analysis). She was awarded special grants by the Russian Foundation for Basic Research (RFBR). So far she has taken part in a great many domestic and international conferences and workshops devoted to Data Mining, digital signal processing, and acoustics, PRIA-2004 (St. Petersburg, Russia), PRIA-2007 (Yoshkar-Ola, Russia, 2007), PRIA-2010 (St. Petersburg, Russia), DSPA-2007-2010 (Moscow, Russia, 2007–2010), SCM-2005-2016, Solar- Terrestrial Relations and Physics of Earthquakes Precursors (Petropavlovsk-Kamchatsky, Russia, 2004, 2007, 2010), Intelligent Information Processing (Cyprus, 2010), Design of scientific and engineering implementations in MATLAB (Moscow, 2002), etc. She has submitted several papers to international and domestic journals (journals “Pattern Recognition and Image Analysis,” “Digital Signal Processing,” “Information Technologies,” “Geophysical research,” “Prediction of atmospheric phenomena,” Proceedings of the Russian Academy of Sciences). Mandrikova is the author and co-author of several books on geophysics, basics of signal processing, wavelets, and parametric models of time-series analysis. She has 3 inventors certificate for software development in Russia and 3 monographs. The outlook for the future is mainly connected with further investigation and development of geophysical signal processing methods with regard to acoustics and telemetric signal processing.
Igor’ Solovjev graduate of Kamchatka Technical University, Department of Applied mathematics (Petropavlovsk- Kamchatsky, Russia, 2005). In 2013 he defended his PhD thesis (at Saint Petersburg Electrotechnical University “LETI,” St. Petersburg, Russia) in the field of geophysical signal processing, earthquake and magnetic storm prediction. At present, he is working in the Institute of Cosmophysical Researches and Radio Wave Propagation (Far Eastern Branch of the Russian Academy of Sciences, Petropavlovsk-Kamchatsky, Russia) as a researcher and programmer. Solovjev also works as a lecturer in Kamchatka Technical University and teaches “Computer science,” “Digital signal processing,” and “Modern geophysics.” His scientific work is connected with earthquake and magnetic storm prediction, discovering abnormal values in geophysical signals by neural networks and wavelet analysis, ionosphere measurements, ionospheric data acquisition, and applications of MATLAB in studies and research. He has significantly developed several applications of geophysical signal processing and Data Mining techniques (segmentation, classification, sequential analysis). He was awarded special grants by the Russian Foundation for Basic Research (RFBR). So far he has taken part in a great many domestic and international conferences and workshops devoted to Data Mining, digital signal processing, and acoustics, PRIA-2004 (St. Petersburg, Russia), PRIA-2007 (Yoshkar-Ola, Russia, 2007), PRIA-2010 (St. Petersburg, Russia), DSPA-2007-2010 (Moscow, Russia, 2007–2010), Solar-Terrestrial Relations and Physics of Earthquakes Precursors (Petropavlovsk-Kamchatsky, Russia, 2010), Intelligent Information Processing (Cyprus, 2010), etc. He has submitted several papers to international and domestic journals (journals “Pattern Recognition and Image Analysis,” “Digital Signal Processing,” “Geophysical Research,” “Prediction of Atmospheric Phenomena”). The outlook for the future is mainly connected with further investigation and development of geophysical signal processing methods with regard to acoustics and telemetric signal processing.
Sergei Khomutov is the head of the Geophysical Observatory “Paratunka” of IKIR FEB RAS (Kamchatka) since 2013. He graduated from the Department of Astronomy fo the Faculty of Physics of the Kharkov University in 1981. From 1981 to 1989 he worked in the Department of Earth’s rotation of the Institute of metrology in Irkutsk and from 1989 to 2013 he is Scientist Leader of Geophysical Observatory “Klyuchi” of Institute of Geophysics and Geophysical survey of Siberian Branch of RAS, Novosibirsk. Main professional interests: the magnetic measurements, the organization of work observatory, the development of methodics and software for processing of magnetic data.
Dmitrii Baishev, PhD, head of laboratory, IKFIA SB RAS (laboratory of magnetospheric and ionospheric researches); contact: Shafer Institute of Cosmophysical Research and Aeronomy Siberian Brach, Russian Academy of Sciences, ul. Lenin 31, Yakutsk, 677980 Russia phone: +7(4112) 390- 441, fax:+7(4112) 390-450, e-mail: baishev@ikfia.sbras.ru. Dr. Baishev works at IKFIA about 29 years. In total 81 papers have been published including 37 papers in peer-reviewed Russian and foreign journals and 44 in Conference Proceedings. In 2000 he defended his PhD thesis in study of relationships between non-stationary auroral structures and geomagnetic pulsations at IKFIA. Primary Research Topics: Extensive experience in the study of geomagnetic pulsations and auroral phenomena. The analysis of magnetic and optical observations from MAGDAS/ CPMN stations in the far-eastern region of Russia. Major Research Accomplishments: First identification of relations of N-S aurora (auroral streamers) with “evening” Ps6 pulsations during substorms and convection disturbances, and large-scale undulations on the equatorward diffuse auroral boundary with Pc5 pulsations during a magnetic storm. New results based on a statistical analysis of observations of large-scale undulations during the 23rd solar cycle by optical data from two stations at Tixie (71.6°N, 128.9°E) and Zhigansk (66.8°N, 123.4°E) were obtained. The occurrence frequency of eveningside (17–23 LT) undulations during the solar activity growth (1999) and decline (2003–2005) phases tends to increase. Large-scale undulations were revealed to be generated both on the equatorial boundary of the diffuse auroral zone and inside the diffuse zone.
Vladimir Geppener, PhD, Dr. of Tech. Sci., Professor, graduate of St. Petersburg Electrotechnical University “LETI,” Department of Electric and Electronic Engineering (St. Petersburg, Russia, 1962) and Saint Petersburg State University, Department of Mathematics and Mechanics (St. Petersburg, Russia, 1979). In 2000 he defended his doctoral thesis in the field of artificial intelligence and signal processing and later was conferred the rank of full professor at St. Petersburg State Electrotechnical University (2003). At present, he is working in the Research and Engineering Center of St. Petersburg Electrotechnical University (St. Petersburg, Russian Federation) as a leading researcher. Geppener also works as a full professor in St. Petersburg Electrotechnical University and teaches Digital signal processing, Artificial Intelligence, and Speech recognition. In 1999–2005 he gave lectures on Digital signal processing at Petropavlovsk-Kamchatsky State University (Petropavlovsk-Kamchatsky, Russia) and taught Computational mathematics. Geppener’s scientific work is connected with acoustics, digital signal processing, intellectual analysis of data, speech processing, pattern recognition, and image analysis. He has developed several applications of acoustics and Data Mining. He was twice awarded special grants by the Russian Foundation for Basic Research (RFBR). Geppener is the author and co-author of several books on geophysics, fundamentals of signal processing, and wavelets. The outlook for the future is mainly connected with further investigation and development of Data Mining techniques with regard to acoustics and telemetric signal processing. He is the author of more than 200 papers on digital signal processing.
Dmitrii Klionskiy, PhD, associate Professor, Deputy Dean for international affairs (faculty of Computer Technologies and Informatics), leading researcher at Saint Petersburg Electrotechnical University “LETI” (St. Petersburg, Russian Federation). In 2013 he defended his PhD thesis in applied mathematics and digital signal processing at Saint Petersburg Electrotechnical University “LETI.” The current research and academic work are concerned with adaptive signal processing (empirical mode decomposition (EMD), wavelet analysis, singular spectral analysis) and intellectual analysis of signals on the basis of Data Mining technique (segmentation, clustering, classification, mining association rules, sequential analysis). Klionskiy regularly takes part in different joint projects connected with telemetric signal processing, geophysical data processing and analysis and intellectual analysis of geophysical and telemetric data. The most substantial results are in the fields of adaptive signal processing and spectral analysis of signals including signal preprocessing (denoising, detrending, Hurst parameter estimation via EMD, time-frequency analysis, segmentation and clustering of signals). Klionskiy was awarded special prizes by the Ministry of Education and Science of the Russian Federation for academic achievements. He is the author of more than 80 papers on digital signal processing.
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Mandrikova, O.V., Solovjev, I.S., Khomutov, S.Y. et al. Estimation of geomagnetic field disturbance using the wavelet transform. Pattern Recognit. Image Anal. 26, 773–781 (2016). https://doi.org/10.1134/S1054661816040076
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DOI: https://doi.org/10.1134/S1054661816040076