Browsing by Subject "Geomagnetism"
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Item Open Access Association of ionospheric storms and substorms of global electron content with proxy AE index(Pergamon Press, 2015) Yenen, S. D.; Gulyaeva, T. L.; Arikan, F.; Arıkan, OrhanStorm time modeling of Global Electron Content (GEC) calculated from GIM-TEC for 1999-2013 is associated with new proxy of Auroral Electrojet variability expressed as a smoothed and normalized Auroral Electrojet index (AEsn). The variability in GEC is captured by the computation of DGEC which is obtained by taking the hourly ratio of instant GEC to median of GEC values at the same hour of 7 preceding days. The storm onset is determined by a joint analysis of variations in IMF-B magnitude, its derivative (dB/dt) and direction of IMF-Bz together with sudden increase in AE exceeding 900 nT. The start of the pre-storm period is chosen to be 7 h prior to the storm onset time and the storm recovery period ends 41 h after the storm onset. The hourly AEsn is related to DGEC during the storm period through a polynomial whose coefficients are estimated in the linear least squares sense. Estimated coefficients are examined and grouped with respect to different kinds of auroral storms. Examples of modeling methodology are provided using four different kinds of intense storms and substorms, namely, Positive Arctic, Positive Antarctic, Negative Arctic and Negative Antarctic that occurred between 1999 and 2013. The estimated coefficients for storm periods are compared with those of non-storm periods. It is observed that the positive correlation between the increase of AE and GEC can be a promising precursor of space weather variability.Item Open Access Autonomous navigation of robotic units in mobile sensor network(2012) Nazlibilek, S.This work is motivated by the problem of detecting buried anti-tank and anti-personnel mines in roads or some border regions. The problem is tried to be solved by use of small mobile robotic sensors and their some abilities such as measurement of local fields, navigation around a region, communications with each other, and constituting team within a mission area. The aim of this work is to investigate the navigation problem for the team behavior of mobile sensors within a potential field available in a small-scale environment such as an indoor area or an outdoor region. The mobile sensor network here is a collection of robotic units with sensing capability of earth magnetic field anomalies. A new kind of positioning system is needed for their collective behavior. In this work, a new method of navigation is proposed as a local positioning system. It utilizes ultrasound and radio frequency information to determine the coordinates of the points inside the operational area. The method proposed here is compared with the ultra wideband ranging ping-pong method that is used widely in recent applications. A time division multiple access method is used for the communications among the mobile sensors. The results on the positioning methods together with several simulations and experimental works are given. It is shown that the positioning method utilizing ultrasound-radio frequency method can give fairly good results. © 2012 Elsevier Ltd. All rights reserved.Item Open Access Classification of regional ionospheric disturbance based on machine learning techniques(European Space Agency, 2016) Terzi, Merve Begüm; Arıkan, Orhan; Karatay, S.; Arıkan, F.; Gulyaeva, T.In this study, Total Electron Content (TEC) estimated from GPS receivers is used to model the regional and local variability that differs from global activity along with solar and geomagnetic indices. For the automated classification of regional disturbances, a classification technique based on a robust machine learning technique that have found wide spread use, Support Vector Machine (SVM) is proposed. Performance of developed classification technique is demonstrated for midlatitude ionosphere over Anatolia using TEC estimates generated from GPS data provided by Turkish National Permanent GPS Network (TNPGN-Active) for solar maximum year of 2011. As a result of implementing developed classification technique to Global Ionospheric Map (GIM) TEC data, which is provided by the NASA Jet Propulsion Laboratory (JPL), it is shown that SVM can be a suitable learning method to detect anomalies in TEC variations.Item Open Access Identification of materials with magnetic characteristics by neural networks(2012) Nazlibilek, S.; Ege, Y.; Kalender O.; Sensoy, M.G.; Karacor, D.; Sazli, M.H.In industry, there is a need for remote sensing and autonomous method for the identification of the ferromagnetic materials used. The system is desired to have the characteristics of improved accuracy and low power consumption. It must also autonomous and fast enough for the decision. In this work, the details of inaccurate and low power remote sensing mechanism and autonomous identification system are given. The remote sensing mechanism utilizes KMZ51 anisotropic magneto-resistive sensor with high sensitivity and low power consumption. The images and most appropriate mathematical curves and formulas for the magnetic anomalies created by the magnetic materials are obtained by 2-D motion of the sensor over the material. The contribution of the paper is the use of the images obtained by the measurement of the perpendicular component of the Earth magnetic field that is a new method for the purpose of identification of an unknown magnetic material. The identification system is based on two kinds of neural network structures. The MultiLayer Perceptron (MLP) and the Radial Basis Function (RBF) network types are used for training of the neural networks. In this work, 23 different materials such as SAE/AISI 1030, 1035, 1040, 1060, 4140 and 8260 are identified. Besides the ferromagnetic materials, three objects are also successfully identified. Two of them are anti-personal and anti-tank mines and one is an empty can box. It is shown that the identification system can also be used as a buried mine identification system. The neural networks are trained with images which are originally obtained by the remote sensing system and the system is operated by images with added Gaussian white noises. © 2012 Elsevier Ltd. All rights reserved.Item Open Access Investigation of hourly and daily patterns for lithosphere-ionosphere coupling before strong earthquakes(IEEE, 2009-06) Karatay, S.; Arıkan F.; Arıkan, OrhanThe ionosphere can be characterized with its electron density distribution which is a complex function of spatial and temporal variations, geomagnetic, solar and seismic activity. An important measurable quantity about the electron density is the Total Electron Content (TEC) which is proportional to the total number of electrons on a line crossing the atmosphere. TEC measurements enable monitoring variations in the space weather. Global Positioning System (GPS) and the network of world-wide receivers provide a cost-effective solution in estimating TEC over a significant proportion of global land mass. In this study, five earthquakes between 2003-2008 that occurred in Japan with different seismic properties, and the China earthquake in May 2008 are investigated. The TEC data set is investigated by using the Kullback-Leibler Divergence (KLI), Kullback-Leibler Distance (KLD) and L2-Norm (L2N) which are used for the first time in the literature in this context and Cross Correlation Function (CCF) which is used in the literature before for quiet day period (QDP), disturbed day period (DDP), periods of 15 days before a strong earthquake (BE) and after the earthquake (AE). In summary, it is observed that the CCF, KLD and L2N between the neighbouring GPS stations cannot be used as a definitive earthquake precursor due to the complicated nature of earthquakes and various uncontrolled parameters that effect the behavior of TEC such as distance to the earthquake epicenter, distance between the stations, depth of the earthquake, strength of the earthquake and tectonic structure of the earthquake. KLD, KLI and L2N are used for the first time in literature for the investigation of earthquake precursor for the first time in literature and the extensive study results indicate that for more reliable estimates further space-time TEC analysis is necessary over a denser GPS network in the earthquake zones. ©2009 IEEE.Item Open Access Investigation of total electron content variability due to seismic and geomagnetic disturbances in the ionosphere(Wiley-Blackwell Publishing, 2010-10-20) Karatay S.; Arikan, F.; Arıkan, OrhanVariations in solar, geomagnetic, and seismic activity can cause deviations in the ionospheric plasma that can be detected as disturbances in both natural and man-made signals. Total electron content (TEC) is an efficient means for investigating the structure of the ionosphere by making use of GPS receivers. In this study, TEC data obtained for eight GPS stations are compared with each other using the cross-correlation coefficient (CC), symmetric Kullback-Leibler distance (KLD), and L2 norm (L2N) for quiet days of the ionosphere, during severe geomagnetic storms and strong earthquakes. It is observed that only KLD and L2N can differentiate the seismic activity from the geomagnetic disturbance and quiet ionosphere if the stations are in a radius of 340 km. When TEC for each station is compared with an average quiet day TEC for all periods using CC, KLD, and L2N, it is observed that, again, only KLD and L2N can distinguish the approaching seismicity for stations that are within 150 km radius to the epicenter. When the TEC of consecutive days for each station and for all periods are compared, it is observed that CC, KLD, and L2N methods are all successful in distinguishing the geomagnetic disturbances. Using sliding-window statistical analysis, moving averages of daily TEC with estimated variance bounds are also obtained for all stations and for all days of interest. When these bounds are compared with each other for all periods, it is observed that CC, KLD, and L2N are successful tools for detecting ionospheric disturbances.Item Open Access A new wireless asynchronous data communications module for industrial applications(2013) Ege, Y.; Şensoy, M.G.; Kalender O.; Nazlibilek, S.; Çitak H.All the sensors such as temperature, humidity, and pressure used in industry provide analog outputs as inputs for their control units. Wireless transmission of the data has advantages on wired transmission such as USB port, parallel port and serial port and therefore has great importance for industrial applications. In this work, a new wireless asynchronous data communications module has been developed to send the earth magnetic field data around a ferromagnetic material detected by a KMZ51 AMR sensor. The transmitter module transmits the analog data obtained from a source to a computer environment where they are stored and then presented in a graphical form. In this design, an amplitude shift keying (ASK) transceiver working at the frequency of 433.92 MHz which is a frequency inside the so called Industrial Scientific Medical band (ISM band) used for wireless communications. The analog data first fed into a 10-bit ADC controlled by a PIC microcontroller and then the digital data is sent to the transmitter. A preamble bit string is added in front of the data bits and another bit string for achieving synchronization and determination the start of the data is used. The data arriving at the receiver is taken by the microcontroller and sent to a LCD display as well as the serial port of a computer where it is written in a text file. A Visual Basic based graphics interface is designed to receive, store and present the data in the form of graphical shapes. In the paper, all the work has been explained in detail. © 2013 Published by Elsevier Ltd. All rights reserved.Item Open Access Numerical analysis for remote identification of materials with magnetic characteristics(2011) Ege, Y.; Şensoy, M.G.; Kalender O.; Nazlibilek, S.There is a variety of methods used for remote sensing of objects such as acoustic, ground penetration radar detection, electromagnetic induction spectroscopy, infrared imaging, thermal neutron activation, core four-pole resonance, neutron backscattering, X-ray backscattering, and magnetic anomaly. The method that has to be used can be determined by the type of material, geographical location (underground or water), etc. Recent studies have been concentrated on the improvement of the criteria such as sensing distances, accuracy, and power consumption. In this paper, anomalies created by materials with magnetic characteristics at the perpendicular component of the Earth magnetic field have been detected by using a KMZ51 anisotropic magnetoresistive sensor with high sensitivity and low power consumption, and also, the effects of physical properties of materials on magnetic anomaly have been investigated. By analyzing the graphics obtained by 2-D motion of the sensor over the material, the most appropriate mathematical curves and formulas have been determined. Based on the physical properties of the magnetic material, the variations of the variables constituting the formulas of the curves have been analyzed. The contribution of this paper is the use of the results of these analyses for the purpose of identification of an unknown magnetic material. This is a new approach for the detection and determination of materials with magnetic characteristics by sensing the variation at the perpendicular component of the Earth magnetic field. The identification process has been explained in detail in this paper. © 2011 IEEE.