Initial Results from SQUID Sensor: Analysis and Modeling for the ELF/VLF Atmospheric Noise

In this paper, the amplitude probability density (APD) of the wideband extremely low frequency (ELF) and very low frequency (VLF) atmospheric noise is studied. The electromagnetic signals from the atmosphere, referred to herein as atmospheric noise, was recorded by a mobile low-temperature superconducting quantum interference device (SQUID) receiver under magnetically unshielded conditions. In order to eliminate the adverse effect brought by the geomagnetic activities and powerline, the measured field data was preprocessed to suppress the baseline wandering and harmonics by symmetric wavelet transform and least square methods firstly. Then statistical analysis was performed for the atmospheric noise on different time and frequency scales. Finally, the wideband ELF/VLF atmospheric noise was analyzed and modeled separately. Experimental results show that, Gaussian model is appropriate to depict preprocessed ELF atmospheric noise by a hole puncher operator. While for VLF atmospheric noise, symmetric α-stable (SαS) distribution is more accurate to fit the heavy-tail of the envelope probability density function (pdf).

[1]  Michel Chouteau,et al.  Sferics noise reduction in time-domain electromagnetic systems: application to MegaTEMII signal enhancement , 2010 .

[2]  Umran S. Inan,et al.  Sensitive Broadband ELF/VLF Radio Reception With the AWESOME Instrument , 2010, IEEE Transactions on Geoscience and Remote Sensing.

[3]  Masashi Hayakawa,et al.  Global Lightning Activity on the Basis of Inversions of Natural ELF Electromagnetic Data Observed at Multiple Stations around the World , 2011 .

[4]  H. Lilliefors.  On the Kolmogorov-Smirnov Test for Normality with Mean and Variance Unknown , 1967 .

[5]  Jürgen F. Brune,et al.  Coal Mine Communications , 1900 .

[7]  Yan Han,et al.  A Missile-Borne Angular Velocity Sensor Based on Triaxial Electromagnetic Induction Coils , 2016, Sensors.

[8]  Yan Fan,et al.  A high-temperature superconducting receiver for low-frequency radio waves , 1997, IEEE Transactions on Applied Superconductivity.

[9]  Boualem Boashash,et al.  Estimating and interpreting the instantaneous frequency of a signal. I. Fundamentals , 1992, Proc. IEEE.

[10]  J. Ilow,et al.  Detection for binary transmission in a mixture of Gaussian noise and impulsive noise modeled as an alpha-stable process , 1994, IEEE Signal Processing Letters.

[11]  Wenwei Ying,et al.  A Multidimensional Class B Noise Model Based on Physical and Mathematical Analysis , 2012, IEEE Transactions on Communications.

[12]  D. A. Chrissan,et al.  A comparison of low‐frequency radio noise amplitude probability distribution models , 2000 .

[13]  Alex I. Braginski,et al.  Fundamentals and technology of SQUIDs and SQUID systems , 2004 .

[14]  Qing He,et al.  Design and Characterization of a Low-Cost Self-Oscillating Fluxgate Transducer for Precision Measurement of High-Current , 2016, IEEE Sensors Journal.

[15]  M. Rosenblatt.  A CENTRAL LIMIT THEOREM AND A STRONG MIXING CONDITION. , 1956, Proceedings of the National Academy of Sciences of the United States of America.

[16]  Li Su.  Ground-Airborne electromagnetic signals de-noising using a combined wavelet transform algorithm , 2013 .

[17]  U. Inan,et al.  Utilizing nonlinear ELF generation in modulated ionospheric heating experiments for communications applications , 2013 .

[18]  R. Gnanadesikan,et al.  Probability plotting methods for the analysis of data. , 1968, Biometrika.

[19]  Stuart A. Wolf,et al.  Superconducting Extremely Low Frequency (ELF) Magnetic Field Sensors for Submarine Communications , 1974, IEEE Trans. Commun..

[20]  Karina M. Fors,et al.  A log-likelihood ratio for improved receiver performance for VLF/LF communication in atmospheric noise , 2015, MILCOM 2015 - 2015 IEEE Military Communications Conference.

[21]  Yuan Wang,et al.  A wavelet-based baseline drift correction method for grounded electrical source airborne transient electromagnetic signals , 2013 .

[22]  Douglas A. Chrissan,et al.  Statistical analysis and modeling of low-frequency radio noise and improvement of low-frequency communications , 1998 .

[23]  T. S. Radhakrishnan,et al.  Baseline drift removal and denoising of MCG data using EEMD: role of noise amplitude and the thresholding effect. , 2014, Medical engineering & physics.

[24]  Yasushi Matsumoto,et al.  Evaluation of Impact on Digital Radio Systems by Measuring Amplitude Probability Distribution of Interfering Noise , 2015, IEICE Trans. Commun..

[25]  Feng Gao,et al.  An Ultra-Sensitive Magnetic Field Sensor Based on Extrinsic Fiber-Optic Fabry–Perot Interferometer and Terfenol-D , 2015, Journal of Lightwave Technology.

[26]  Josiane Zerubia,et al.  Modeling SAR images with a generalization of the Rayleigh distribution , 2004, IEEE Transactions on Image Processing.

[27]  Xi Zhang,et al.  BER Analysis for Digital Modulation Schemes under Symmetric Alpha-Stable Noise , 2014, 2014 IEEE Military Communications Conference.

[28]  J. Lenz,et al.  Magnetic sensors and their applications , 2006, IEEE Sensors Journal.

[29]  Robert J. Dinger,et al.  Development of a superconducting ELF receiving antenna , 1977 .

[30]  M. Jiang,et al.  Comparison of Noise Performance of the dc SQUID Bootstrap Circuit With That of the Standard Flux Modulation dc SQUID Readout Scheme , 2011, IEEE Transactions on Applied Superconductivity.

[31]  Umran S. Inan,et al.  Mitigation of 50–60 Hz power line interference in geophysical data , 2010 .

[32]  M. Cohen,et al.  ELF/VLF wave generation via ionospheric HF heating: Experimental comparison of amplitude modulation, beam painting, and geometric modulation , 2010 .

[33]  Carmine Granata,et al.  Multichannel System Based on a High Sensitivity Superconductive Sensor for Magnetoencephalography , 2014, Sensors.