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Sensors 2017, 17(2), 371; doi:10.3390/s17020371

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

1
College of Communications Engineering, PLA University of Science and Technology, Nanjing 210007, China
2
Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China
*
Author to whom correspondence should be addressed.
Academic Editor: Vittorio M. N. Passaro
Received: 4 December 2016 / Revised: 8 February 2017 / Accepted: 10 February 2017 / Published: 14 February 2017
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [1261 KB, uploaded 14 February 2017]   |  

Abstract

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). View Full-Text
Keywords: amplitude probability density; atmospheric noise; superconducting quantum interference device; SαS distribution amplitude probability density; atmospheric noise; superconducting quantum interference device; SαS distribution
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Hao, H.; Wang, H.; Chen, L.; Wu, J.; Qiu, L.; Rong, L. Initial Results from SQUID Sensor: Analysis and Modeling for the ELF/VLF Atmospheric Noise. Sensors 2017, 17, 371.

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