scholarly journals Low-frequency (100 kc./s.) Radio Noise from the Aurora

Nature ◽  
1959 ◽  
Vol 184 (4689) ◽  
pp. 803-803 ◽  
Author(s):  
R. L. DOWDEN
Keyword(s):  
Low Frequency ◽  
Radio Noise

Global Measurements of Low-Frequency Radio Noise

1992 ◽  
Author(s):  
A. C. Fraser-Smith ◽  
P. R. McGill ◽  
A. Bernardi ◽  
R. A. Helliwell ◽  
M. E. Ladd
Keyword(s):  
Low Frequency ◽  
Radio Noise

Low-frequency atmospheric radio noise in Florida

1952 ◽  
Vol 33 (5) ◽  
pp. 650 ◽  
Author(s):  
A. W. Sullivan ◽  
H. M. VanValkenburg ◽  
J. M. Barney
Keyword(s):  
Low Frequency ◽  
Radio Noise ◽  
Atmospheric Radio ◽  
Atmospheric Radio Noise

scholarly journals A Novel Linear Spectrum Frequency Feature Extraction Technique for Warship Radio Noise Based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise, Duffing Chaotic Oscillator, and Weighted-Permutation Entropy

Entropy ◽  
2019 ◽  
Vol 21 (5) ◽  
pp. 507 ◽  
Author(s):  
Yuxing Li ◽  
Long Wang ◽  
Xueping Li ◽  
Xiaohui Yang
Keyword(s):  
Feature Extraction ◽  
Empirical Mode Decomposition ◽  
Low Frequency ◽  
Extraction Technique ◽  
Permutation Entropy ◽  
Radio Noise ◽  
Mode Decomposition ◽  
Linear Spectrum ◽  
Frequency Feature ◽  
Feature Extraction Technique

Warships play an important role in the modern sea battlefield. Research on the line spectrum features of warship radio noise signals is helpful to realize the classification and recognition of different types of warships, and provides critical information for sea battlefield. In this paper, we proposed a novel linear spectrum frequency feature extraction technique for warship radio noise based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), duffing chaotic oscillator (DCO), and weighted-permutation entropy (W-PE). The proposed linear spectrum frequency feature extraction technique, named CEEMDAN-DCO-W-PE has the following advantages in comparison with other linear spectrum frequency feature extraction techniques; (i) as an adaptive data-driven algorithm, CEEMDAN has more accurate and more reliable decomposition performance than empirical mode decomposition (EMD) and ensemble EMD (EEMD), and there is no need for presetting parameters, such as decomposition level and basis function; (ii) DCO can detect the linear spectrum of narrow band periodical warship signals by way of utilizing its properties of sensitivity for weak periodical signals and the immunity for noise; and (iii) W-PE is used in underwater acoustic signal feature extraction for the first time, and compared with traditional permutation entropy (PE), W-PE increases amplitude information to some extent. Firstly, warship radio noise signals are decomposed into some intrinsic mode functions (IMFs) from high frequency to low frequency by CEEMDAN. Then, DCO is used to detect linear spectrum of low-frequency IMFs. Finally, we can determine the linear spectrum frequency of low-frequency IMFs using W-PE. The experimental results show that the proposed technique can accurately extract the line spectrum frequency of the simulation signals, and has a higher classification and recognition rate than the traditional techniques for real warship radio noise signals.

Sprites in low-frequency radio noise

2013 ◽  
Vol 40 (10) ◽  
pp. 2395-2399 ◽  
Author(s):  
Martin Füllekrug ◽  
Andrew Mezentsev ◽  
Serge Soula ◽  
Oscar van der Velde ◽  
Thomas Farges
Keyword(s):  
Low Frequency ◽  
Radio Noise
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