DocumentCode :
2930328
Title :
Data processing for intensity of HF signal based on the GM (1, 1) model
Author :
Xia Bin ; Chen Bolin
Author_Institution :
Luoyang Electron. Equip. Testing Center, Luoyang, China
fYear :
2013
fDate :
15-17 Nov. 2013
Firstpage :
154
Lastpage :
157
Abstract :
In order to solver the high frequency (HF) skywave signal field intensity data influenced by ionosphere fast fading, the gross error discriminant formula based on GM(1,1) is used to eliminate the break data influenced by the ionosphere fast fading in this paper. By introducing modeling accuracy and distinguish threshold, the gross error discriminant formula can rationally eliminate gross error data from signal field intensity data. For illustration, a typical HF skywave signal field intensity data treatment example is utilized to show the feasibility of the gross error discriminant formula in reducing the influence of ionosphere fast fading and improving the processing accuracy. Empirical results show that the Rayleigh distribution characteristic changes between, before and after treatment directly illustrated by the effectiveness of the gross error discriminant formula. The gross error discriminant formula based on the GM(1,1) Model can effectively eliminate the break data influenced by the ionosphere fast fading and solve the problem of HF skywave signal field intensity data processing and analysis.
Keywords :
grey systems; intensity measurement; signal processing; GM (1,1) model; HF signal intensity; Rayleigh distribution characteristic; data analysis; data processing; error data elimination; gross error discriminant formula; high frequency skywave signal; ionosphere fast fading; signal field intensity data; Accuracy; Data models; Data processing; Ionosphere; Rayleigh channels; 1) Model; GM(1; HF skywave field intensity measurement; Rayleigh distribution; fuzzy estimate method; ionosphere fast fading;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Grey Systems and Intelligent Services, 2013 IEEE International Conference on
Conference_Location :
Macao
ISSN :
2166-9430
Print_ISBN :
978-1-4673-5247-5
Type :
conf
DOI :
10.1109/GSIS.2013.6714767
Filename :
6714767
Link To Document :
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