International Journal of Electronic Engineering and Computer Science
Articles Information
International Journal of Electronic Engineering and Computer Science, Vol.3, No.1, Feb. 2018, Pub. Date: Jan. 16, 2018
Improvement of Correlation Identification Method Based on Non-Negative Periodic Autocorrelation Function
Pages: 1-5 Views: 1060 Downloads: 365
Authors
[01] Ren Rui, School of Information Engineering, China University of Geosciences (Beijing), Beijing, China.
[02] Cao Jian-peng, School of Information Engineering, China University of Geosciences (Beijing), Beijing, China.
[03] Zhang Qiao-dan, School of Information Engineering, China University of Geosciences (Beijing), Beijing, China.
[04] Li Mei, School of Information Engineering, China University of Geosciences (Beijing), Beijing, China.
Abstract
The correlation identification algorithm is a system identification method that can effectively suppress stochastic noise. However, since the auto spectrum of m-sequence has zero amplitude points, it will seriously affect the result of identification. Based on this problem, this paper proposes advanced method: we only take the non-negative part of the autocorrelation function and the cross correlation function, the spectrum of non-negative period autocorrelation function does not exist zero points. Compared with the auto spectrum of m sequence, the spectrum of non-negative period autocorrelation function has obvious advantages. In order to solve the conventional zero problem and improve the identification accuracy, this paper uses this method. Experiments showed that the improved correlation identification method had a higher identification accuracy and had achieved better identification results.
Keywords
Correlation Identification, Autocorrelation Function, Non-negative Period, M-sequences
References
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