Electronics Optics & Control, Volume. 27, Issue 4, 15(2020)
A Pulsar Signal Denoising Algorithm Based on Wavelet Basis Function Selection and Improved Threshold Function
When the pulsar signal is denoised by using wavelet transform, the selection of wavelet basis and decomposition layer and the construction of the threshold function have a great effect on the accuracy of pulsar navigation.In this paper, the subordination relationship between the wavelet basis and the wavelet decomposition coefficient is studied firstly, and then the reasonable wavelet basis and decomposition layer are screened according to the cross correlation between the wavelet decomposition coefficient and the original signal.During the study of wavelet decomposition coefficients, it is found that the wavelet coefficients formed by noise decrease with the increase of the decomposition layer.Based on this feature, a threshold function based on the decomposition layer is constructed.The experimental results show that, compared with the traditional wavelet-domain denoising method, the proposed method can not only accurately select the optimal wavelet basis and the optimal decomposition layer, but also effectively improve the Signal-to-Noise Ratio (SNR), Peak Signal-to-Noise Ratio (PSNR) and decrease the Error of Peak Position (EPP) of the pulsar signal after denoising with our threshold function.The study provides a new idea for the denoising of pulsar signals.
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GAO Yingdong, WANG Hongli, YOU Sihai, FENG Lei, HE Yiyang, LIU Ke. A Pulsar Signal Denoising Algorithm Based on Wavelet Basis Function Selection and Improved Threshold Function[J]. Electronics Optics & Control, 2020, 27(4): 15
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Received: Mar. 20, 2019
Accepted: --
Published Online: Jun. 15, 2020
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