Affiliations: [a] College of Physics and Information Engineering, Cangzhou Normal University, Cangzhou, China
| [b] Department System Design Engineering, University of Waterloo, Waterloo, ON, Canada
Correspondence:
[*]
Corresponding author. Yuxiu Guo, College of Physics and Information Engineering, Cangzhou Normal University, Cangzhou, 061001, China. E-mail: 58686887@qq.com.
Abstract: At present, weak signal detection algorithm detects parallel weak signals under Gauss noise interference, which has the problems of low denoising performance, inaccurate detection results and low detection efficiency. To this end, a parallel weak signal detection algorithm based on Gauss noise interference is proposed. Wavelet transform is applied to detect weak signals with Gauss noise by wavelet threshold denoising method, and the weak signal is denoised based on the set threshold function and threshold. The EMD decomposition method is used to decompose the weak signal after denoising, and the weak signal is filtered through the imitation Cauchy convergence filter stopping criterion to extract the characteristics of weak signal. The weak signal detection under the interference of Gauss noise is completed based on the Doffing oscillator and the characteristic of the weak signal extracted. The experimental results show that the proposed method has high signal-to-noise ratio, accurate detection of weak signal, and the time of detection is below 8 s. The results show that the proposed method has high denoising performance, high detection accuracy and high detection efficiency.
Keywords: Gauss noise, noise interference, weak signal, signal
