Wavelet Denoising Correlation for Satellite Signals Based on Improved Wavelet Threshold

To enhance the denoising performance of satellite signals at a low signal-to-noise ratio (SNR), we propose an improved wavelet threshold denoising correlation (IWTDC) method that utilizes wavelet decomposition to analyze the received satellite signals. By dynamically selecting the threshold based on the transformation of the wavelet coefficients of each layer, we reconstruct the signal using processed coefficients for effective denoising. To validate the denoising effect of the proposed IWTDC method, we compare it with methods such as traditional cross-correlation, adaptive filtering correlation, and wavelet threshold correlation. Simulation results indicate that compared to other methods, SNR can be improved by up to 5 dB using the IWTDC method, leading to superior signal correlation and enhanced detection performance for the related peaks. Furthermore, experimental data collected during the study were consistent with the simulation results, confirming the performance of the IWTDC method. Thus, our proposed method can overcome the limitations of using traditional threshold functions through adaptive threshold selection, preserve signal details, and significantly improve the denoising performance.

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Publication Details

Journal
Electronics
Published
2025-12-23
DOI
https://doi.org/10.3390/electronics15010054
Primary Topic
PAPR reduction in OFDM
Type
article
Field-Weighted Citation Impact
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article

Wavelet Denoising Correlation for Satellite Signals Based on Improved Wavelet Threshold

Xian Zhao, Shanhe Wang, Y. Xiang, Ya Gao et al.
Electronics
PAPR reduction in OFDM
article

Wavelet Denoising Correlation for Satellite Signals Based on Improved Wavelet Threshold

Xian Zhao, Shanhe Wang, Y. Xiang, Ya Gao, Yu Hua, Changjiang Huang
article en

Abstract

To enhance the denoising performance of satellite signals at a low signal-to-noise ratio (SNR), we propose an improved wavelet threshold denoising correlation (IWTDC) method that utilizes wavelet decomposition to analyze the received satellite signals. By dynamically selecting the threshold based on the transformation of the wavelet coefficients of each layer, we reconstruct the signal using processed coefficients for effective denoising. To validate the denoising effect of the proposed IWTDC method, we compare it with methods such as traditional cross-correlation, adaptive filtering correlation, and wavelet threshold correlation. Simulation results indicate that compared to other methods, SNR can be improved by up to 5 dB using the IWTDC method, leading to superior signal correlation and enhanced detection performance for the related peaks. Furthermore, experimental data collected during the study were consistent with the simulation results, confirming the performance of the IWTDC method. Thus, our proposed method can overcome the limitations of using traditional threshold functions through adaptive threshold selection, preserve signal details, and significantly improve the denoising performance.

ElectronicsVol. 15(1)
National Time Service Center (CN), Institute of Navigation (US)
Affordable and clean energy
Openalex Percentile: Top 42%
PAPR reduction in OFDM
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