Wavelet Denoising Correlation for Satellite Signals Based on Improved Wavelet Threshold

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.