Research on Noise Reduction Algorithm for Unmanned Surface Vehicle Radar Based on Variable Threshold Wavelet Filtering

A wavelet filtering algorithm with a variable threshold is proposed to address the challenge of accurately identifying the environment in noisy radar signals. This algorithm considers radar signal length, noise intensity, and high-frequency wavelet coefficients after decomposition, introducing a dynamic threshold adjustment to improve noise reduction. Simulation experiments on a digital twin platform demonstrate that the algorithm effectively reduces radar signal noise, especially clutter like rain and snow, enhancing radar detection performance, target recognition accuracy, and the environmental perception of unmanned surface vessel.

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Publication Details

Published
2024-09-13
DOI
https://doi.org/10.1109/icacte62428.2024.10871715
Primary Topic
Advanced SAR Imaging Techniques
Type
article
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article

Research on Noise Reduction Algorithm for Unmanned Surface Vehicle Radar Based on Variable Threshold Wavelet Filtering

KunPeng Liu, Zeyu Chen, Lifei Song, Rong Guo et al.
Advanced SAR Imaging Techniques
article

Research on Noise Reduction Algorithm for Unmanned Surface Vehicle Radar Based on Variable Threshold Wavelet Filtering

KunPeng Liu, Zeyu Chen, Lifei Song, Rong Guo, Wei Peng
article en

Abstract

A wavelet filtering algorithm with a variable threshold is proposed to address the challenge of accurately identifying the environment in noisy radar signals. This algorithm considers radar signal length, noise intensity, and high-frequency wavelet coefficients after decomposition, introducing a dynamic threshold adjustment to improve noise reduction. Simulation experiments on a digital twin platform demonstrate that the algorithm effectively reduces radar signal noise, especially clutter like rain and snow, enhancing radar detection performance, target recognition accuracy, and the environmental perception of unmanned surface vessel.

Wuhan University of Technology (CN), Shanghai Jian Qiao University (CN), CSSC Offshore & Marine Engineering Company (China) (CN)
Affordable and clean energy
Openalex Percentile: Top 55%
Advanced SAR Imaging Techniques
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