西安电子科技大学学报（自然科学版）2026，Vol.53Issue(3)：32-43,12.DOI:10.19665/j.issn1001-2400.20260117
熵权特征融合的声雷达近地面风速反演算法
Entropy-weighted feature fusion SODAR wind retrieval algorithm
摘要
Abstract
Sonic Detection and Ranging serves as a critical technology for near-surface wind field monitoring,holding significant value in wind energy development and meteorological exploration.However,its practical application faces severe challenges from Doppler spectral peak drift and complex electromagnetic noise interfer-ence,which constrain wind speed retrieval accuracy.To address these issues,this study proposes an entropy-weighted feature fusion algorithm.To overcome spectral peak drift,a Doppler window dynamic migration model based on the power-law distribution of turbulent dynamics is constructed.Targeting the critical bottleneck of insufficient robustness and accuracy in spectral peak discrimination under complex noise environ-ments,this study introduces an entropy-weighted feature fusion method grounded in information entropy theory.This method constructs a feature space incorporating key discriminative indicators such as signal-to-noise ratio and Doppler frequency shift difference,while dynamically assigning weights to each feature using information entropy theory,thereby effectively mitigating the subjectivity and environmental adaptability limitations inherent in traditional feature weight assignment methods.Furthermore,to ensure the physical rationality of symmetric beam results,a symmetry constraint is introduced for optimization.Experimental validation demonstrates that the entropy-weighted feature fusion algorithm significantly enhances the spectral peak identification capability and wind speed inversion accuracy of sonic wind radar in complex interference scenarios,providing an effective solution for high-reliability near-surface wind field monitoring.关键词
声波测风雷达/熵权特征融合/动态多普勒窗口/对称性约束优化/近地面风速反演Key words
sonic wind radar/entropy-weighted feature fusion/dynamic doppler window/symmetry-constrained optimization/near-surface wind speed retrieval分类
信息技术与安全科学引用本文复制引用
卢昌学,李翠芸,冯天乐..熵权特征融合的声雷达近地面风速反演算法[J].西安电子科技大学学报（自然科学版）,2026,53(3):32-43,12.基金项目
国家自然科学基金(U21A20455) （U21A20455）
