摘要
针对蒸发波导数据压缩感知过程中易受噪声干扰且采用传统重构方法抗噪性能较差的问题,提出了一种基于相似度阈值的自适应正则化匹配追踪去噪方法。该方法可以在信号稀疏度难以获知的情况下,利用自适应思想逐步扩充候选集,同时通过设置相似度阈值来对部分候选原子进行剔除,并结合正则化过程对支撑集原子进行二次筛选,从而较好地约束了噪声分量的重构,提高了信号的重构精度。理论分析和实验表明,所提方法的重构性能优于现有同类重构方法,去噪性能优于小波去噪方法,相同条件下,可获得更高的重构信噪比,有效实现了蒸发波导数据的去噪重构。
To solve the problem that the evaporation duct data is easily disturbed by noise in compressed sensing and traditional reconstruction methods have poor performance in denoising,an adaptive regularized matching pursuit denoising method is proposed and it based on the similarity threshold.This method can gradually expand the candidate set by using the adaptive idea when the signal sparsity is difficult to be known.At the same time,some atoms are removed by setting the similarity threshold,and the support set atoms are screened by the regularization process,so that the reconstruction of noise components is better constrained and the reconstruction accuracy of signal is improved.Theoretical analysis and experiments show that the proposed method has better reconstruction performance than the existing similar reconstruction methods and has better denoising performance than the wavelet denoising method.The proposed method can obtain higher reconstruction SNR under the same conditions,and can effectively realize the denoising and reconstruction of the evaporation duct data.
作者
芮国胜
崔田田
田文飚
Rui Guosheng;Cui Tiantian;Tian Wenbiao(Key Laboratory of Signal and Information Processing in Shandong Province,Naval Aeronautical University,Yantai 264001,China)
出处
《电子测量技术》
北大核心
2023年第4期6-11,共6页
Electronic Measurement Technology
基金
国家自然科学基金(41606117,41476089,61671016)项目资助
关键词
压缩感知
蒸发波导
相似度阈值
自适应
正则化
去噪重构
compressed sensing
evaporation duct
similarity threshold
adaptive
regularization
denoising and reconstruction
