光学学报, 2019, 39 (12): 1204001, 网络出版: 2019-12-06   

基于双参数阈值函数和多层阈值的X射线脉冲星信号消噪 下载: 1187次

X-Ray Pulsar Signal Denoising Based on Two-Parameter Threshold Function and Multi-Layer Threshold
作者单位
火箭军工程大学导弹工程学院, 陕西 西安 710025
摘要
在利用小波变换解决脉冲星含噪信号去噪问题时,阈值的选择及阈值函数的构建决定去噪效果的优劣。首先结合小波变换的性质分析噪声小波分解系数的分布特性,并结合软、硬阈值函数的构造特点构建了一种非线性的双参数阈值函数;通过粒子群算法优化参数大小以使阈值函数可自适应地改变位置和弯曲程度,进而得到良好的阈值函数去噪模型;在分析噪声小波分解系数随分解层变化特点的基础上,对统一阈值选取策略进行改进,引入梯度衰减因子构造一种基于各分解层噪声均方差的阈值选取方法。实验结果表明,相比于传统小波域消噪方法,本文方法可以明显改善X射线脉冲星含噪信号的信噪比、峰值信噪比以及峰位误差,为X射线脉冲星信号去噪提供了新思路。
Abstract
When we use wavelet transform to solve the denoising problem in pulsar noise signal, the choice of threshold and construction of threshold function determine the denoising effect. Herein, we analyze the distribution characteristics of noise wavelet decomposition coefficients by combining the wavelet transform properties. We construct a nonlinear two-parameter threshold function by combining the structural characteristics of the soft threshold and hard threshold functions. Furthermore, we use particle swarm algorithm to optimize the parameter size to change the position and bending degree of the threshold function adaptively, thereby obtaining a good threshold function denoising model. Based on the analysis on the variation in the noise wavelet decomposition coefficient with decomposition layer, the unified threshold selection strategy is improved. Then, a gradient attenuation factor is introduced to construct a threshold selection method based on the noise mean square error of each decomposition layer. The experimental results show that, compared to the traditional wavelet domain denoising method, the proposed method significantly improves the signal-to-noise ratio, peak signal-to-noise ratio, and peak-to-bit error of X-ray pulsar noise signals, supporting the new ideas of X-ray pulsar signal denoising.

高迎东, 王宏力, 由四海, 冯磊, 何贻洋. 基于双参数阈值函数和多层阈值的X射线脉冲星信号消噪[J]. 光学学报, 2019, 39(12): 1204001. Yingdong Gao, Hongli Wang, Sihai You, Lei Feng, Yiyang He. X-Ray Pulsar Signal Denoising Based on Two-Parameter Threshold Function and Multi-Layer Threshold[J]. Acta Optica Sinica, 2019, 39(12): 1204001.

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