自适应小波阈值去噪算法在低空飞行声目标的应用

发布时间：2018-03-21 18:45

  本文选题：小波去噪　切入点：阈值函数　出处：《振动与冲击》2017年09期 　论文类型：期刊论文

【摘要】：近年来,低空飞行声目标的探测与识别已得到军事领域的重点关注,而如何滤除信号中的背景噪声并准确保留信号的有效特征信息是该领域的一个难点。在研究小波去噪算法特点的基础上,针对低空飞行声目标信号的噪声特性,构建了一个新的阈值函数,通过自适应调整阈值函数实现在小波分解细尺度和宽尺度上对噪声信号最大限度的滤除,同时,运用香农熵理论来判断最优层数。通过大量的实验仿真验证,并与传统阈值去噪算法比较分析,结果表明该算法对去噪指标SNR有较大尺度的提高,可以更好的去除噪声,并对低空声目标信号去噪有很好的去噪效果。
[Abstract]:In recent years, the detection and recognition of low altitude acoustic targets has been paid more and more attention in the military field. However, how to filter the background noise from the signal and accurately retain the effective characteristic information of the signal is a difficulty in this field. Based on the study of the characteristics of the wavelet denoising algorithm, the noise characteristics of the low-altitude flight acoustic target signal are studied. A new threshold function is constructed, which adaptively adjusts the threshold function to maximize the filtering of the noise signal on the wavelet decomposition scale and the wide scale. At the same time, The Shannon entropy theory is used to determine the optimal number of layers. A large number of experiments are carried out and compared with the traditional threshold denoising algorithm. The results show that the algorithm can improve the denoising index SNR in a large scale and can remove noise better. And it has good denoising effect for low altitude acoustic target signal.
【作者单位】： 兰州理工大学电气工程与信息工程学院;兰州理工大学理学院;95876部队;
【基金】：国家自然科学基金(61663024)
【分类号】：TN911.4
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本文编号：1645091