摘要
在实际战场中，采样声信号不可避免的受到各种噪声和干扰的污染，导致声信号特征提取变得困难而不利于进一步的目标识别。为了有效去除混叠在战场声信号中的噪声信号。运用离散小波理论对其进行阂值去嗓处理。通过对几种去噪方法对比分析和基于MATLAB信号去噪的仿真试验，仿真结果表明对于战场声信号而言，基于Birge—Massart阂值算法具有更好的去噪效果。
In the practical battlefield, sampling acoustic signals are inevitably influenced by noise, which makes it difficult to extract the feature of acoustic signal and hinder the further target discrimination. In order to effectively eliminate the noise signal mixed in the battlefield - acoustic signal, the discrete wavelet theory is applied to threshold denoising.ln comparison with several methods ofdenoiseing and via the simulated denoising experiments based on MALAB, simulation results show that when coping with the battlefield-acoustic signal, the method based on Birge-Massart threshold algorithm is better at denoising than other methods.
作者
仝飞
顾晓辉
吕艳新
TONG Fei, GU Xiao-hui, LV Yan-xin （School of Mechanical Engineering, Nanjing UniversiW of Science and Technology, Nanjing 210094, China）
出处
《电脑知识与技术》
2010年第2期939-941,共3页
Computer Knowledge and Technology
关键词
战场声信号
小波变换
阈值去噪
MATLAB
去噪
battlefield - acoustic signal
wavelet transform
thresholddenoising
matlab
denoising
