摘要
为了解决强噪声下识别率低的问题,提出了一种新的战场声目标特征参数提取方法。该方法将小波包分析和Teager能量算子(TEO)相结合,采用小波包对带噪声信号进行分解,对分解系数计算Teager能量。实验结果表明:基于小波包分析和Teager能量算子的特征参数提取方法具有良好的抗噪性能,提高了噪声环境下的声目标识别的准确率。
In order to solve the problem of low recognition rate under strong noise,a new method was proposed for feature extraction from acoustic targets by combining wavelet packet analysis with Teager energy operator（TEO）.Adopted wavelet packet to decompose noisy acoustic signal and computed Teager energy of decomposition parameters.The experiment results showed that the feature extraction method based on wavelet packet analysis and Teager energy operator had better robustness and improved recognition rate in the noisy environment.
出处
《探测与控制学报》
CSCD
北大核心
2010年第6期54-58,62,共6页
Journal of Detection & Control
关键词
声信号
特征提取
小波包分析
TEAGER能量算子
acoustic signal
feature extraction
wavelet packet analysis
teager energy operator
