脉冲声信号影响锥特征的自适应选取  

Adaptively selecting the cone of influence features of impulsive acoustic signals

作　　者：王璐 刘小睿[1] 王勇 招启军[5] 鲍明[1,2,3,6] WANG Lu;LIU Xiaorui;WANG Bo;ZHAO Qijun;BAO Ming(Institute of Acoustics,Chinese Academy of Sciences ,Beijing 100190;Key Laboratory of Noise and Vibration Research,Chinese Academy of Sciences, Beijing 100190;University of Chinese Academy of Sciences ,Beijing 100049;Key Laboratory of Aerodynamic Noise Control,China Aerodynamics Research and Development Center,Mianyang 621000;Nanjing University of Aeronautics and Astronautics,Nanjing 210016;The School of Automation,Northwestern Polytechnical University ,Xi'an 710072)

机构地区：[1]中国科学院声学研究所,北京100190 [2]中国科学院噪声与振动重点实验室,北京100190 [3]中国科学院大学,北京100049 [4]中国空气动力研究与发展中心低速空气动力研究所,绵阳621000 [5]南京航空航天大学,南京210016 [6]西北工业大学自动化学院,西安710072

出　　处：《声学学报》2022年第6期843-855,共13页Acta Acustica

基　　金：国家自然科学基金项目(11774379)资助。

摘　　要：为了解决低信噪比下脉冲声信号影响锥特征的自适应选取和检测问题,提出了一种改进的整体嵌套边缘检测方法。利用脉冲信号小波域的时间-尺度分析谱图中明显的边缘效应特征,构造自适应影响锥(A-COI)模型。该模型可自适应输出最适影响锥部分,在减弱噪声干扰的同时最大程度的包含了脉冲信号的主要特征。进而将最适影响锥部分对应的小波系数用于脉冲信号检测,有效提升了低信噪比下的检测性能。对典型直升机桨-涡干扰脉冲信号的仿真和实验数据进行分析,结果表明在0 dB,2 dB,5 dB信噪比的复杂环境下,使用基于A-COI模型的检测率分别达到了65.13%,82.33%,95.27%,相对于传统固定大小影响锥的检测算法提升了42.42%,22.99%和2.36%。An improved holistically-nested edge detection method is proposed to solve the problem of adaptively selecting and detecting the cone of influence features of impulsive acoustic signals under low Signal-to-Noise Ratio(SNR).By leveraging the significant edge effects in the time-scale analysis spectrum obtained by the wavelet transform for the impulsive signal,an Adaptive Cone of Influence(A-COI) model is constructed.The model can adaptively output the most suitable area in the cone of influence,which contains the main features of the impulsive signal to the greatest extent while reducing the noise interference.The wavelet coefficient corresponding to the optimum cone of influence is used to assist the design of the impulsive signal detector,and effectively improves the detection performance under low SNR.The simulation and experimental data of helicopter blade-vortex interference signal(a typical helicopter impulsive signal) are analyzed.The results verify that the results show that under the complex environments with SNR of 0 dB,2 dB and 5 dB,the detection rate based on the A-COI model reaches 65.13%,82.33% and 95.27%,which compared with the traditional fixed-size impact cone detection algorithm,the improvement is 42.42%,22.99% and 2.36% respectively.

关 键 词：脉冲信号 影响锥 噪声干扰 脉冲声 边缘效应 低信噪比 尺度分析 检测率 

分 类 号：TB52[理学—物理]