四种典型波束形成声源识别清晰化方法  

Four Typical Clearness Methods for Beamforming Acoustic Source Identification

作　　者：杨洋[1] 褚志刚[2] 

机构地区：[1]重庆工业职业技术学院汽车工程学院,重庆401120 [2]重庆大学机械工程学院,重庆400044

出　　处：《数据采集与处理》2014年第2期316-326,共11页Journal of Data Acquisition and Processing

基　　金：牵引动力国家重点实验室开发课题(TPL0903)资助项目;中央高校基本科研业务费(CDJZR13110001)资助项目

摘　　要：为准确运用波束形成声源识别结果清晰化方法识别声源,基于仿真模拟的已知单声源、不相干声源、相干声源的识别成像图及性能曲线和进行的扬声器声源识别算例试验,对比分析DAMAS2,FFT-NNLS,CLEAN,CLEAN-SC的性能,结果表明:四种方法在识别单声源、不相干声源时均能有效衰减旁瓣,显著提高分辨率,CLEAN-SC的准确度最高;对于相干声源,DAMAS2,FFT-NNLS的识别准确度高,CLEAN-SC不能识别相干声源;计算效率方面,DAMAS2最高,FFT-NNLS次之,CLEAN,CLEAN-SC略低。In order to utilize the clearness methods for beamforming acoustic source identifica- tion exactly, imaging diagrams of the given single source, incoherent sources and coherent sources, together with corresponding performance curves are simulated and the loudspeaker sound source identification experiments are conducted. The characteristics of DAMAS2, FFT- NNLS, CLEAN and CLEAN-SC are demonstrated and compared with each other. Three con- clusions are drawn. Firstly, for single source or incoherent sources, all these four methods could not only suppress sidelobes effectively but also improve resolution remarkably and CLEAN-SC has the highest accuracy rating especially. Secondly, DAMAS2 and FFT-NNLS have high accuracy rating for coherent sources, while CLEAN-SC couldn＇t identify coherent sources. Thirdly, DAMAS2 has the highest computational efficiency, FFT-NNLS follows, CLEAN and CLEAN-SC are slightly slow.

关 键 词：波束形成 声源识别 清晰化方法 对比分析 

分 类 号：TB5[理学—物理] TH11[理学—声学]