Underwater Acoustic Target Classification Based on Modified GFCC Features

摘要：

　　A major challenge for underwater acoustic target classification relates to significant performance decrease in complex underwater environment.Recent researches have shown that the auditory feature extracted from Gammatone filter has remarkable ability on robust speaker identification.If this remarkable ability can be simulated,the accuracy of underwater acoustic target classification will be improved significantly in noisy underwater environment.Aiming at this purpose,a novel implementation of the Gammatone filter-based feature is proposed and applied to underwater acoustic target classification in this paper.Support Vector Machine(SVM)is used as the classifier in our experiments.Classification results indicates that the proposed feature,namely Modified Gammatone Frequency Cepstrum Coefficients(MGFCC)features are more robust than conventional acoustic features in underwater acoustic target classification.

关键词： Auditory feature Gammatone filter underwater acoustic target classification

作者: Zixu Lian Ke Xu Jianwei Wan Gang Li

作者单位: College of Electronic Science and Engineering National University of Defense Technology Changsha,China

会议类型: 国际会议

会议名称: 2017 IEEE 2nd Advanced Information Technology,Electronic and Automation Control Conference(IAEAC 2017)(2017 IEEE 第2届先进信息技术、电子与自动化控制国际会议)

会议地点: 重庆

会议语种:英文

页码: 258-262

在线出版日期: 2017-03-25（万方平台首次上网日期，不代表论文的发表时间）