抑制风噪声的频点离散值加权GCC-PHAT时延估计算法
详细信息    查看全文 | 推荐本文 |
  • 英文篇名:GCC-PHAT time difference estimation algorithm based on binary frequency weight with suppressing wind noise
  • 作者:乔健 ; 王建明
  • 英文作者:Qiao Jian;Wang Jianming;Department of Computer Science and Technology,Nanjing Tech University;
  • 关键词:广义互相关 ; 到达时差 ; 离散频点权值 ; 风噪声
  • 英文关键词:GCC;;TDOA;;binary frequency weight;;wind noise
  • 中文刊名:DZJY
  • 英文刊名:Application of Electronic Technique
  • 机构:南京工业大学计算机科学与技术学院;
  • 出版日期:2018-03-06
  • 出版单位:电子技术应用
  • 年:2018
  • 期:v.44;No.477
  • 语种:中文;
  • 页:DZJY201803018
  • 页数:6
  • CN:03
  • ISSN:11-2305/TN
  • 分类号:78-82+86
摘要
针对麦克风阵列使用GCC-PHAT算法估计信号到达时差对加性噪声敏感,以及基于信噪比估计的连续值加权GCC-PHAT算法无法消除环境中类似风噪声的变化噪声干扰的情况,提出了一种抑制风噪声的频点加权GCC-PHAT算法。通过分析已有算法的不足,新算法选择使用离散频点加权,并通过信号频点间相干性量化值和时域关联性计算权值,去除风噪声干扰频点;同时估计声源信号活跃度,调整算法运算量。实验表明,与已有的GCCPHAT算法相比,新算法能有效消除风噪声对估计结果的干扰,同时降低运算负载。
        Aiming at the problems that GCC-PHAT algorithm is sensitive to additive noise and the weighted GCC-PHAT algorithm based on prior SNR can ′ t eliminate the jamming of non-stationary noise —— wind noise, an improved GCC-PHAT algorithm is presented. The improved algorithm utilizes the binary frequency weight calculated by magnitude of coherence and correlation in signal adjacent frames to eliminate frequency component disturbed by wind noise. Meanwhile, computational load of the algorithm would be modulated with voice activity according to binary weight. The experiment results show that the proposed algorithm can effectively suppress wind noise and significantly improve computational load.
引文
[1]BADALI A,VALIN J M,MICHAUD F,et al.Evaluating real-time audio localization algorithms for artificial audition in robotics[C].IEEE/RSJ International Conference on Intelligent Robots and Systems,2009,IROS 2009,IEEE,2009:2033-2038.
    [2]VALIN J M,MICHAUD F,ROUAT J.Robust localization and tracking of simultaneous moving sound sources using beamforming and particle filtering[J].Robotics and Autonomous Systems,2007,55(3):216-228.
    [3]COHEN I,BERDUGO B.Noise estimation by minima controlled recursive averaging for robust speech enhancement[J].IEEE Signal Processing Letters,2002,9(1):12-15.
    [4]夏丙寅,鲍长春.适应噪声强度突变的噪声估计加速方法[J].信号处理,2013,29(10):1336-1345.
    [5]宋知用.MATLAB在语音信号分析与合成中的应用[M].北京:北京航空航天大学出版社,2013.
    [6]NELKE C M,VARY P.Measurement,analysis and simulation of wind noise signals for mobile communication de vices[C].2014 14th International Workshop on Acoustic Signal Enhancement(IWAENC),IEEE,2014:327-331.
    [7]NELKE C M,VARY P.Dual microphone wind noise reduction by exploiting the complex coherence[C].Proceedings of Speech Communication,11.ITG Symposium,VDE,2014:1-4.
    [8]LOIZOU P C.语音增强-理论与实践[M].高毅,肖莉,邓方,译.成都:电子科技大学出版社,2012.
    [9]武晓光,郭天文.基于房间冲激响应的声学模型的建立和仿真[J].微电子学与计算机,2014(4):56-59.

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700