Near-field localization algorithm of multiple sound sources based on approximated kernel density estimator

被引：0
|
作者：
Fang Y.-Z. [1 ]
Xu Z.-Y. [1 ]
Zhao Z. [1 ]
机构：
[1] School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing
来源：
Xu, Zhi-Yong (ezyxu@mail.njust.edu.cn) | 1600年 / Editorial Board of Journal on Communications卷 / 38期
基金：
中国国家自然科学基金;
关键词：
Approximated kernel density estimator; Data fusion; Microphone array; Multi-stage of sub-band processing; Spatial likelihood function;
D O I：
10.11959/j.issn.1000-436x.2017013
中图分类号：
学科分类号：
摘要：
For near-field localization of multiple sound sources in reverberant environments, a algorithm model based on approximated kernel density estimator (KDE) was proposed. Multi-stage (MS) of sub-band processing was introduced to effectively solve the spatial aliasing by wide spacing. Spatial likelihood function (SLF) was built for multi-dimensional fusion by using two operators, sum (S) and prod (P). Then four algorithms, S-KDE, P-KDE, S-KDEMS, P-KDEMS, were derived. By the comprehensive comparison of the two statistical indicators root mean square error (RMSE) and percentage of SLF (PSLF) which denoted the recognition, P-KDEMS is confirmed as a near-field localization algorithm of multiple sound sources with high robustness and recognition. © 2017, Editorial Board of Journal on Communications. All right reserved.
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页码：106 / 116
页数：10
相关论文
共 16 条
  • [1] Wu K., Khong A.W.H., Sound source localization and tracking, Context Aware Human-Robot and Human-Agent Interaction, pp. 55-78, (2016)
  • [2] Knapp C.H., Carter G.C., The generalized correlation method for estimation of time delay, IEEE Transactions on Acoustics, Speech, and Signal Processing, 24, 4, pp. 320-327, (1976)
  • [3] Brandstein M.S., Silverman H.F., A practical methodology for speech source localization with microphone arrays, Computer Speech and Language, 11, 2, pp. 91-126, (1997)
  • [4] Rabinkin D.V., Ranomeron R.J., Dahl A., Et al., A DSP implementation of source location using microphone arrays, Journal of the Acoustical Society of America, 99, 4, pp. 88-99, (1996)
  • [5] Ward D.B., Williamson R.C., Particle filter beamforming for acoustic source localization in a reverberant environment, 2002 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), pp. 1777-1780, (2002)
  • [6] Dibiase J.H., A high-accuracy, low-latency technique for talker localization in reverberant environments using microphone arrays, pp. 73-105, (2000)
  • [7] Pertila P., Korhonen T., Visa A., Measurement combination for acoustic source localization in a room environment, EURASIP Journal on Audio Speech and Music Processing, 2008, pp. 1-14, (2008)
  • [8] Tsiami A., Katsamanis A., Maragos P., Et al., Experiments in acoustic source localization using sparse arrays in adverse indoors environments, 2014 European Signal Processing Conference (EUSIPCO), pp. 2390-2394, (2014)
  • [9] Xu Z.Y., Zhao Z., Liu M., Real-time unambiguous passive direction finding for multiple sound sources with widely spaced microphone array, Journal of Electronics & Information Technology, 33, 9, pp. 2056-2061, (2011)
  • [10] Nesta F., Omologo M., Generalized state coherence transform for multidimensional TDOA estimation of multiple sources, IEEE Transactions on Audio, Speech, and Language Processing, 20, 1, pp. 246-260, (2012)
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