一种稳健的室内无模糊多声源TDOA估计算法

房玉琢; 许志勇

doi:10.11999/JEIT150824

一种稳健的室内无模糊多声源TDOA估计算法

doi: 10.11999/JEIT150824

房玉琢¹,
许志勇¹

基金项目:

国家自然科学基金(61171167, 61401203)，江苏省自然科学基金(BK20130776)

计量
- 文章访问数: 1468
- HTML全文浏览量: 193
- PDF下载量: 491
- 被引次数: 0
出版历程
- 收稿日期: 2015-07-09
- 修回日期: 2015-12-18
- 刊出日期: 2016-05-19

A Robust Algorithm for Unambiguous TDOA Estimation of Multiple Sound Sources under Indoor Environment

FANG Yuzhuo¹,
XU Zhiyong¹

Funds:

The National Natural Science Foundation of China (61171167, 61401203), Natural Science Foundation of Jiangsu Province (BK20130776)

摘要

摘要: 该文针对室内环境下的宽间距多声源到达时间差(TDOA)估计问题，研究了一种基于近似核密度估计(KDE)的无模糊算法。根据声频信号的短时频谱稀疏性，利用相关性检测(CT)提取单个声源能量占优的时频支撑域，进而将观测信号的归一化互功率谱(NCS)所构建的近似核函数通过累加平均削弱室内混响的干扰，同时引入多阶段(MS)分频带处理有效解决宽间距时的空域模糊。理论推导及仿真研究验证了该算法是一种稳健的室内无模糊多声源TDOA估计算法。
- 语音信号处理 /
- 麦克风阵列 /
- 归一化互功率谱 /
- 相关性检测 /
- 近似核密度函数 /
- 无模糊到达时间差估计
Abstract: For Time Difference Of Arrival (TDOA) estimation of multiple sound sources with wide spacing under indoor environment, an unambiguous algorithm based on approximated Kernel Destiny Estimator (KDE) is studied. According to the short-time spectral sparseness of audio signals, the time-frequency bin with energy dominance of a single source is extracted from Coherence Test (CT), then an approximated kernel function constructed of Normalized Cross-Spectrum (NCS) of obtained signals is used to weaken the interference of indoor reverberation with cumulative average, while adding Multi-Stage (MS) to divide the frequency band, the spatial ambiguity with wide spacing can be solved effectively. This algorithm is verified as an unambiguous TDOA estimation algorithm of multi-source under indoor environment by both theoretical derivation and simulation results.

HTML全文

参考文献(17)

KNAPP C H and CARTER G C. The generalized correlation method for estimation of time delay[J]. IEEE Transactions on Acoustics, Speech, and Signal Processing, 1976, 24(4): 320-327.

TSIAMI A, KATSAMANIS A, MARAGOS P, et al. Experiments in acoustic source localization using sparse arrays in adverse indoors environments[C]. Proceedings of 2014 European Signal Processing Conference (EUSIPCO), Lisbon, Portugal, 2014: 2390-2394.

张超, 吴小培, 吕钊. 基于独立分量分析的运动目标检测算法中对通道数选择和观测向量生成方式的实验和分析[J]. 电子与信息学报, 2015, 37(1): 137-142. doi: 10.11999/ JEIT140197.

ZHANG Chao, WU Xiaopei, and L Zhao. Experiments and analysis on observation vector generation and channel number selection in motion detection algorithm based on independent component analysis[J]. Journal of Electronics Information Technology, 2015, 37(1): 137-142. doi: 10.11999/ JEIT140197.

LOMBARD A, ZHENG Y, BUCHNER H, et al. TDOA estimation for multiple sound sources in noisy and reverberant environments using broadband independent component analysis[J]. IEEE Transactions on Audio, Speech, and Language Processing, 2011, 19(6): 1490-1503.

NESTA F, SVAIZER P, and OMOLOGO M. Cumulative state coherence transform for a robust two-channel multiple source localization[C]. Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation (ICA), Berlin, Germany, 2009: 290-297.

NESTA F and OMOLOGO M. Generalized state coherence transform for multidimensional TDOA estimation of multiple sources[J]. IEEE Transactions on Audio, Speech, and Language Processing, 2012, 20(1): 246-260.

REDDY V V, KHONG W H, and NG B P. Unambiguous speech DOA estimation under spatial aliasing conditions[J]. IEEE Transactions on Audio, Speech, and Language Processing, 2014, 22(12): 2133-2145.

YILMAZ O and RICKARD S. Blind separation of speech mixtures via time-frequency masking[J]. IEEE Transactions on Signal Processing, 2004, 52(7): 1830-1847.

ARAKI S, SAWADA H, MUKAI R, et al. DOA estimation for multiple sparse sources with normalized observation vector clustering[C]. Proceedings of 2006 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP 2006), Toulouse, France, 2006: 33-36.

BRUTTI A and NESTA F. Tracking of multidimensional TDOA for multiple sources with distributed microphone pairs[J]. Computer Speech Language, 2013, 27(3): 660-682.

THO N T N, ZHAO Shengkui, and JONES D L. Robust DOA estimation of multiple speech sources[C]. Proceedings of 2014 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), Florence, Italy, 2014: 2287-2291.

许志勇, 赵兆, 刘明. 宽间距麦克风阵列实时无模糊多声源被动测向[J]. 电子与信息学报, 2011, 33(9): 2056-2061. doi: 10.3724/SP.J.1146.2010.01273.

XU Zhiyong, ZHAO Zhao, and LIU Ming. Real-time unambiguious passive direction finding for multiple sound sources with widely spaced microphone array[J]. Journal of Electronics Information Technology, 2011, 33(9): 2056-2061. doi: 10.3724/SP.J.1146.2010.01273.

GUSTAFFSON T, RAO B D, and TRIVEDI M. Source localization in reverberant environments: Modeling and statistical analysis[J]. IEEE Transactions on Speech and Audio Processing, 2003, 11(6): 791-803.

LEHMANN E and JOHANSSON A. Prediction of energy decay in room impulse responses simulated with an image-source model[J]. Acoustical Society of America, 2008, 124(1): 269-277.

BLANDIN C, OZEROV A, and VINCENT E. Multi-source TDOA estimation in reverberant audio using angular spectra and clustering[J]. Signal Processing, 2012, 92(8): 1950-1960.

施引文献

资源附件(0)

访问统计