摘要
麦克风阵列已广泛应用于音/视频会议、语音识别及增强等领域。声源定位是阵列信号处理的主要任务之一,是实现空间滤波的基础。基于阵列的定位算法分为超分辨算法和非超分辨算法。非超分辨类算法的定位精度受到阵列孔径的限制,只能用于定位精度要求较低的情况。超分辨类算法定位精度可以突破瑞利限,在一定条件下可以实现任意定位精度,具有极大的应用价值。传统的超分辨算法假设信源为窄带远场平稳信号,而麦克风阵列处理主要针对宽带短时平稳的语音信号,且声源可能位于阵列的近场,这导致DOA(direction of arrival)估计算法不能通用。基于麦克风阵列的声源多维定位与传统的信源定位相比,主要存在如下问题:
1) 宽带信号:在窄带条件下,阵元之间的相位差可以近似认为是信号源位置的函数,频率为一常量;而语音信号为宽带非调制信号,阵元之间的相位差为频率和信号源位置的复合函数。
2) 近场源信号:在麦克风阵列处理中,因为应用环境不同,声源可能位于阵列的近场或远场,而传统的阵列信号处理均假设信源位于阵列的远场。
3) 空间干扰源:在室内环境中,空间干扰源和语音信号同时辐射到阵列上,严重影响定位性能。
4) 多维定位:麦克风阵列应用一般需要二维/三维定位,传统的阵列处理算法主要针对一维DOA估计。
本文围绕这些问题,提出了几种声源定位算法,实现了声源多维定位,主要工作如下:
1) 提出了基于麦克风阵列的近场信号模型:根据语音的传播特性和阵列处理的要求,提出了基于球面波前的近场信号模型,该模型综合考虑了阵元之间的幅度衰减和时延两个因素。当信源与阵列的距离较远时,阵元接收信号之间的幅度差异减小,该模型可以退化为远场信号模型。针对多维定位问题,提出了麦克风阵列的一般设计原则,并设计三种麦克风阵列:二维均匀圆环麦克风阵列、三维均匀直线麦克风阵列和三维均匀球面麦克风阵
Microphone arrays (MA) are widely used in audio/video conferences, speech recognitions, and speech enhancements etc. The localization of the speech source is the primary task of the array signal processing, and the basis of spatial filter designing. The source localization strategies include the high (super)-resolution algorithms and the general resolution ones. To the general resolution method, the precision of localization is limited by the array aperture, and has only been used in low precision case. Used the high resolution algorithm, the precision of localization can get beyond the Rayleigh Resolution Limit decided by the array aperture, and can even gain arbitrary resolution at some case. Therefore, this type of methods is of great value. The classical high-resolution methods suppose that the signal sources are narrow-band and stationary in the far field. However, the speech signal is wide-band and short-time stationary in the near field. And then, the classical DOA (direction of arrival) estimation methods can't solve the speech source localization problems. Speech source multi-dimension localization (MDL) methods based MA, vs. classical DOA methods, have some problems as follows:
1) Wide-band signal: In the case of narrow-band signal, the phase-difference between two adjacent elements of array is supposed to be a function of source's location, and the frequency of the signal is a constant. While, speech signal is wide-band and non-modulated, whose phase-difference is a compound function of the frequency and the location of sources.
2) Near field source: In the MA processing, speech source is usually the near field of the array. While, the source lies in the far field of the array in the classical array processing.
3) Spatial interference signal: The spatial interference and speech signal are captured simultaneously by the MA in the room environment, resulting in the bad performance of the speech source localization
4) Multi-dimension localization: it requires two- or three-dimension localization in MA application, but only one-dimension localization in the classical array processing.
Focusing on these problems, several algorithms of speech source localization are presented as follows:
1) The near field signal model based on MA: To meet the array signal
引文
[1] Michael Brandstein, Darren Ward, Microphone Arrays: Signal Prpcessing Techniques and Applications, Berlin, Springer-Verlag, 2001.
[2] Acero, Acoustical and environmental robustness in automatic speech recognition, Kluwer, 1992.
[3] Y.Gong, Speech recognition in noisy environments: A survey, Speech Communication, vol.16, pp.261-291,1995
[4] J.C.Junqua and J.P.Haton, Robustness in automatic speech recognition.Kluwer, 1996.
[5] C.H.Lee, F.K.Soong, and K.K.Paliwal, Automatic speech and speaker recognition. Kluwer, 1996
[6] S.Furui,Recent advances in robust speech recognition,in Proc.of ESCANATO Workshop on robust Speech Recognition for Unknown Communication Channels,pp. 11-20,1997
[7] M.Omologo, P.Svaizer, and M.Matassoni,Environmental conditions and acoustic transduction in hands-free speech recognition, Speech Communication, vol.25, pp.75-95, 1998 。
[8] B.D.Van Veen and K.M.Buckley,Beamforming:A versatile approach to spatial filtering,Ieee ASSP Mag., vol.5,no.2,pp.4-24,Apr.1988
[9] T.D.Abhayapala, R.A.Kennedy, and R.C.Williamson, Near-field broadband array design using a radially invariant modal expansion, J. Acoust. Soc. Amer, vol.107, no.1, pp. 392-403, Jan.2000
[10] J. L. Flanagan, D. A. Berkeley, G. W. Elko, etc., Autodirective microphone systems, Acustical, vol.73,pp.58-71,1991
[11] W.Kellermann, A self-steering digital microphone array, in Proc. IEEE Int. Conf. Acoust., Speech, Signal Processing(ICASSP-91),1991,vol.5,pp.3581-3584.
[12] F.Khalil,J.P.Jullien,and A.Gilloire.Microphone array for sound pickup in teleconference sustems,J.Audio Eng.Soc, vol.42,no.9,pp.691-700,Sept.1994
[13] J.Lardies, Acoustic ring array with constant beamwidth over a very wide frequency range, Acoust. Letters, vol.13, no.5, pp.77-81, 1989.
[14] R. Smith, Constant beam width receiving arrays for broad band sonar systems, Acustica, vol.23, pp.21-26,1970.
[15] M.M.Goodwin and GW.Elko, Constant beamwidth beamforming,in Proc.IEEE Int. Conf. Acoust., Speech, Signal Processing(ICASSP-93),1993,vol.1,pp.169-172
[16] John E. Adcock, Optimal Filtering And Speech Recognition With Microphone Arrays, Ph.D. dissertation, Division of Engineering, Brown University, Providence, Rhode Island,May 2001
[17] Krasny, Leonid, Oraintara, Sootorn, Microphone antenna array using voice activity detection, USA patent number: 20030027600.
[18] P. Aarabi and S. Zaky, Robust sound localization using multi-source audiovisual information fusion, Inform. Fusion, vol. 2, pp. 209-223,2001.
[19] D. Rabinkin, R. J. Renomeron, A. Dahl, J. French, J. Flanagan, and M. Bianchi, A DSP implementation of source location using microphone arrays, J. Acoust. Soc. Amer., vol. 99, no. 4, p. 2503, 1996.
[20] Yamada, S. Nakamura, and K. Shikano, Distant-talking speech recognition based on a 3-D Viterbi search using a microphone array, IEEE Trans. Speech Audio Processing, vol. 10, pp. 48-56, Feb. 2002.
[21] Tailiang Ju, Yiliang Xu and Qicong Peng, Speech source localization in near field, pp. 769-772, vol.2, ICCCAS'04, UESTC, Chengdu, China,2004, IDS Number: BBC53, EI: 05038790125.
[22] LiveSize Phone Datasheet at http://www.lifesize.com/products/lifesize_phone/
[23] Microsoft Co. Microphone Array Support in Windows Vista, August 26, 2005
[24] Tashev, H. Malvar. A New Beamformer Design Algorithm for Microphone Arrays. Proceedings of ICASSP, Philadelphia, PA, USA, March 2005.
[25] Tashev. Gain Self-Calibration Procedure for Microphone Arrays. Proceedings of ICME, Taipei, Taiwan, July 2004.
[26] Intel High Definition Audio specification at http://www.intel.com/standards/hdaudio/
[27] Simon Doclo, Multi-Microphone Noise Reduction And Dereverberation Techniques For Speech Applications,Ph.D. dissertation, Katholieke Universiteit Leuven Faculteit Toegepaste Wetenschappen Departement Elektrotechniek Kasteelpark Arenberg 10, 3001 Leuven (Heverlee), Belgium
[28] 赵力,语言信号处理,北京,机械工业出版社,2003年4月,第5~30页。
[29] J. Adcock, M. Brandstein, H. Silverman, A practical timedelay estimator for localizing speech sources with a microphone array, Comput. Speech Lang., 1995, vol. 9, pp. 153-169.
[30] M. Brandstein, Time-delay estimation of reverberated speech exploiting harmonic structure, J. Acoust. Soc. Amer., 1999, vol. 105, no. 5, pp. 2914-2919.
[31] B. Champagne, S. Bedard, A. Stephanne, Effects of room reverberation on time-delay estimation performance, Proc.IEEE Int. Conf. Acoust., Speech, Signal Processing, 1994, pp.II 261-264.
[32] Acero, H. Attias, J.C. Platt, L. Deng, Speech denoising and dereverberation using probabilistic models, in Adv. Neural Information Processing Systems, 2001, pp. 758-764.
[33] H. Attias, L. Deng, A new approach to speech enhancement with a microphone array using em and mixture models, in Proc. 7th Int. Conf. on Spoken Language Processing, 2002.
[34] Panayiotis G, Georgiou, Chris Kyriakakis, An Alternative Model for Sound Signals Encountered in Reverberant Environments; Robust Maximum Likelihood Localization and Parameter Estimation Based on a Sub-Gaussian Model, Audio Engineering Society(AES) 113th Convention Paper, 2002, Los Angeles, USA
[35] Ilyas Potamitis, Huimin Chen, and George Tremoulis, Tracking of Multiple Moving Speakers with Multiple Microphone Arrays, IEEE Trans. On Speech and Audio Processing, 2004, Vol. 12(5): 520-529.
[36] G. Carter. Variance bounds for passively locating an acoustic source with a symmetric line array. Journal of Acoustical Society of America, 1977, Vol.62(4):922-926
[37] W. Hahn, S.Tretter. Optimum processing for delay vector estimation in passive signal arrays. IEEE Transactions on Information Theory, 1973, Vol.19(1):608-614
[38] W. Hahn. Optimum signal processing for passive sonar range and bearing estimation. Journal of Acoustical Society of America, 1975, V6158. (1) :1210-1217
[39] M.Wax, T.Kailath. Optimum localization of multiple sources by passive arrays. IEEE Transactions on Acoustics, Speech and Signal Processing, 1983, Vol.31 (5):1210-1217
[40] V. M. Alvarado, Talker Localization and Optimal Placement of Microphone for a Linear Microphone Array using Stochastic Region Contraction. Ph. D thesis, Brown University, Providence, Rhode Island, USA, May 1990.
[41] H. F. Silverman, S. E. Kirtman, A two-stage algorithm for determining talker location from linear microphone array data, Computer, Speech, and Language, vol. 6, pp. 129-152, April 1992.
[42] J. Dibiase, A High-Accuracy, Low-Latency Technique for Talker Localization in Reverberant Environments, Ph. D Thesis, Brown University, Providence, Rhode Island, USA, May 2000.
[43] Dirk Bechler, Kristian Kroschel, Reliability Criteria Evaluation for TDOA Estimates in a Variety of Real Environments, 2005 IEEE Int. Conf. Acoustics, Speech and Signal Processing (ICASSP), Pennsylvania, Philadelphia, USA, 2005, pp. Ⅳ: 985-988.
[44] 王宏禹,邱天爽,自适应噪声抵消和时间延迟估计,大连,大连理工大学出版社,1999.8.
[45] 周浩洋,基于麦克风阵列的声源定位方法研究,硕士论文,大连,大连理工大学,2002年3月。
[46] 陆晓燕,基于麦克风阵列实现声源定位,硕士论文,大连,大连理工大学,2003年3月。
[47] P. S. Murthy and B. Yegnanarayana, Robustness of group-delay-based method for extraction of significant instants of excitation from speech signals, IEEE Trans. Speech Audio Processing, vol. 7, no. 6, pp. 609-619, Nov. 1999.
[48] B. Yegnanarayana and N. J. Veldhuis, Extraction of vocal-tract system characteristics from speech signals, IEEE Trans. Speech Audio Processing, vol. 6, pp. 313-327, Jul. 1998.
[49] B. Yegnanarayana and P. S. Murthy, Enhancement of reverberant speech using LP residual signal, IEEE Trans. Speech Audio Processing, vol. 8, no. 3, pp. 267-281, May 2000
[50] B. Yegnanarayana, S. R. M. Prasanna, and K. S. Rao, Speech enhancement using excitation source information, in Proc. IEEE Int. Conf. Acoust., Speech, Signal Processing, vol. I, Orlando, FL, May 2002, pp. 541-544
[51] 王永良,陈辉,彭应宁等,空间谱估计理论与算法,北京,清华大学出版社,2004 年11月, page2~14。
[52] Krim H., Viberg M., Two decades of array signal processing research, IEEE Sigan Processing Magazine, 1996,13(4), page: 67-94.
[53] Kay S.M., Marple S.L., Spectrum analysis-a modern perspective. Proc. of the IEEE,1981, 11.
[54] Burg J.P., Maximum entropy spectral analysis, Proc. of the 37th meeting of the Annual Int. SEG Meeting, Oklahoma City,OK,1967
[55] Capon J. High-resolution frequency-wavenumber spectrum analysis. Proc. of IEEE, 1969, 57(8):1408~1418.
[56] Kumaresan R., Tufts D.W., Estimating the angels of arrival of plane waves. IEEE Trans. OnAES, 1983, 19(1): 134~139
[57] Schmidit R.O., Multiple emitter locateon and signal parameter estimateion, IEEE trans., 1986, AP-34(3): 276~280.
[58] Cadzow J.A., Kim Y.S., Shie D.C., General direction of arrival estimateion: a signal subspace approach, IEEE Trans. On AES, 1989, 25(1): 31~46.
[59] Rao B.D., Hari K.V.S., Performance analysis of Root-MUSIC, IEEE Trans. On ASSP, 1989, 37(12): 1939-1949.
[60] Kung S.Y., Arun K.S., Rao D.V.B., State space and SVD based approximation methods for the harmonic retrieval proplem, J. Opt. Soc. Amer., 1983, 73(12): 1799-1811.
[61] Rao R., Kailath T., ESPRIT-a subspace rotation approach to estimation of parameters of cissoids in noise, IEEE Trans. On ASSP, 1986, 34(10): 1340-1342.
[62] Rao R., Kailath T, ESPRIT-estimation of signal parameters via rotational invariantce techniques, IEEE Trans, on ASSP, 1989, 37(7): 984-995.
[63] Stoica P., Nehorai A., MUSIC, Maximum likelihood, and Cramer-Rao bound, In Proc. ICASSP, 1988,2296-2299.
[64] Ottersren B., Viberg M., Stoica P., Nehorai A., Exact and large sample ML techniques for parameter estimateion and detection in array processing, In Haykin, Litva, and shepherd, editors, Radar array processing, Springer-Verlag, Berlin,1993,99~151.
[65] Cadzow J.A., A high resolution direction of arrival algorithm for narrow-band coherent and incoherent sources, IEEE Trans.on ASSP, 1988, 36(7): 965-979.
[66] Clergeot H., Tressens S., Ouamri A., Perfermance of high resolution frequencies estimateion methods compared to the Cramer-Rao bounds, IEEE Trans, on ASSP, 1989, 37(11): 1703-1720.
[67] Ziskind I., Wax M. Maximum likelihood localization of multiple sources by alternating projection, IEEE. Trans. On ASSP, 1988,36(10): 1553-1559.
[68] Stoica P., Sharman K.C., Novel eigenanalysis method for direction estimateion, IEEE. Proceeding, Pt.F, 1990, 137(1): 19-26.
[69] Viberg M., Ottersren B., Kailath T., Detection and estimateion in sensor arrays using wighted subspace fitting, IEEE. Trans, on SP, 1991, 39(11): 2436-2499.
[70] Bresler Y., Macovski A., Exact maximum likelihood parameter estimation of superimposed exponential signals in noise, IEEE. Trans. On ASSP, 1986, 34(5): 1081-1089.
[71] J. C. Chen, K. Yao, and R. E.Hudson, Source localization and beamforming, IEEE Signal Processing Magazine, vol. 19, no. 2, pp. 30-39, 2002.
[72] Valee S., Kabal P. Wideband array processing using two-sided correlation transformation. IEEE Trans. On SP, 1995,43(1): 160-172
[73] Hung H., Kaveh M. Focusing Matrices for coherent signal subspace processing. IEEE Trans. OnASSP, 1988,36(8):1272~1281.
[74] Doron M.A., Weiss A.J., On focusing matrices for wideband array processing, IEEE Trans. On SP, 1992, 40(6): 1295-1302.
[75] Valee S., Champagne B. Localization of wideband signals using Least-squares and Total Least-squares approaches. IEEE Trans. On SP, 1999,47(5): 1213-1222.
[76] J. C. Chen, R. E. Hudson, and K. Yao, Maximum-likelihood source localization and unknown sensor location estimation for wideband signals in the near-field, IEEE Trans. Signal Processing, vol. 50, no. 8, pp. 1843-1854, 2002.
[77] J.C. Chen, , Kung Yao, Hudson ,R.E., Acoustic Source Localization and Beamforming: Theory and Practice, EURASIP Journal on Applied Signal Processing 2003:4, 359-370
[78] Futoshi Asano, Masataka Goto, Katunobu Itou, Real-time Sound Source localization and Separation System and its Application to Automatic Speech Recognition, Proc. Eurospeech, Alborg, Denmark, 2001,pp: 1013-1016.
[79] 邵怀宗,林静然,彭启琮,居太亮,基于麦克风阵列的声源定位研究,云南民族大学学报,2004/4,Vol.13,No.4 pp.256-258;
[80] 林静然,彭启琮,邵怀宗,“基于麦克风阵列的双波束近场定位及语音分离”,仪器仪表学报,2004增刊,pp1000-1002;
[81] 林静然,彭启琮,邵怀宗,居太亮,基于麦克风均匀圆阵的近场声源定位及分离,2004全国博士生学术论坛,pp73-76。
[82] 林静然,基于麦克风阵列的说话人跟踪及语音分离实现技术的研究,硕士论文,指导教师:彭启琮,2005年,电子科技大学图书馆。
[83] 徐胜,基于智能麦克风阵列的说话人跟踪技术,硕士论文,指导教师:彭启琮,2004年,电子科技大学图书馆。
[84] 吴云韬,非平稳、色噪声环境下的参数估计方法研究,博士论文,西安电子科技大学,2003年8月。
[85] H. Sinath and V. U. Reddy, Analysis of MUSIC Algorithm with sensor gain and phase preturbations, Signal processing 23, PP: 245-256, 1991.
[86] Fu. Li., R. Vaccaro, Performance degradation of DOA estimators due to unknown noise fields, IEEE. Trans, SP-40, No. 3, PP: 686-690, 1992.
[87] J. P. Le Cadre, Parametric methods for spatial signal processing known colored noise fields, IEEE Trans. ASSP, Vol. 37, No. 7, 1989.
[88] V. Nagesha and S. Kay, Maximum likelihood estimation for array processing in colored noise, IEEE Trans. SP, Vol. 44, No. 2, 1996.
[89] J. F. Bohme, D. Kraus, On least squares methods for direction of arrival estimation in the presence of unknown noise fields, Proc. ICASSP, Apr., 1988.
[90] A. H. Tewfik, Direction finding in the presence of colored noise by candidate identification, IEEE Trans. SP, Vol. 39, No. 9, 1991.
[91] Porat, B. Friedlander, Direction finding algorithms based on high-order statistics, IEEE. Trans. SP, Vol. 39, No. 9, 1991.
[92] Y. H. Chen, Y. S. Lin, Fourth-order cumulant matrices for DOA estimation, IEE. Proc. Radar Sonar Navig., Vol. 141, No. 3, June, 1994.
[93] Haesun Park, ESPRIT direction-of-arrival estimation in the presence of spatially correlated noise, SIAM, J. Matrix Anal. Appl., Vol: 15, No. 1, 1994.
[94] Schell. S. V, An overview of sensor array processing for cyclostationary signal, Gardner, W. A. ed. Cyclostationarity in Communications and Signal Processing, New York, IEEE Press, 1994.
[95] Halder, M. Viberg, T. Kailath, An efficient non-iterative method for estimating the angles of arrival of known signals, ICASSP'93, pp: 1396-1400, 1993.
[96] 居太亮,彭启琮,邵怀宗,基于麦克风阵列的近场声源定位子阵算法研究,电子测量与仪器学报,已录用,待刊出。
[97] Lim J. S., Oppenheim A. V., Enhancement and bandwidth compression of noisy speech. Proceedings of. IEEE, 1979, 67(12): 1586-1604.
[98] Steven F. Boll, Suppression of Acoustic Noise In Speech using Spectral Subtraction, IEEE Trans. Acoustics, Speech and Signal Processing, Vol, ASSP-27, April 1979, p113-120.
[99] Y. Ephraim, H. L. Van Trees, A Signal Subspace Approach for Speech Enhancement, IEEE Trans. On Speech and Audio Processing Vol. 3 No. 4 1995 p251-266.
[100] Futoshi Asano, et. al, Speech Enhancement Based on the Subspace Method. IEEE Trans. On Speech and Audio Processing, Vol. 8 No. 5 2000(9) p497-507
[101] Y. Kaneda, J. Ohga, Adaptive Microphone-array System for Noise Reduction, IEEE Trans. Acoust., Speech & Signal Process., vol. ASSP-34, pp. 1391—1400, 1986.
[102] Zelinski. R., A Microphone Array with Adaptive Post-filtering for Noise Reduction in Reverberant Rooms, IEEE Trans. Acoustics, Speech and Signal Processing, ICASSP88, p2578-2581
[103] Zelinski. R., Noise reduction Based on Microphene Array with LMS Adaptive Post-Filtering. IEEE Trans. Electronics Letters, Vol. 26, Issue: 24, 1990 p2036-2037;
[104] Ian A. MCCowan, Herv'e Bourlard. Microphone Array post-filtering for diffuse Noise Field, Acoustics, speech and Signal Processing, 2002, ICASSP2002 vol(1), 12-17, May 2002, pI905-I908.
[105] Mallat S., Hwang W L., Singularity Detection and Processing with Wavelets, IEEE Trans. On Information Theory, 1992, vol. 32(2)
[106] DonoHO D L. Denoiseing by Soft Threshold, IEEE Trans. On Information Theory, 1995, vol. 3
[107] J.D.Gibson, B.Koo, S.d.Gray, Filtering of colored noise for speech enhancement and coding, IEEE Trans. Acoust., Speech, Signal Processing, ASSP-39, No.B, 1991, pp: 1732-1742.
[108] J.S.Lim, A.V.Oppenheim, All-pole modeling of degraded speech, IEEE Trans. Acoust., Speech, Signal Processing, ASSP-26, No.3, June 1978, pp: 197-210.
[109] K.K.Paliwal, A.Basu, A speech enhancement method based on Kalman filtering, ICASSP'87, pp: 177-180.
[110] Y.Ephraim, D.Malah, H.Juang,On the application of Hidden Markov models for enhancing noisy speech, IEEE Trans. Acoust, Speech, Signal Processing, Vol.37, No.12, 1989, pp: 1846-1856.
[111] Y.Ephraim,A Bayesian estimation approach for speech enhancement using Hidden Markov models, IEEE Trans. Signal Processing Vol.40, No.4 ,Apr 1992
[112] S. Haykin. Adaptive Filter Theory. Fourth Edition. 北京:电子工业出版社. 2002
[113] Zelinski. R., A microphone array with adaptive post-filtering for noise reduction in reverberant rooms, IEEE Trans. Acoustics, Speech and Signal Processing, ICASSP-88, April, 1988, pp: 2578-2581.
[114] Simon Doclo, Marc Moonen, Multimicrophone Noise Reduction Using Recursive GSVD- Based Optimal Filtering With ANC Postprocessing Stage, IEEE. Trans, on Speech and Audio Processing, Vol. 13, No. 1, January 2005, pp: 53-69.
[115] S. Doclo, M. Moonen, GSVD-based optimal filtering for single and multi-microphone speech enhancement, IEEE Trans. Signal Process., vol. 50, no. 9, pp: 2230-2244, Sep. 2002.
[116] T.Rutkowski, A.Cichocki, and A.K. Barros, Speech enhancement from interfering sounds using CASA techniques and blind source separation, Proceedings of 3rd International Conference on Independent Component Analysis and Blind Signal Separation, pp: 728-733, ICA, Dec. 2001.
[117] T.Rutkowski, A.Cichocki, and A.K. Barros, Speech enhancement using adaptive filters and independent component analysis approach, Proceedings of International Conference on Artificial Intelligence in Science and Technology (AISAT2000), pp.191-196,2000.
[118] S. Van Gerven and D. Van Compemolle, Signal separation by symmetric Signal Processing, vol. 43, pp. 1602-1612, July 1995
[119] Weinstein, M. Feder, and A. Oppenheim, Multi-channel signal separation by decorrelation, IEEE. Trans. Speech Audio Processing, vol. 1, pp. 405-413, Oct. 1993.
[120] P. Comon, Independent component analysis: A new concept?, Signal Processing, vol. 36, no. 3, pp. 287-314, Apr. 1994
[121] C. Jutten and J. Herault, Blind separation of sources, Part Ⅰ: An adaptive algorithm based on neuromimetic architecture, Signal processing, vol. 24, pp. 1-10, 1991.
[122] S. Douglas, Blind Signal separation and Blind Deconvolution, in Handbook of Neural Networks for Signal Processing, (J.-N. Hwang and Y.-H. Hu, eds.), CRC Press, 2001
[123] Grbic N, Dahl M, Claesson I. Neural Network based Adaptive Microphone Array System for Speech Enhancement. IEEE International Joint Conference on Neural Networks Proceedings, 1998, 3: 2180-2183.
[124] 赵光,贾林飞,王冬霞,王琼,基于神经网络的麦克风阵列语音增强方法,辽宁工学院学报,Vol.25(3),2005年6月。
[125] 居太亮,邵怀宗,彭启琮,林静然,基于任意麦克风阵列的近场声源三维定位算法研究,信号处理,已录用,待刊出。
[126] 居太亮,彭启琮,邵怀宗,林静然,麦克风阵列拓扑结构研究,2005通信理论与信号处理年会论文集,桂林,2005,电子工业出版社,第154-159页。
[127] 杜功焕、朱哲民等,声学基础,南京,南京大学出版社,2001。
[128] Harry L. Van Trees, Optimum Array Processing, Part Ⅳ of Detection, Estimation, and Modulation Theory, John Wiley & Sons, Inc., Publication, 2002
[129] Prabhakar S. Naidu, Sensor Array Signal Processing, CRC Press, 2001
[130] 居太亮,邵怀宗,彭启琮,林静然,近场声源三维定位MUSIC算法研究,电子测量与仪器学报,已录用,待刊出。
[131] 邵怀宗,居太亮,彭启琮,林静然,一种声源定位方法,专利申请号:200510051313.0.
[132] 居太亮、彭启琮,邵怀宗等,基于任意麦克风阵列的声源二维DOA估计算法研究,通信学报,2005(8),pp.129~133。
[133] 陈昊,空间谱估计算法的高速实现,硕士论文,成都,电子科技大学,2003年 4月。
[134] Pisarenko, V. F., on the estimation of spectra by means of nonlinear functions of covariance matrix, Geophys. J. R. Astr. Soc., 28, 511-531, 1972.
[135] M. Wax, T. J. Shan, T. Kailath., Spatio-temporal spectral analysis by eigenstructure methods, IEEE Trans. Acoust., Speech, Signal Processing, vol ASSP-32, pp. 817—827, Aug 1984
[136] Yin Q, Zou L. Separately estimation the frequency wavenumber of coherent sources by signal eignvector smoothing technique. Proc. ICASSP, 1988, pp. 2905~2908
[137] Futoshi ASANO, Hideki ASOH, and Toshihiro MATSUI, Sound Source Localization and Separation in Near Field, Ieice Trans. Fundamentals, Vol. E83-A, No. 11 Nov. 2000.
[138] Futoshi Asano, Hideki Asoh and Toshihiro Matsui, Sound source localization and signal separation for office robot "jijo-2", Proc. MFI'99, pp. 243-248
[139] S. F. Boll, Suppression of Acoustic Noise in Speech Using Spectral Subtract, IEEE. Trans. Acoustic, Speech, and Signal Processing, vol. ASSP-29, no. 2, pp: 113-120, 1979.
[140] M. Berouti, R. Schwartz, J. Makhoul, Enhancement of speech Corrupted by Additive Noise, Proc. IEEE. Int. conf. Acoustic, Speech, and Signal Processing, pp: 208-211, 1979.
[141] 居太亮 彭启琮 邵怀宗 林静然,基于麦克风阵列的声源三维定位聚焦算法研究,声学学报,已投。
[142] 居太亮、彭启琮,邵怀宗等,二维DOA估计宽带聚焦算法研究,电子科技大学学报,已录用,待刊出。
[143] 吴云韬,廖桂生,张光斌,空间非平稳噪声环境下的DOA估计新算法,西安电子科技大学学报,Vol.30,No.1,2003。
[144] 吴云韬,廖桂生,陈建锋,一种色噪声环境下的DOA估计新算法,《电子学报》,Vol.25,No.12,2001。
[145] 居太亮,邵怀宗,彭启琮,林静然,一种基于麦克风阵列的宽带波束形成技术,专利申请号:20051009074.X
[146] Ju Tailiang, Peng Qi-cong, Shao Huai-zong, Lin Jing-ran, Speech Source localization Sub-space Algorithm Research Based on Microphone Array in Near Field, Vol. 3, pp. 695~701, ICEMI'2005, NJTU, Beijing, china, 2005, IDS Number: BDR67
[147] R. G. Lorenz, S. P. Boyd, Robust minimum variance beamforming, IEEE Trans. Signal Processing, vol. 53, no. 5, May. 2005.
[148] D. Feldman and L. J. Griffiths, A projection approach to robust adaptive beamforming, IEEE Trans. Signal Processing, vol. 42, pp. 867-876, Apr. 1994.
[149] M. H. Er, A. Cantoni, An alternative formulation for an optimum beamformer with robustness capability, Proc. Int. Elect. Eng. F, Commun., Radar, Signal Process., vol. 132, pp. 447-460, 1985.
[150] J. Li, P. Stoica, Z. Wang, On robust Capon beamforming and diagonal, IEEE Trans. Signal Processing, vol. 51, no. 7, July. 2003.
[151] S. A. Vorobyov, Y. Rong, A. B. Gershman, Robust adaptive beamforming using probability-constrained optimization, Proc. IEEE SSP Workshop, Bordeaux, France, July 2005.
[152] S. A. Vorobyov, A. B. Gershman, and Z. Luo, Robust adaptive beamforming using worst-case performance optimization: A solution to the signal mismatch problem, IEEE Trans. Signal Processing, vol. 51, pp. 313-324, Feb. 2003.
[153] 杨益新,声呐波束形成与波束域高分辨方位估计技术研究,博士学位论文,西北工业大学,2002年4月。
[154] Krolik J, Swingler D. Focused wide-band array processing by spatial resampling. Trans. Acoust., Speech, and Signal Processing, 1990; 38(2): 356-360.
[155] 智婉君,水下宽带阵列信号处理的高分辨技术研究,博士学位论文,西北工业大学,1998。
[156] Ward D B, Kermedy R A, Williamson R C. Theory and design of broadband sensor arrays with frequency invariant far-field beam patterns. J. Acoust. Soc. Am., 1995; 97(2): 1023-1034.
[157] 张保高,宽带接收水声基阵优化设计研究,博士学位论文,西北工业大学,1999。