شکل‌دهی وفقی پرتو آکوستیکی با روش بهبودیافته تفاضلی
محورهای موضوعی : مهندسی برق و کامپیوترنگار سرشار 1 , مهدی بکرانی 2 *
1 - دانشكده مهندسی برق و كامپيوتر، دانشگاه صنعتی قم، ایران
2 - دانشكده مهندسی برق و كامپيوتر، دانشگاه صنعتی قم، ایران
کلید واژه: آرایه میکروفن, بهره نویز سفید, شکل‌دهی پرتو, فاکتور جهت‌دهی,
چکیده مقاله :
شکل‌دهنده‌های پرتو تفاضلی عملکرد مؤثری در کاربردهای پهن‌باند نظیر کاربردهای آکوستیکی دارند؛ اما دارای بهره نویز سفید محدودی هستند. در این مقاله به‌منظور بهبود بهره نویز سفید شکل‌دهنده پرتو تفاضلی، یک الگوریتم شکل‌دهنده تفاضلی بر مبنای وزن‌دهی وفقی ارائه شده که از روش شکل‌دهی پرتو پاسخ کمینه واریانس بدون اعوجاج (MVDR) بهره می‌گیرد. به این منظور، ابتدا شکل‌دهی پرتو تفاضلی در دو مرحله اجرا شده که در مرحله اول، تفاضل مکانی مشاهده‌ها به‌دست آمده و در مرحله دوم شکل‌دهنده پرتو بهینه گردید. سپس با محاسبه ضرایب و تلفیق شکل‌دهنده‌های پرتو تفاضلی و MVDR، شکل‌دهنده پرتو وفقی پیشنهادی به‌دست آمد. در شکل‌دهنده پیشنهادی، سهم روش تفاضلی و روش MVDR در ایجاد سیگنال خروجی توسط ضریب تلفیق وفقی که تابع فرکانس، فاصله بین میکروفن‌ها، زاویه هدف و تعداد میکروفن‌ها است، تعیین می‌گردد. شکل‌دهنده پرتو پیشنهادی با درنظرگرفتن چهار میکروفن و فاصله دو سانتی‌متری بین میکروفن‌ها منجر به بهبود بهره نویز سفید به مقدار 35 دسی‌بل و بهره SNR به مقدار 18 دسی‌بل نسبت به شکل‌دهنده پرتو تفاضلی در فرکانس 1 کیلوهرتز می‌شود. همچنین فاکتور جهت‌دهی در الگوریتم وفقی پیشنهادی به میزان 5/3 دسی‌بل نسبت به شکل‌دهنده پرتو تفاضلی بهبود پیدا کرده است.
Differential beamformers exhibit effective performance in broadband applications, such as acoustic applications, but they have limited white noise gain. To address this limitation, this paper introduces an adaptive weighting-based algorithm designed to enhance the white noise gain of the differential beamformer by leveraging the minimum variance distortionless response (MVDR) beamforming technique. For this purpose, differential beamforming is implemented in two stages: in the first stage, the spatial difference of observations is obtained, and in the second stage, the beamformer is optimized. Subsequently, by calculating the coefficients and combining the differential and MVDR beamformers, the proposed adaptive beamformer is derived. In this beamformer, to construct the output signal, the contribution of the differential and MVDR methods is dynamically adjusted using an adaptive combination coefficient, which is a function of frequency, microphone inter-distance, target angle, and the number of microphones. The proposed beamformer, considering four microphones spaced 2 cm apart reveals a remarkable enhancement in white noise gain by 35 dB and SNR gain by 18 dB at a frequency of 1 kHz. Additionally, the proposed adaptive algorithm demonstrates a 3.5 dB improvement in directivity factor over its differential counterpart.
[1] T. Tripathy and C. Novak, Acoustic Beamforming: Automotive Applications for Noise, Vibrations and Harshness, University of Windsor, 2017.
[2] J. Benesty, C. Pan, and J. Chen, Fundamentals of Differential Beamforming, Singapore: Springer, Apr. 2016.
[3] U. Michel, "History of acoustic beamforming," in Proc. 1st Berlin Beamforming Conf., 17 pp., Berlin, Germany, 21-22 Nov. 2006.
[4] J. Benesty, J. Chen, and Y. Huang, Microphone Array Signal Processing, Berlin: Springer-Verlag, 2008.
[5] M. Bekrani and M. Lotfizad, "A modified wavelet-domain adaptive filtering algorithm for stereophonic acoustic echo cancellation in the teleconferencing application," in Proc. Int. Symp. on Telecommunications, pp. 548-554, Tehran, Iran, 27-28 Aug. 2008.
[6] M. Bekrani, A. W. H. Khong, and M. Lotfizad, "Neural network based adaptive echo cancellation for stereophonic teleconferencing application," in Proc. IEEE Int. Conf. on Multimedia and Expo, Singapore, Singapore, pp. 1172-1177, 19-23 Jul. 2010.
[7] م. بکرانی، "طراحی و تحلیل یک الگوریتم وفقی LMS/Newton بهبودیافته در کاربرد حذف پژواک آکوستیکی،" نشریه مهندسی برق و مهندسی کامپيوتر ايران، ب- مهندسی کامپیوتر، سال 18، شماره 2، صص. 116-105، تابستان 1399.
[8] M. Bekrani and H. Zayyani, "A weighted soft-max PNLMS algorithm for sparse system identification," International J. of Information and Communication Technology Research, vol. 8, no. 3, pp. 7-14, Summer 2016.
[9] W. Yang, G. Huang, J. Benesty, and J. Chen, "On the design of flexible kronecker product beamformers with linear microphone arrays," in Proc. Int. Conf. on Acoustics, Speech and Signal Processing, ICASSP'19, pp. 441-445, Brighton, UK, 12-17 May 2019.
[10] G. Huang, J. Benesty, I. Cohen, and J. Chen, "A simple theory and new method of differential beamforming with uniform linear microphone arrays," IEEE/ACM Trans. on Audio, Speech, and Language Processing, vol. 28, pp. 1079-1093, 2020.
[11] G. Huang, Y. Wang, J. Benesty, I. Cohen, and J. Chen, "Combined differential beamforming with uniform linear microphone arrays," in Proc. Int. Conf. on Acoustics, Speech and Signal Processing, ICASSP'21, pp. 781-785, Toronto, Canada, 6-11 Jun. 2021.
[12] G. Huang, J. Chen, J. Benesty, I. Cohen, and X. Zhao, "Steerable differential beamformers with planar microphone arrays," EURASIP J. on Audio, Speech, and Music Processing, vol. 2020, Article ID: 15, 18 pp., 2020.
[13] G. Huang, J. Chen, and J. Benesty, "On the design of differential beamformers with arbitrary planar microphone array geometry," J. of the Acoustical Society of America, vol. 144, no. 1, Article ID: EL66, Jul. 2018.
[14] X. Wang, G. Huang, I. Cohen, J. Benesty, and J. Chen, "Robust steerable differential beamformers with null constraints for concentric circular microphone arrays," in Proc. Int. Conf. on Acoustics, Speech and Signal Processing, ICASSP'21, pp. 4465-4469, Toronto, Canada, 6-11 Jun. 2021.
[15] G. Huang, I. Cohen, J. Chen, and J. Benesty, "Continuously steerable differential beamformers with null constraints for circular microphone arrays," J. of the Acoustical Society of America, vol. 148, no. 3, pp. 1248-1258, Sept. 2020.
[16] G. Huang, J. Chen, and J. Benesty, "Insights into frequency-invariant beamforming with concentric circular microphone arrays," IEEE/ACM Trans. on Audio, Speech, and Language Processing, vol. 26, no. 12, pp. 2305-2318, Dec. 2018.
[17] G. Huang, J. Benesty, and J. Chen, "Design of robust concentric circular differential microphone arrays," J. of the Acoustical Society of America, vol. 141, no. 5, pp. 3236-3249, May 2017.
[18] J. Benesty, I. Cohen, and J. Chen, Fundamentals of Signal Enhancement and Array Signal Processing, John Wiley & Sons, Dec. 2017.
[19] G. Huang, J. Benesty, I. Cohen, and J. Chen, "Differential beamforming on graphs," IEEE/ACM Trans. on Audio, Speech, and Language Processing, vol. 28, pp. 901-913, Feb. 2020.
[20] G. Huang, J. Benesty, J. Chen, and I. Cohen, "Robust and steerable kronecker product differential beamforming with rectangular microphone arrays," in Proc. Int. Conf. on Acoustics, Speech and Signal Processing, ICASSP'20, pp. 211-215, Barcelona, Spain, 4-8 May 2020.
[21] M. Bekrani, A. H. T. Nguyen, and A. W. H. Khong, "An adaptive non-linear process for under-determined virtual microphone beamforming," in Proc. Int. Conf. on Acoustics, Speech and Signal Processing, ICASSP'21, pp. 4495-4499, Toronto, Canada, 6-11 Jun. 2021.
[22] G. Itzhak and I. Cohen, "Differential and constant-beamwidth beamforming with uniform rectangular arrays," in Proc. Int. Workshop on Acoustic Signal Enhancement, WAENC'22, 5 pp., Bamberg, Germany, 5-8 Sept. 2022.
[23] X. Wang, I. Cohen, J. Benesty, and J. Chen, "Study of the null directions on the performance of differential beamformers," in Proc. Int. Conf. on Acoustics, Speech and Signal Processing, ICASSP'22, pp. 4928-4932, Singapore, Singapore, 23-27 May 2022.
[24] G. Itzhak, I. Cohen, and J. Benesty, "Multistage approach for steerable differential beamforming with rectangular arrays," Speech Communication, vol. 142, pp. 61-76, Jul. 2022.
[25] A. A. Nugraha, K. Sekiguchi, M. Fontaine, Y. Bando, and K. Yoshii, "DNN-free low-latency adaptive speech enhancement based on frame-online beamforming powered by block-online FastMNMF," in Proc. Int. Workshop on Acoustic Signal Enhancement, IWAENC'22, 5 pp., Bamberg, Germany, 5-8 Sept. 2022.
[26] H. Kim, K. Kang, and J. W. Shin, "Factorized MVDR deep beamforming for multi-channel speech enhancement," IEEE Signal Processing Letters, vol. 29, pp. 1898-1902, 2022.
[27] X. Xiao, et al., "Deep beamforming networks for multi-channel speech recognition," in Proc. Int. Conf. on Acoustics, Speech and Signal Processing, ICASSP'16, pp. 5745-5749, Shanghai, China, 20-25 Mar. 2016.
[28] I. McCowan, Microphone Arrays: A Tutorial, Queensland University, Australia, pp. 1-38, Apr. 2001.
[29] E. A. P. Habets, J. Benesty, I. Cohen, S. Gannot, and J. Dmochowski, "New insights into the MVDR beamformer in room acoustics," IEEE Trans. on Audio, Speech, and Language Processing, vol. 18, no. 1, pp. 158-170, Jun. 2009.
[30] T. Dietzen, S. Doclo, M. Moonen, and T. V. Waterschoot, "Integrated sidelobe cancellation and linear prediction Kalman filter for joint multi-microphone speech dereverberation, interfering speech cancellation, and noise reduction," IEEE/ACM Trans. on Audion, Speech, and Language Processing, vol. 28, pp. 740-754, 2020.