Collaborative Sensor Networking Towards Real-Time Acoustical Beamforming in Free-Space and Limited Reverberance
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Wireless sensor networks have been attracting increasing research interest given the recent advances in microelectronics, array processing, and wireless networking. Consisting of a large collection of small, wireless, low-cost, integrated sensing, computing, and communicating nodes capable of performing various demanding collaborative space-time processing tasks, wireless sensor network technology poses various unique design challenges, particularly for real-time operation. In this paper, we review the Approximate Maximum-Likelihood (AML) method for source localization and direction-of-arrival (DOA) estimations. Then, we consider the use of least-squares (LS) method applied to DOA bearing crossings to perform source localization. A novel virtual array model applicable to the AML-DOA estimation method is proposed for reverberant scenarios. Details on the wireless acoustical testbed are given. We consider the use of Compaq iPAQ 3760s, which are handheld, battery-powered device normally meant to be used as personal organizers (PDAs), as sensor nodes. The iPAQ provide a reasonable balance of cost, availability, and functionality. It has a build-in StrongARM processor, microphone, codec for acoustic acquisition and processing, and a PCMCIA bus for external IEEE 802.11b wireless cards for radio communication. The iPAQs form a distributed sensor network to perform real-time acoustical beamforming. Computational times and associated real-time processing tasks are described. Field measured results for linear, triangular, and square subarrays in free-space and reverberant scenarios are presented. These results show the effective and robust operation of the proposed algorithms and their implementations on a real-time acoustical wireless testbed.
[1] 211 J. Agre and L. Clare, An Integrated Architecture for Cooperative Sensing and Networks Computer, vol. 33, no. 5, May 2000.
[2] G. Pottie and W. Kaiser, Wireless Integrated Network Sensors Comm. ACM, vol. 43, May 2000.
[3] S. Kumar, F. Zhao, and D. Shepherd, IEEE Signal Processing Magazine, special issue on collaborative signal and information processing in microsensor networks, vol. 19, Mar. 2002.
[4] S. Iyengar and S. Kumar, Int'l J. High Performance Computing Applications, special issue on advances in information technology for high performance and computational intensive distributed sensor networks, vol. 16, Fall 2002.
[5] K. Yao, D. Estrin, and Y.H. Hu, European J. Applied Signal Processing, special issue on sensor networks, vol. 2003, no. 4, Mar. 2003.
[6] B.D.V. Veen and K.M. Buckley, Beamforming: A Versatile Approach to Spatial Filtering IEEE Acoustics, Speech, and Signal Processing Magazine, vol. 5, pp. 4-24, Apr. 1988.
[7] J. Chen, K. Yao, and R. Hudson, Source Localization and Beamforming IEEE Signal Processing Magazine, vol. 19, pp. 30-39, Mar. 2002.
[8] M.S. Branstein and D.B. Ward, Microphone Arrays: Techinques and Applications. Springer-Verlag, 2001.
[9] H.L.V. Trees, Optimal Array Processing. New York: Wiley, 2002.
[10] Hp-Compaq Products, available athttp:/www.hp.com/, 2004.
[11] The Familiar Project, available athttp:/familiar.handhelds.org/, 2004.
[12] J. Elson, L. Girod, and D. Estrin, Fine-Grained Network Time Synchronization Using Reference Broadcasts Proc. Symp. Operating Systems Principles (SOSP), Dec. 2002.
[13] J. Chen, R. 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, Aug. 2002.
[14] I. Ziskine and M. Wax, Maximum Likelihood Localization of Multiple Sources by Alternating Projection IEEE Trans. Acoustics, Speech, and Signal Processing, vol. 36, no. 10, pp. 1553-1560, Oct. 1988.
[15] L. Yip, J.C. Chen, R.E. Hudson, and K. Yao, Numerical Implementation of the AML Algorithm for Wideband DOA Estimation Proc. SPIE, vol. 5205, pp. 164-172, Aug. 2003.
[16] D. Johnson and D. Dudgeon, Array Signal Processing, 1993.
[17] J. Chen, K. Yao, T. Tung, C. Reed, and D. Chen, Source Localization and Tracking of a Wideband Source Using a Randomly Distributed Beamforming Sensor Array Int'l J. High Performance Computing Applications, vol. 16, no. 3, pp. 259-272, Fall 2002.
[18] J.B. Allen and D. Berkley, Image Method for Efficiency Simulating Small-Room Acoustics Acoustical Soc. Am., vol. 65, no. 4, Apr. 1979.
[19] L. Girod, V. Bychkobskiy, J. Elson, and D. Estrin, Locating Tiny Sensors in Time and Space: A Case Study Proc. IEEE Int'l Conf. Computer Design (ICCD), 2002.
[20] P. Stoica and A. Nehorai, Music, Maximum Likelihood, and Cramer-Rao Bound IEEE Trans. Acoustics, Speech, and Signal Processing, vol. 37, pp. 720-741, 1989.
Index Terms:
Beamforming, source localization, distributed sensor network, wireless network, microphone array, time synchronization, reverberance.
Citation:
Pierpaolo Bergamo, Shadnaz Asgari, Hanbiao Wang, Daniela Maniezzo, Len Yip, Ralph E. Hudson, Kung Yao, Deborah Estrin, "Collaborative Sensor Networking Towards Real-Time Acoustical Beamforming in Free-Space and Limited Reverberance," IEEE Transactions on Mobile Computing, vol. 3, no. 3, pp. 211-224, July 2004, doi:10.1109/TMC.2004.17
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