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Editorial

Editorial Deborah Estrin Department of Computer Science, University of California, Los Angeles (UCLA), Los Angeles, CA 90095-1596, USA Email: destrin@cs.ucla.edu Yu Hen Hu Department of Electrical and Computer Engineering, University of Wisconsin-Madison, 1415 Engineering Drive, Madison, WI 53706-1691, USA Email: hu@engr.wisc.edu Advances in low-cost and low-power wireless communication, microsensor, and microprocessor hardware, as well as progress in ad hoc networking routing and protocols, distributed signal and array processing, pervasive computing, and embedded systems have all made sensor networking a topic of active interest. In recent years, the Internet has been able to provide a large number of users with the ability to move diverse forms of information readily and thus revolutionized business, industry, defense, science, education, research, and human interactions. Sensor networking may, in the long run, be equally significant by providing measurement of the physical phenomena around us, leading to their understanding and ultimately the utilization of this information for a wide range of applications. Potential applications of sensor networking include environmental monitoring, health care monitoring, battlefield surveillance and reconnaissance, modern highway, modern manufacturing, condition-based maintenance of complex systems, and so forth. In order to understand and build sensor networks, diverse technology and technical disciplines are involved. However, in this special issue we deal only with various signal processing aspects of sensor networking. Of the seven papers, four of them deal with source localization, two of them with tracking, and one with sensor network decomposition and organization. Energy-Based Collaborative Source Localization Using Acoustic Microsensor Array, by D. Li and Y. H. Hu, uses acoustic energy measurements to perform source localization. This approach assumes the acoustic source energy decays inversely with the square of the distance. By comparing acoustic sensor energy measurements around the source, the source location can be estimated as the intersection of multiple hyperspheres. The Fusion of Distributed Microphone Arrays for Sound Localization, by P. Aarabi, also deals with acoustic source localization. The author proposes to use the spatial observability function (SOF), which gives an indication of how well a microphone array perceives events at different spatial position. Each microphone array also has a spatial likelihood function (SLF) which reports the likelihood of a source at each spatial location. SOF and SLF approaches are used together for sound localization. In A Self-Localization Method for Wireless Sensor Networks, by R. L. Moses, D. Krishnamurthy, and R. Patterson, the authors consider the problem of locating and orienting a network of unattended sensors by using a number of known source signals for calibration purposes. The maximum-likelihood (ML) estimation and Cram´ r-Rao Bound (CRB) techniques are used. e Acoustic Source Localization and Beamforming: Theory and Practice, by J. C. Chen, K. Yao, and R. E. Hudson, again uses the ML method for direct localization of wideband acoustical source in the near field and uses the cross bearing of the direction-of-arrivals (DOA) for localization in the far field. For multiple sources, an alternating projection procedure is used. CRB analysis provides various insights for the localization problem. Dynamic Agent Classification and Tracking Using an Ad Hoc Mobile Acoustic Sensor Network, by D. Friedlander, C. Griffin, N. Jacobson, S. Phoha, and R. R. Brooks, presents methods for dynamic distributed signal processing using an ad hoc mobile network of sensors to detect, identify, and track targets. Forming dynamic clusters around events of interest allows for processing multiple events in parallel over different geographic areas along the trajectory of the targets. In Collaborative In-Network Processing for Target Tracking, J. Liu, J. Reich, and F. Zhao consider collaborative signal 320 processing using acoustic-amplitude sensors for target distance estimation and DOA sensors for bearing estimation. The information-driven sensor querying framework selectively activates sensors based on their utility and cost. Issues of distributed processing for tracking and energy efficiency of the network are addressed. Preprocessing in a Tiered Sensor Network for Habitat Monitoring, by H. Wang, D. Estrin, and L. Girod, considers some common principles for task-decomposition and collaboration for tiered sensor networks. The system has a few powerful macronodes in the first tier and many less-powerful nodes in the second tier. Each macronode combines data collected by many micronodes for target classification and localization. Application is made to habitat monitoring and classification and localization of birds. All seven of these papers use simulations and measured data to verify the proposed methods. In the coming years, it is expected that sensor networking will become ever more important both in research and industry and that hardware and software availability will enable significant data collection and field experimentation. Kung Yao received the B.S.E. (Highest Honors), M.A., and Ph.D. degrees in electrical engineering all from Princeton University, Princeton, NJ. He was a NAS-NRC Postdoctoral Research Fellow at the University of California, Berkeley. Presently, he is a Professor in the Electrical Engineering Department at UCLA. In 1969, he was a Visiting Assistant Professor at the Massachusetts Institute of Technology. In 1985–1988, he served as an Assistant Dean of the School of Engineering and Applied Science at UCLA. His research and professional interests include sensor array system, digital communication theory and system, smart antenna and wireless radio system, chaos communications and system theory, digital and array and signal and array processing, systolic and VLSI algorithms, architectures and systems, radar system, and simulation. He has published over 250 journal and conference papers. Dr. Yao received the IEEE Signal Processing Society’s 1993 Senior Award in VLSI Signal Processing. He was the coeditor of a two-volume series of an IEEE Reprint Book on High Performance VLSI Signal Processing, IEEE Press, 1997. In 1991– 1993, he was the Associate Editor of VLSI Signal Processing of the IEEE Trans. on Circuits and Systems. Since 1999, he is an Associate Editor of the IEEE Communications Letters. He is a member of the Editorial Board of the Journal of VLSI Signal Processing and Integration: the VLSI Journal. He was also a Guest Editor of a Special Issue on Applications of Chaos in Modern Communication Systems of the IEEE Trans. on Circuits and Systems—Part I in 2001. He is a Fellow of IEEE. Deborah Estrin is a Professor of computer science at UCLA and Director of the Center for Embedded Networked Sensing (CENS), a newly awarded National Science Foundation Science and Technology Center. She received her Ph.D. degree in computer science from the MIT (1985) and was on the faculty of Computer Science at USC from 1986 through mid-2000, where she received the National Science Foundation, Presidential EURASIP Journal on Applied Signal Processing Young Investigator Award for her research in network interconnection and security (1987). During the subsequent 10 years her research focused on the design of network and routing protocols for very large, global networks. Estrin has been instrumental in defining the national research agenda for wireless sensor networks, first chairing a 1998 DARPA ISAT study and then a 2001 NRC study; the latter culminated in an NRC publication—Embedded Everywhere: A Research Agenda for Networked System of Embedded Computers. Estrin’s research group develops algorithms and systems to support rapidly-deployable and robustly operating networks of many thousands of physically embedded devices. She is particularly interested in applications to environmental monitoring. Estrin has served on numerous program committees and editorial boards, including SIGCOMM, Mobicom, SOSP, and ACM/IEEE Transactions on Networks. She is a Fellow of the ACM and the AAAS. Yu Hen Hu received the B.S.E.E. degree from National Taiwan University, Taiwan, in 1976. He received the M.S. and Ph.D. degrees both in electrical engineering from University of Southern California, Los Angeles, Calif in 1980 and 1982, respectively. Currently, he is a Professor at the Electrical and Computer Engineering Department of the University of Wisconsin-Madison, Wis, USA. Previously, he has been with the Electrical Engineering Department of the Southern Methodist University, Dallas, Tex, USA. Dr. Hu’s research interests include multimedia signal processing, design methodology and implementation of signal processing algorithms and systems, sensor network and distributive signal processing algorithms, and neural network signal processing. He published more than 200 journal and conference papers and edited two books: Programmable Digital Signal Processors and Handbook of Neural Network Signal Processing. Dr. Hu is a Fellow of IEEE. He served as Associate Editor for IEEE Transactions on Signal Processing, IEEE Signal Processing Letters, Journal of VLSI Signal Processing, EURASIP Journal on Applied Signal Processing. He served as Secretary of IEEE signal processing society, board of governors of IEEE neural network council, Chair of IEEE signal processing society, and neural network signal processing technical committee. Photograph © Turisme de Barcelona / J. Trullàs Preliminary call for papers The 2011 European Signal Processing Conference (EUSIPCO 2011) is the nineteenth in a series of conferences promoted by the European Association for Signal Processing (EURASIP, www.eurasip.org). This year edition will take place in Barcelona, capital city of Catalonia (Spain), and will be jointly organized by the Centre Tecnològic de Telecomunicacions de Catalunya (CTTC) and the Universitat Politècnica de Catalunya (UPC). EUSIPCO 2011 will focus on key aspects of signal processing theory and applications as li t d b l li ti listed below. A Acceptance of submissions will b b d on quality, t f b i i ill be based lit relevance and originality. Accepted papers will be published in the EUSIPCO proceedings and presented during the conference. Paper submissions, proposals for tutorials and proposals for special sessions are invited in, but not limited to, the following areas of interest. Organizing Committee Honorary Chair Miguel A. Lagunas (CTTC) General Chair Ana I. Pérez Neira (UPC) General Vice Chair Carles Antón Haro (CTTC) Technical Program Chair Xavier Mestre (CTTC) Technical Program Co Chairs Javier Hernando (UPC) Montserrat Pardàs (UPC) Plenary Talks Ferran Marqués (UPC) Yonina Eldar (Technion) Special Sessions Ignacio Santamaría (Unversidad de Cantabria) Mats Bengtsson (KTH) Finances Montserrat Nájar (UPC) Tutorials Daniel P. Palomar (Hong Kong UST) Beatrice Pesquet Popescu (ENST) Publicity Stephan Pfletschinger (CTTC) Mònica Navarro (CTTC) Publications Antonio Pascual (UPC) Carles Fernández (CTTC) Industrial Liaison & Exhibits I d i l Li i E hibi Angeliki Alexiou (University of Piraeus) Albert Sitjà (CTTC) International Liaison Ju Liu (Shandong University China) Jinhong Yuan (UNSW Australia) Tamas Sziranyi (SZTAKI Hungary) Rich Stern (CMU USA) Ricardo L. de Queiroz (UNB Brazil) Areas of Interest • Audio and electro acoustics. • Design, implementation, and applications of signal processing systems. • Multimedia signal processing and coding. l d l d d • Image and multidimensional signal processing. • Signal detection and estimation. • Sensor array and multi channel signal processing. • Sensor fusion in networked systems. • Signal processing for communications. • Medical imaging and image analysis. • Non stationary, non linear and non Gaussian signal processing. Submissions Procedures to submit a paper and proposals for special sessions and tutorials will be detailed at www.eusipco2011.org. Submitted papers must be camera ready, no more than 5 pages long, and conforming to the standard specified on the EUSIPCO 2011 web site. First authors who are registered students can participate in the best student paper competition. Important Deadlines: Proposals f special sessions P l for i l i Proposals for tutorials Electronic submission of full papers Notification of acceptance Submission of camera ready papers Webpage: www.eusipco2011.org 15 Dec 2010 D 18 Feb 2011 21 Feb 2011 23 May 2011 6 Jun 2011 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png EURASIP Journal on Advances in Signal Processing Hindawi Publishing Corporation

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Hindawi Publishing Corporation
Copyright
Copyright © 2003 Hindawi Publishing Corporation.
ISSN
1110-8657
eISSN
1687-6180
Publisher site
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Abstract

Deborah Estrin Department of Computer Science, University of California, Los Angeles (UCLA), Los Angeles, CA 90095-1596, USA Email: destrin@cs.ucla.edu Yu Hen Hu Department of Electrical and Computer Engineering, University of Wisconsin-Madison, 1415 Engineering Drive, Madison, WI 53706-1691, USA Email: hu@engr.wisc.edu Advances in low-cost and low-power wireless communication, microsensor, and microprocessor hardware, as well as progress in ad hoc networking routing and protocols, distributed signal and array processing, pervasive computing, and embedded systems have all made sensor networking a topic of active interest. In recent years, the Internet has been able to provide a large number of users with the ability to move diverse forms of information readily and thus revolutionized business, industry, defense, science, education, research, and human interactions. Sensor networking may, in the long run, be equally significant by providing measurement of the physical phenomena around us, leading to their understanding and ultimately the utilization of this information for a wide range of applications. Potential applications of sensor networking include environmental monitoring, health care monitoring, battlefield surveillance and reconnaissance, modern highway, modern manufacturing, condition-based maintenance of complex systems, and so forth. In order to understand and build sensor networks, diverse technology and technical disciplines are involved. However, in this special issue we deal only with various signal processing aspects of sensor networking. Of the seven papers, four of them deal with source localization, two of them with tracking, and one with sensor network decomposition and organization. Energy-Based Collaborative Source Localization Using Acoustic Microsensor Array, by D. Li and Y. H. Hu, uses acoustic energy measurements to perform source localization. This approach assumes the acoustic source energy decays inversely with the square of the distance. By comparing acoustic sensor energy measurements around the source, the source location can be estimated as the intersection of multiple hyperspheres. The Fusion of Distributed Microphone Arrays for Sound Localization, by P. Aarabi, also deals with acoustic source localization. The author proposes to use the spatial observability function (SOF), which gives an indication of how well a microphone array perceives events at different spatial position. Each microphone array also has a spatial likelihood function (SLF) which reports the likelihood of a source at each spatial location. SOF and SLF approaches are used together for sound localization. In A Self-Localization Method for Wireless Sensor Networks, by R. L. Moses, D. Krishnamurthy, and R. Patterson, the authors consider the problem of locating and orienting a network of unattended sensors by using a number of known source signals for calibration purposes. The maximum-likelihood (ML) estimation and Cram´ r-Rao Bound (CRB) techniques are used. e Acoustic Source Localization and Beamforming: Theory and Practice, by J. C. Chen, K. Yao, and R. E. Hudson, again uses the ML method for direct localization of wideband acoustical source in the near field and uses the cross bearing of the direction-of-arrivals (DOA) for localization in the far field. For multiple sources, an alternating projection procedure is used. CRB analysis provides various insights for the localization problem. Dynamic Agent Classification and Tracking Using an Ad Hoc Mobile Acoustic Sensor Network, by D. Friedlander, C. Griffin, N. Jacobson, S. Phoha, and R. R. Brooks, presents methods for dynamic distributed signal processing using an ad hoc mobile network of sensors to detect, identify, and track targets. Forming dynamic clusters around events of interest allows for processing multiple events in parallel over different geographic areas along the trajectory of the targets. In Collaborative In-Network Processing for Target Tracking, J. Liu, J. Reich, and F. Zhao consider collaborative signal 320 processing using acoustic-amplitude sensors for target distance estimation and DOA sensors for bearing estimation. The information-driven sensor querying framework selectively activates sensors based on their utility and cost. Issues of distributed processing for tracking and energy efficiency of the network are addressed. Preprocessing in a Tiered Sensor Network for Habitat Monitoring, by H. Wang, D. Estrin, and L. Girod, considers some common principles for task-decomposition and collaboration for tiered sensor networks. The system has a few powerful macronodes in the first tier and many less-powerful nodes in the second tier. Each macronode combines data collected by many micronodes for target classification and localization. Application is made to habitat monitoring and classification and localization of birds. All seven of these papers use simulations and measured data to verify the proposed methods. In the coming years, it is expected that sensor networking will become ever more important both in research and industry and that hardware and software availability will enable significant data collection and field experimentation. Kung Yao received the B.S.E. (Highest Honors), M.A., and Ph.D. degrees in electrical engineering all from Princeton University, Princeton, NJ. He was a NAS-NRC Postdoctoral Research Fellow at the University of California, Berkeley. Presently, he is a Professor in the Electrical Engineering Department at UCLA. In 1969, he was a Visiting Assistant Professor at the Massachusetts Institute of Technology. In 1985–1988, he served as an Assistant Dean of the School of Engineering and Applied Science at UCLA. His research and professional interests include sensor array system, digital communication theory and system, smart antenna and wireless radio system, chaos communications and system theory, digital and array and signal and array processing, systolic and VLSI algorithms, architectures and systems, radar system, and simulation. He has published over 250 journal and conference papers. Dr. Yao received the IEEE Signal Processing Society’s 1993 Senior Award in VLSI Signal Processing. He was the coeditor of a two-volume series of an IEEE Reprint Book on High Performance VLSI Signal Processing, IEEE Press, 1997. In 1991– 1993, he was the Associate Editor of VLSI Signal Processing of the IEEE Trans. on Circuits and Systems. Since 1999, he is an Associate Editor of the IEEE Communications Letters. He is a member of the Editorial Board of the Journal of VLSI Signal Processing and Integration: the VLSI Journal. He was also a Guest Editor of a Special Issue on Applications of Chaos in Modern Communication Systems of the IEEE Trans. on Circuits and Systems—Part I in 2001. He is a Fellow of IEEE. Deborah Estrin is a Professor of computer science at UCLA and Director of the Center for Embedded Networked Sensing (CENS), a newly awarded National Science Foundation Science and Technology Center. She received her Ph.D. degree in computer science from the MIT (1985) and was on the faculty of Computer Science at USC from 1986 through mid-2000, where she received the National Science Foundation, Presidential EURASIP Journal on Applied Signal Processing Young Investigator Award for her research in network interconnection and security (1987). During the subsequent 10 years her research focused on the design of network and routing protocols for very large, global networks. Estrin has been instrumental in defining the national research agenda for wireless sensor networks, first chairing a 1998 DARPA ISAT study and then a 2001 NRC study; the latter culminated in an NRC publication—Embedded Everywhere: A Research Agenda for Networked System of Embedded Computers. Estrin’s research group develops algorithms and systems to support rapidly-deployable and robustly operating networks of many thousands of physically embedded devices. She is particularly interested in applications to environmental monitoring. Estrin has served on numerous program committees and editorial boards, including SIGCOMM, Mobicom, SOSP, and ACM/IEEE Transactions on Networks. She is a Fellow of the ACM and the AAAS. Yu Hen Hu received the B.S.E.E. degree from National Taiwan University, Taiwan, in 1976. He received the M.S. and Ph.D. degrees both in electrical engineering from University of Southern California, Los Angeles, Calif in 1980 and 1982, respectively. Currently, he is a Professor at the Electrical and Computer Engineering Department of the University of Wisconsin-Madison, Wis, USA. Previously, he has been with the Electrical Engineering Department of the Southern Methodist University, Dallas, Tex, USA. Dr. Hu’s research interests include multimedia signal processing, design methodology and implementation of signal processing algorithms and systems, sensor network and distributive signal processing algorithms, and neural network signal processing. He published more than 200 journal and conference papers and edited two books: Programmable Digital Signal Processors and Handbook of Neural Network Signal Processing. Dr. Hu is a Fellow of IEEE. He served as Associate Editor for IEEE Transactions on Signal Processing, IEEE Signal Processing Letters, Journal of VLSI Signal Processing, EURASIP Journal on Applied Signal Processing. He served as Secretary of IEEE signal processing society, board of governors of IEEE neural network council, Chair of IEEE signal processing society, and neural network signal processing technical committee. Photograph © Turisme de Barcelona / J. Trullàs Preliminary call for papers The 2011 European Signal Processing Conference (EUSIPCO 2011) is the nineteenth in a series of conferences promoted by the European Association for Signal Processing (EURASIP, www.eurasip.org). This year edition will take place in Barcelona, capital city of Catalonia (Spain), and will be jointly organized by the Centre Tecnològic de Telecomunicacions de Catalunya (CTTC) and the Universitat Politècnica de Catalunya (UPC). EUSIPCO 2011 will focus on key aspects of signal processing theory and applications as li t d b l li ti listed below. A Acceptance of submissions will b b d on quality, t f b i i ill be based lit relevance and originality. Accepted papers will be published in the EUSIPCO proceedings and presented during the conference. Paper submissions, proposals for tutorials and proposals for special sessions are invited in, but not limited to, the following areas of interest. Organizing Committee Honorary Chair Miguel A. Lagunas (CTTC) General Chair Ana I. Pérez Neira (UPC) General Vice Chair Carles Antón Haro (CTTC) Technical Program Chair Xavier Mestre (CTTC) Technical Program Co Chairs Javier Hernando (UPC) Montserrat Pardàs (UPC) Plenary Talks Ferran Marqués (UPC) Yonina Eldar (Technion) Special Sessions Ignacio Santamaría (Unversidad de Cantabria) Mats Bengtsson (KTH) Finances Montserrat Nájar (UPC) Tutorials Daniel P. Palomar (Hong Kong UST) Beatrice Pesquet Popescu (ENST) Publicity Stephan Pfletschinger (CTTC) Mònica Navarro (CTTC) Publications Antonio Pascual (UPC) Carles Fernández (CTTC) Industrial Liaison & Exhibits I d i l Li i E hibi Angeliki Alexiou (University of Piraeus) Albert Sitjà (CTTC) International Liaison Ju Liu (Shandong University China) Jinhong Yuan (UNSW Australia) Tamas Sziranyi (SZTAKI Hungary) Rich Stern (CMU USA) Ricardo L. de Queiroz (UNB Brazil) Areas of Interest • Audio and electro acoustics. • Design, implementation, and applications of signal processing systems. • Multimedia signal processing and coding. l d l d d • Image and multidimensional signal processing. • Signal detection and estimation. • Sensor array and multi channel signal processing. • Sensor fusion in networked systems. • Signal processing for communications. • Medical imaging and image analysis. • Non stationary, non linear and non Gaussian signal processing. Submissions Procedures to submit a paper and proposals for special sessions and tutorials will be detailed at www.eusipco2011.org. Submitted papers must be camera ready, no more than 5 pages long, and conforming to the standard specified on the EUSIPCO 2011 web site. First authors who are registered students can participate in the best student paper competition. Important Deadlines: Proposals f special sessions P l for i l i Proposals for tutorials Electronic submission of full papers Notification of acceptance Submission of camera ready papers Webpage: www.eusipco2011.org 15 Dec 2010 D 18 Feb 2011 21 Feb 2011 23 May 2011 6 Jun 2011

Journal

EURASIP Journal on Advances in Signal ProcessingHindawi Publishing Corporation

Published: Jan 1, 1900

There are no references for this article.