Node Localization in Wireless Sensor Networks / Synthesis Lectures on Communications (PDF)
(Sprache: Englisch)
In sensor network applications, measured data are often meaningful only when the location is accurately known. In this booklet, we study research problems associated with node localization in wireless sensor networks. We describe sensor network localization...
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In sensor network applications, measured data are often meaningful only when the location is accurately known. In this booklet, we study research problems associated with node localization in wireless sensor networks. We describe sensor network localization problems in terms of a detection and estimation framework and we emphasize specifically a cooperative process where sensors with known locations are used to localize nodes at unknown locations. In this class of problems, even if the location of a node is known, the wireless links and transmission modalities between two nodes may be unknown. In this case, sensor nodes are used to detect the location and estimate pertinent data transmission activities between nodes. In addition to the broader problem of sensor localization, this booklet studies also specific localization measurements such as time of arrival (TOA), received signal strength (RSS), and direction of arrival (DOA). The sequential localization algorithm, which uses a subset of sensor nodes to estimate nearby sensor nodes' locations is discussed in detail. Extensive bibliography is given for those readers who want to delve further into specific topics.
Autoren-Porträt von Xue Zhang, Cihan Tepedelenlioglu, Mahesh Banavar, Andreas Spanias
Xue Zhang is a Senior System Engineer at Intel Corporation in Santa Clara, CA. She received her B.S. degree from Xi'an Shiyou University in 2008, her M.S. degree from California State University Fullerton in 2010, and her Ph.D. degree from Arizona State University in 2016, all in Electrical Engineering. Her research interests include Digital Signal Processing and Communications. Specifically, she is interested in localization in wireless sensor networks.Cihan Tepedelenlioglu was born in Ankara, Turkey in 1973. He received his B.S. degree with highest honors from Florida Institute of Technology in 1995, and his M.S. degree from the University of Virginia in 1998, both in electrical engineering. From January 1999 to May 2001 he was a research assistant at the University of Minnesota, where he completed his Ph.D. degree in Electrical and Computer Engineering. He is currently an associate professor of electrical engineering at Arizona State University. He was awarded the NSF (early) Career grant in 2001, and has served as an associate editor for several IEEE Transactions including IEEE Transactions on Communications, IEEE Signal Processing Letters, IEEE Transactions on Wireless Communications, and IEEE Transactions on Vehicular Technology. His research interests include statistical signal processing, system identification, wireless communications, estimation and equalization algorithms for wireless systems, multi-antenna communications, OFDM, ultra-wideband systems, distributed detection and estimation, and data mining for PV systems.Mahesh Banavar is an assistant professor in the Department of Electrical and Computer Engineering at Clarkson University. He received a B.E. degree in telecommunications engineering from Visvesvaraya Technological University, Karnataka, India in 2005, an M.S. degree and a Ph.D. degree, both in electrical engineering, from Arizona State University in 2007 and 2010, respectively. His research area is signal processing and communications, and
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he is specifically working on wireless communications and sensor networks. He is a member of MENSA and the Eta Kappa Nu honor society.Andreas Spanias is a Professor in the School of Electrical, Computer, and Energy Engineering at Arizona State University. He is also the director of the Sensor Signal and Information Processing (SenSIP) center and the founder of the SenSIP industry consortium (now an NSF I/UCRC site). His research interests are in the areas of adaptive signal processing, speech processing, and sensor systems. He and his student team developed the computer simulation software Java-DSP and its award winning iPhone/iPad and Android versions. He is the author of two textbooks: Audio Processing and Coding by Wiley and DSP and An Interactive Approach (2nd ed.). He served as associate editor of the IEEE Transactions on Signal Processing and as General Co-chair of IEEE ICASSP-99. He also served as the IEEE Signal Processing Vice-President for Conferences. Andreas Spanias is co-recipient of the 2002 IEEE Donald G. Fink paper prize award and was elected Fellow of the IEEE in 2003. He served as distinguished lecturer for the IEEE Signal Processing Society in 2004. He is a series editor for the Morgan & Claypool lecture series on algorithms and software.
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Bibliographische Angaben
- Autoren: Xue Zhang , Cihan Tepedelenlioglu , Mahesh Banavar , Andreas Spanias
- 2022, 1. Auflage, 50 Seiten, Englisch
- Verlag: Springer International Publishing
- ISBN-10: 3031016831
- ISBN-13: 9783031016837
- Erscheinungsdatum: 01.06.2022
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