Distributed signal processing in distributed sensor networks


15:30 - 16:15

EI 1 Petritsch Hörsaal

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Distributed signal processing in distributed sensor networks

Prof. Bernie Mulgrew, Institute for Digital Communications, University of Edinburgh

A personal view of distributed or collaborative signal processing will be provided starting with the definition of fundamental concepts such as consensus, diffusion, accelerated consensus and node specific learning. A motivational example will also be given and a methodology for addressing the bearing estimation problem in a distributed network will be outlined. Finally, recent work on algorithms for multi sensor registration that exploit targets of opportunity in a scalable, distributed manner will be discussed and demonstrated.

Professor Bernard (Bernie) Mulgrew (FIEEE, FREng, FRSE, FIET) received his B.Sc. degree in 1979 from Queen’s University Belfast. After graduation, he worked for 4 years as a Development Engineer in the Radar Systems Department at Ferranti, Edinburgh. From 1983-1986 he was a research associate in the Department of Electrical Engineering at the University of Edinburgh. He was appointed to lectureship in 1986, received his Ph.D. in 1987, promoted to senior lecturer in 1994 and became a reader in 1996. The University of Edinburgh appointed him to a Personal Chair in October 1999 (Professor of Signals and Systems). His research interests are in adaptive signal processing and estimation theory and in their application to radar and sensor systems. Prof. Mulgrew is a co-author of three books on signal processing.