Upcoming Webinar: "Distributed Localization and Tracking of Mobile Networks"

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News and Resources for Members of the IEEE Signal Processing Society

Upcoming Webinar: "Distributed Localization and Tracking of Mobile Networks"

Upcoming Webinar -  28 May 2020
Webinar Topic: "Distributed Localization and Tracking of Mobile Networks"

Presented by Dr. Florian Meyer

Based on the IEEE Xplore® article:
"Distributed Localization and Tracking of Mobile Networks Including Noncooperative Objects"
Published in the IEEE Transactions on Signal and Information Processing over Networks, March 2016




Dr. Florian Meyer
28 May 2020
02:00 pm EDT (New York time)
Approximately 1 hour
Attendee Registration

Original article is open access and freely available for download on IEEE Xplore®


Register for the Webinar


The IEEE Signal Processing Society would like to express our concern and support for the members of our global community and all affected by the current COVID-19 pandemic. We appreciate your continued patience and support as we work together to navigate these unforeseen and uncertain circumstances. We hope that you, your families, and your communities are safe!

About this topic:

A new era of pervasive data generation is enabled by emerging sensing modalities and will pose new challenges to signal processing, data science, and robotics. For example, underwater robotic technology enables the development of advanced networks for underwater localization and mapping, and emerging aerial robotic technology enables the development of advanced networks for wide area localization and mapping. Bayesian graph signal processing is a promising approach that can yield innovative signal processing solutions.

Based on this approach, this webinar will propose a method for distributed sequential localization of mobile networks composed of both cooperative agents and noncooperative objects. This method provides a consistent combination of cooperative self-localization and distributed tracking. Multiple mobile agents and objects are localized and tracked using measurements between agents and objects and between agents.

For a distributed operation and low complexity, we combine particle-based belief propagation with a consensus or gossip scheme. High localization accuracy is achieved through a probabilistic information transfer between the self-localization and tracking parts of the underlying factor graph. Simulation results demonstrate significant improvements in both agent self-localization and object localization performance compared to separate cooperative self-localization and distributed tracking.

About the presenter:

Dr. Florian Meyer

Dr. Florian Meyer received the M.Sc. and Ph.D. degrees in electrical engineering from TU Wien, the Vienna University of Technology, Austria, in 2011 and 2015, respectively. 

He is an Assistant Professor in Applied Ocean Sciences with University of California San Diego, La Jolla, CA, jointly between the Scripps Institution of Oceanography and the Electrical and Computer Engineering Department. From 2017 to 2019, he was a Postdoctoral Fellow and Associate with the Laboratory for Information and Decision Systems at the Massachusetts Institute of Technology, Cambridge, MA, and from 2016 to 2017, he was a Research Scientist with the NATO Centre for Maritime Research and Experimentation, La Spezia, Italy.

Dr. Meyer was a keynote speaker at the IEEE Aerospace Conference in 2020. He served on the technical program committees of several IEEE conferences and as a co-chair of the IEEE Workshop on Advances in Network Localization and Navigation at the IEEE International Conference on Communications in 2018, 2019, and 2020. He is an Associate Editor for the ISIF Journal of Advances in Information Fusion and an Erwin Schrödinger Fellow.

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