Talks and Poster Presentations (with Proceedings-Entry):

F. Meyer, E. Riegler, O. Hlinka, F. Hlawatsch:
"Simultaneous Distributed Sensor Self-Localization and Target Tracking Using Belief Propagation and Likelihood Consensus";
Talk: Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA; 11-04-2012 - 11-07-2012; in: "Asilomar 2012", (2012), 5 pages.

English abstract:
We introduce the framework of cooperative simultaneous localization and tracking (CoSLAT), which provides a consistent combination of cooperative self-localization (CSL) and distributed target tracking (DTT) in sensor networks without a fusion center. CoSLAT extends simultaneous localization and tracking (SLAT) in that it uses also intersensor measurements. Starting from a factor graph formulation of the CoSLAT problem, we develop a particle-based, distributed message passing algorithm for CoSLAT that combines nonparametric belief propagation with the likelihood consensus scheme. The proposed CoSLAT algorithm improves on state-of-the-art CSL and DTT algorithms by exchanging probabilistic information between CSL and DTT. Simulation results demonstrate substantial improvements in both self-localization and tracking performance.

Distributed target tracking, cooperative localization, CoSLAT, nonparametric belief propagation, likelihood consensus.

Electronic version of the publication:

Created from the Publication Database of the Vienna University of Technology.