Talks and Poster Presentations (with Proceedings-Entry):
O. Sluciak, O. Hlinka, M. Rupp, F. Hlawatsch, P. Djuric:
"Sequential Likelihood Consensus and Its Application to Distributed Particle Filtering with Reduced Communications and Latency";
Talk: Asilomar Conference on Signals, Systems, and Computers,
Pacific Grove, CA, USA (invited);
- 11-09-2011; in: "Proc. 45th Asilomar Conf. Signals, Systems, Computers",
We propose a sequential likelihood consensus (SLC) for a distributed, sequential computation of the joint (all-sensors) likelihood function (JLF) in a wireless sensor network. The SLC is based on a novel dynamic consensus algorithm, of which only a single iteration is performed per time step. We demonstrate the application of the SLC in a distributed particle filter with low communication requirements and low latency. Because the JLF is available at each sensor, the local particle filters at the individual sensors take into account the measurements of all sensors. The performance of the proposed distributed particle filter is assessed for a target tracking problem.
Likelihood consensus, distributed particle filter, distributed estimation, target tracking, wireless sensor network
Electronic version of the publication:
Project Head Franz Hlawatsch:
Signal and Information Processing in Science and Engineering - Statistische Inferenz
Project Head Markus Rupp:
Signal and Information Processing in Science and Engineering - Entwicklungsmethodik
Created from the Publication Database of the Vienna University of Technology.