Distributed Monte Carlo information fusion and distributed particle filtering
- Publication Type:
- Conference Proceeding
- IFAC Proceedings Volumes (IFAC-PapersOnline), 2014, 19 pp. 8681 - 8688
- Issue Date:
Copyright Clearance Process
- Recently Added
- In Progress
- Closed Access
This item is closed access and not available.
© IFAC. We present a Monte Carlo solution to the distributed data fusion problem and apply it to distributed particle filtering. The consensus-based fusion algorithm is iterative and it involves the exchange and fusion of empirical posterior densities between neighbouring agents. As the fusion method is Monte Carlo based it is naturally applicable to distributed particle filtering. Furthermore, the fusion method is applicable to a large class of networks including networks with cycles and dynamic topologies. We demonstrate both distributed fusion and distributed particle filtering by simulating the algorithms on randomly generated graphs.
Please use this identifier to cite or link to this item: