Distributed Monte Carlo information fusion and distributed particle filtering
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...[Show more]
|Collections||ANU Research Publications|
|Source:||Proceedings of the 19th IFAC World Congress, 2014|
|01_Manuel_Distributed_Monte_Carlo_2014.pdf||1.23 MB||Adobe PDF||Request a copy|
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