Accession Number:

AD1042335

Title:

Distributed Monte Carlo Information Fusion and Distributed Particle Filtering

Descriptive Note:

Conference Paper

Corporate Author:

AUSTRALIAN NATIONAL UNIV CANBERRA CANBERRA

Personal Author(s):

Report Date:

2014-08-24

Pagination or Media Count:

8.0

Abstract:

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 particlefiltering. 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

Subject Categories:

  • Information Science
  • Statistics and Probability
  • Operations Research

Distribution Statement:

APPROVED FOR PUBLIC RELEASE