Publication detail

A Distributed Bernoulli Filter Based on Likelihood Consensus with Adaptive Pruning

REPP, R. GIUSEPPE, P. MEYER, F. BRACA, P. HLAWATSCH, F.

Original Title

A Distributed Bernoulli Filter Based on Likelihood Consensus with Adaptive Pruning

Type

conference paper

Language

English

Original Abstract

The Bernoulli filter (BF) is a Bayes-optimal method for target tracking when the target can be present or absent in unknown time intervals and the measurements are affected by clutter and missed detections. We propose a distributed particle-based multisensor BF algorithm that approximates the centralized multisensor BF for arbitrary nonlinear and non-Gaussian system models. Our distributed algorithm uses a new extension of the likelihood consensus (LC) scheme that accounts for both target presence and absence and includes an adaptive pruning of the LC expansion coefficients. Simulation results for a heterogeneous sensor network with significant noise and clutter show that the performance of our algorithm is close to that of the centralized multisensor BF.

Keywords

Bernoulli filter; distributed target tracking; distributed particle filtering; likelihood consensus; random finite set; sensor network

Authors

REPP, R.; GIUSEPPE, P.; MEYER, F.; BRACA, P.; HLAWATSCH, F.

Released

6. 9. 2018

Publisher

IEEE

Location

NEW YORK

ISBN

978-0-9964527-6-2

Book

2018 21st International Conference on Information Fusion (FUSION)

Pages from

2445

Pages to

2452

Pages count

8

URL

https://ieeexplore.ieee.org/document/8455302

BibTex

@inproceedings{BUT170646,
  author="REPP, R. and GIUSEPPE, P. and MEYER, F. and BRACA, P. and HLAWATSCH, F.",
  title="A Distributed Bernoulli Filter Based on Likelihood Consensus with Adaptive Pruning",
  booktitle="2018 21st International Conference on Information Fusion (FUSION)",
  year="2018",
  pages="2445--2452",
  publisher="IEEE",
  address="NEW YORK",
  isbn="978-0-9964527-6-2",
  url="https://ieeexplore.ieee.org/document/8455302"
}