Publication result 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

English Title

A Distributed Bernoulli Filter Based on Likelihood Consensus with Adaptive Pruning

Type

Paper in proceedings (conference paper)

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.

English 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

Key words in English

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.

RIV year

2021

Released

06.09.2018

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"
}