Publication detail

Distributed Bernoulli Filtering Using Likelihood Consensus

PAPA, G. REPP, R. MEYER, F. BRACA, P. HLAWATSCH, F.

Original Title

Distributed Bernoulli Filtering Using Likelihood Consensus

Type

journal article in Web of Science

Language

English

Original Abstract

We consider the detection and tracking of a target in a decentralized sensor network. The presence of the target is uncertain, and the sensor measurements are affected by clutter and missed detections. The state-evolution model and the measurement model may be nonlinear and non-Gaussian. For this practically relevant scenario, we propose a particle-based distributed Bernoulli filter (BF) that provides to each sensor approximations of the Bayes-optimal estimates of the target presence probability and the target state. The proposed method uses all the measurements in the network while requiring only local intersensor communication. This is enabled by an extension of the likelihood consensus method that reaches consensus on the likelihood function under both the target presence and target absence hypotheses. We also propose an adaptive pruning of the likelihood expansion coefficients that yields a significant reduction of intersensor communication. Finally, we present a new variant of the likelihood consensus method that is suited to networks containing star-connected sensor groups. Simulation results show that in challenging scenarios, including a heterogeneous sensor network with significant noise and clutter, the performance of the proposed distributed BF approaches that of the optimal centralized multisensor BE We also demonstrate that the proposed distributed BF outperforms a state-of-the-art distributed BF at the expense of a higher amount of intersensor communication.

Keywords

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

Authors

PAPA, G.; REPP, R.; MEYER, F.; BRACA, P.; HLAWATSCH, F.

Released

17. 12. 2018

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC

Location

PISCATAWAY

ISBN

2373-776X

Periodical

IEEE Transactions on Signal and Information Processing over Networks

Year of study

5

Number

2

State

United States of America

Pages from

218

Pages to

233

Pages count

16

URL

https://ieeexplore.ieee.org/document/8579567

BibTex

@article{BUT170645,
  author="PAPA, G. and REPP, R. and MEYER, F. and BRACA, P. and HLAWATSCH, F.",
  title="Distributed Bernoulli Filtering Using Likelihood Consensus",
  journal="IEEE Transactions on Signal and Information Processing over Networks",
  year="2018",
  volume="5",
  number="2",
  pages="218--233",
  doi="10.1109/TSIPN.2018.2881718",
  issn="2373-776X",
  url="https://ieeexplore.ieee.org/document/8579567"
}