Scalable distributed Kalman filtering through consensus

Shrut Kirti, Anna Scaglione

Research output: Chapter in Book/Report/Conference proceedingConference contribution

18 Scopus citations

Abstract

Kalman filtering is a classical technique with a number of potential distributed applications in sensor networks. In this paper we consider a specific algorithm for distributed Kalman filtering proposed recently by Olfati-Saber [1]. We design a communication access protocol for wireless sensor networks that is tailored to converge rapidly to the desired estimate and provides scalable error performance as number of sensors increases. By exploiting the structure of the distributed filtering computations, we derive an optimal communication resource allocation policy for minimizing the component-wise state estimation error. We provide simulation results demonstrating the performance of our architecture.

Original languageEnglish (US)
Title of host publication2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
Pages2725-2728
Number of pages4
DOIs
StatePublished - Sep 16 2008
Externally publishedYes
Event2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP - Las Vegas, NV, United States
Duration: Mar 31 2008Apr 4 2008

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
CountryUnited States
CityLas Vegas, NV
Period3/31/084/4/08

Keywords

  • Average consensus
  • Distributed algorithms
  • Kalman filtering

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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    Kirti, S., & Scaglione, A. (2008). Scalable distributed Kalman filtering through consensus. In 2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP (pp. 2725-2728). [4518212] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). https://doi.org/10.1109/ICASSP.2008.4518212