KIT | KIT-Bibliothek | Impressum | Datenschutz

Fully Decentralized Estimation Using Square-Root Decompositions

Radtke, Susanne; Noack, Benjamin; Hanebeck, Uwe D.


Networks consisting of several spatially distributed sensor nodes are useful in many applications. While distributed information processing can be more robust and flexible than centralized filtering, it requires careful consideration of dependencies between local state estimates.
This paper proposes an algorithm to keep track of dependencies in decentralized systems where no dedicated fusion center is present. Specifically, it addresses double-counting of measurement information due to intermediate fusion results and correlations due to common process noise and common prior information. To limit the necessary amount of data, this paper introduces a method to partially bound correlations, leading to a more conservative fusion result than the optimal reconstruction while reducing the necessary amount of data. Simulation studies compare the performance and convergence rate of the proposed algorithm to other state-of-the-art methods.

Postprint §
DOI: 10.5445/IR/1000136453
Veröffentlicht am 02.06.2022
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Anthropomatik und Robotik (IAR)
Publikationstyp Zeitschriftenaufsatz
Publikationsdatum 01.06.2021
Sprache Englisch
Identifikator ISSN: 1557-6418
KITopen-ID: 1000136453
Erschienen in Journal of Advances in Information Fusion
Band 16
Heft 1
Seiten 3-16
Externe Relationen Abstract/Volltext
KIT – Die Forschungsuniversität in der Helmholtz-Gemeinschaft
KITopen Landing Page