Title: A Study of Fusions of Multiple Estimates for Limit Cases
Authors: Ajgl, Jiří
Straka, Ondřej
Citation: AJGL, J. STRAKA, O. A Study of Fusions of Multiple Estimates for Limit Cases. In Proceedings of the IEEE International Conference on Multisensor Fusion and Integration (MFI 2022). Cranfield, Spojené království: IEEE, 2022. s. 1-6. ISBN: 978-1-66546-026-2 , ISSN: neuvedeno
Issue Date: 2022
Publisher: IEEE
Document type: konferenční příspěvek
ConferenceObject
URI: 2-s2.0-85140982923
http://hdl.handle.net/11025/51445
ISBN: 978-1-66546-026-2
ISSN: neuvedeno
Keywords in different language: Estimation fusion;multiple estimates;unknown correlation;Covariance Intersection
Abstract in different language: Decentralised estimation often sacrifices optimality for solution simplicity, while within the fusion under unknown correlation, a worst-case type of optimality is adopted. This paper studies the gap between the simple solution and the optimal one for special cases. Namely, symmetric configurations are considered for infinite number of estimates and also for infinite dimension of the state to be estimated. In these academic cases, the optimal solution is better than the simple one by low tens percent, if the size of circumscribing balls is considered. In practice, much lower gap can be expected.
Rights: Plný text je přístupný v rámci univerzity přihlášeným uživatelům.
© IEEE
Appears in Collections:Konferenční příspěvky / Conference papers (NTIS)
Konferenční příspěvky / Conference Papers (KKY)
OBD

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