Creator:

Ajgl, Jiři ; Straka, Ondřej

Contributor:

Korbicz, Józef (1951- ) - red. ; Uciński, Dariusz - red.

Title:

Fusion of multiple estimates by covariance intersection: Why and how it is suboptimal

Subject and Keywords:

decentralised estimation ; fusion under unknown correlations ; covariance intersection ; Minkowski sum

Abstract:

The fusion under unknown correlations tunes a combination of local estimates in such a way that upper bounds of the admissible mean square error matrices are optimised. Based on the recently discovered relation between the admissible matrices and Minkowski sums of ellipsoids, the optimality of existing algorithms is analysed. Simple examples are used to indicate the reasons for the suboptimality of the covariance intersection fusion of multiple estimates. Further, an extension of the existing family of upper bounds is proposed, which makes it possible to get closer to the optimum, and a general case is discussed. All results are obtained analytically and illustrated graphically.

Publisher:

Zielona Góra: Uniwersytet Zielonogórski

Date:

2018

Resource Type:

artykuł

DOI:

10.2478/amcs-2018-0040

Pages:

521-530

Source:

AMCS, volume 28, number 3 (2018) ; click here to follow the link

Language:

eng

License CC BY 4.0:

click here to follow the link

Rights:

Biblioteka Uniwersytetu Zielonogórskiego