Optimal centralized state fusion estimation for multi-sensor system with correlated measurement noise

Author

Xue-bo, Jin ; You-xian, Sun

Author_Institution

Coll. of Inf. & Electron., Zhejiang Inst. of Sci. & Technol., Hangzhou, China

Volume

1

fYear

2003

fDate

23-25 June 2003

Firstpage

770

Abstract

Many centralized fusion estimation algorithms assumed that measurement noises among sensors are uncorrelated, but it is not true when there exist the same unmodeled measurement noise source. In this paper, based on the matrix similarity transform, covariance matrix of correlated measurement noise is successfully parallel decomposed and the linear measurement models are transformed. Optimal centralized fusion estimation algorithm is presented. When measurement noises are uncorrelated, the results here are reduced to the standard optimal centralized fusion estimation algorithms.

Keywords

covariance matrices; discrete time systems; estimation theory; noise; sensor fusion; state estimation; centralized state fusion estimation; covariance matrix; discrete system; estimation algorithm; linear measurement models; linear time-invariant system; matrix similarity transform; measurement noise; multisensor system; Covariance matrix; Matrix decomposition; Measurement standards; Noise measurement; Sensor fusion; Sensor systems; State estimation; Sun; Telephony; White noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Applications, 2003. CCA 2003. Proceedings of 2003 IEEE Conference on

Print_ISBN

0-7803-7729-X

Type

conf

DOI

10.1109/CCA.2003.1223535

Filename

1223535