A New Multiscale Associated Filter with multisensors for Dynamic Systems

Author

Wen, C.L. ; Wen, C.B. ; Chen, Z.G.

Author_Institution

Coll. of Autom., Hangzhou Dianzi Univ.

Volume

1

fYear

2006

fDate

4-6 Oct. 2006

Firstpage

124

Lastpage

131

Abstract

This paper proposes a new multiscale associated filter, named as the multiscale sequential block Kalman filter (MSBKF). It processes a dynamic system with multisensor of different sampling rate. By combing the wavelet transform and Kalman filtering, the MSBKF is real time, recursive, optimal and has the capability of the multiscale analysis; thus, it overcomes the shortcomings of the existing hybrid wavelet-Kalman filters. New blocked state and measurement systems are presented and reformulated in the multiscale domain by the q-band orthogonal wavelet transformation. New filters are compared with the conventional point Kalman filter via theoretical and numerical analyses

Keywords

Kalman filters; sensor fusion; signal sampling; wavelet transforms; blocked state system; dynamic system; measurement system; multiscale analysis; multiscale associated filter; multiscale sequential block Kalman filter; multisensors; q-band orthogonal wavelet transformation; sampling rate; wavelet transform; Educational institutions; Filtering; Frequency domain analysis; Helium; Kalman filters; Signal analysis; State estimation; Wavelet analysis; Wavelet coefficients; Wavelet domain; Kalman filtering; Multiscale analysis; Wavelet transformation;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Engineering in Systems Applications, IMACS Multiconference on

Conference_Location

Beijing

Print_ISBN

7-302-13922-9

Electronic_ISBN

7-900718-14-1

Type

conf

DOI

10.1109/CESA.2006.4281637

Filename

4281637