DocumentCode
1845734
Title
Multi-scale fusion and estimation for multi-resolution sensors
Author
Yuemin Li ; Renbiao Wu ; Tao Zhang
Author_Institution
Tianjin Key Lab. for Adv. Signal Process., Civil Aviation Univ. of China, Tianjin, China
Volume
1
fYear
2012
fDate
21-25 Oct. 2012
Firstpage
193
Lastpage
197
Abstract
On the basis of theory for Discrete Wavelet Transform (DWT) of signal statistical characteristics and Dynamic Multi-scale System (DMS) of the state transition model, a novel algorithm for multi-scale fusion and estimation with multi-resolution sensors is derived. In order to construct a uniform resolution model of Kalman Filter, the equations of state and measurement are processed with DWT at different resolution levels, and then the measurements of the same resolution level are fused and filtered. Experimental results indicate that the proposed method is more effective than other existing algorithms.
Keywords
discrete wavelet transforms; estimation theory; sensor fusion; signal processing; DMS; DWT; Kalman Filter; discrete wavelet transform; dynamic multiscale system; multiresolution sensors; multiscale estimation; multiscale fusion; signal statistical characteristics; state transition model; Kalman filter; discrete wavelet transform; dynamic multi-scale system; fusion and estimation;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing (ICSP), 2012 IEEE 11th International Conference on
Conference_Location
Beijing
ISSN
2164-5221
Print_ISBN
978-1-4673-2196-9
Type
conf
DOI
10.1109/ICoSP.2012.6491633
Filename
6491633
Link To Document