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 :
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