DocumentCode :
2891576
Title :
A New Sequential Weighed Fusion Method with Colored Noise and Time Delay
Author :
Xu, Xiao-liang ; Tang, Jing-Fan
Author_Institution :
Coll. of Comput. Sci. & Technol., Hangzhou Dianzi Univ.
fYear :
2006
fDate :
13-16 Aug. 2006
Firstpage :
1879
Lastpage :
1884
Abstract :
Considering existing questions of the traditional synchronous fusion algorithms, e.g. assumptions of white noise and non-transmission delay produced by the influences of weather, humidity, magnetic field and communication line etc., the paper proposes an improved sequential weighted fusion algorithm, which cannot only deal with colored noise but also adapt automatically the case with network-induced delay which is less than a sampling period. Performance analysis shows that proposed method has more advantages than traditional synchronous fusion methods and simulation example indicates that the two kinds of methods have uniform estimate accuracy to object state
Keywords :
Kalman filters; estimation theory; noise; sensor fusion; signal sampling; Kalman filtering; colored noise; data fusion; network-induced delay; object state; sampling period; sequential weighted fusion algorithm; synchronous fusion algorithm; time delay; transmission delay; uniform estimate accuracy; Colored noise; Cybernetics; Delay effects; Filtering; Humidity; Machine learning; Magnetic sensors; Noise measurement; Sensor fusion; State estimation; Time measurement; White noise; Data fusion; Kalman filtering; colored noise; sequential weighted; transmission delay;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2006 International Conference on
Conference_Location :
Dalian, China
Print_ISBN :
1-4244-0061-9
Type :
conf
DOI :
10.1109/ICMLC.2006.259055
Filename :
4028372
Link To Document :
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