DocumentCode
2327929
Title
Nonlinear Fusion of Multiple Sensors with Missing Data
Author
Housfater, Alon Shalev ; Zhang, Xiao-Ping ; Zhou, Yifeng
Author_Institution
Dept. of Electr. & Comput. Eng., Ryerson Univ., Toronto, Ont.
Volume
4
fYear
2006
fDate
14-19 May 2006
Abstract
We introduce a new algorithm, multiple imputation particle filter, to solve the problem of data fusion with missing data in nonlinear state space models. The new algorithm is then applied to the problem of fusing observations by multiple asynchronous radars. Simulated data is used demonstrate the effectiveness and performance of the fusing algorithm
Keywords
particle filtering (numerical methods); radar signal processing; sensor fusion; data fusion; multiple asynchronous radars; multiple imputation particle filter; multiple sensors; nonlinear fusion; nonlinear state space models; Data engineering; Electronic mail; Filtering; Nonlinear systems; Particle filters; Radar; Research and development; Sensor fusion; Signal processing algorithms; State-space methods;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on
Conference_Location
Toulouse
ISSN
1520-6149
Print_ISBN
1-4244-0469-X
Type
conf
DOI
10.1109/ICASSP.2006.1661130
Filename
1661130
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