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Proceedings Paper

Novel estimated algorithm for information fusion on MMW/IR dual-mode combined seeker
Author(s): ZhiShe Cui; Tao Zeng; Teng Long
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Paper Abstract

Based on nonstationary random process with variance stationary and mean value with trend, a adaptive weighted fusion estimated algorithm is presented to fuse MMW/IR Combined seeker data in this paper. The nonstationary random process is transformed to the stationary random process by first difference, which is used for estimating measured data variance. Finally, observations are fused through the weighed fusion estimation algorithm. Simulation indicate that this algorithm is simpler, practical and its convergence speed is faster.

Paper Details

Date Published: 18 September 2001
PDF: 5 pages
Proc. SPIE 4556, Data Mining and Applications, (18 September 2001); doi: 10.1117/12.440304
Show Author Affiliations
ZhiShe Cui, Beijing Institute of Technology (China)
Tao Zeng, Beijing Institute of Technology (China)
Teng Long, Beijing Institute of Technology (China)

Published in SPIE Proceedings Vol. 4556:
Data Mining and Applications

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