6 March 2002 Multisensor statistical interval estimation fusion
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Proceedings Volume 4731, Sensor Fusion: Architectures, Algorithms, and Applications VI; (2002); doi: 10.1117/12.458392
Event: AeroSense 2002, 2002, Orlando, FL, United States
This paper deals with multisensor statistical interval interval estimation fusion, that is, data fusion from multiple statistical interval estimators for the purpose of estimation of a parameter (theta) . A multisensor convex linear statistic fusion model for optimal interval estimation fusion is established. A Gaussian-Seidel iteration algorithm for searching for the fusion weights is proposed. In particular, we suggest convex combination minimum variance fusion that reduces huge computation of fusion weights and yields near optimal estimate performance generally, and moreover, may achieve exactly optimal performance for some specific distributions of observation data. Numerical examples are provided and give additional support to the above results.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yunmin Zhu, Gan Yu, X. Rong Li, "Multisensor statistical interval estimation fusion", Proc. SPIE 4731, Sensor Fusion: Architectures, Algorithms, and Applications VI, (6 March 2002); doi: 10.1117/12.458392; https://doi.org/10.1117/12.458392


Statistical analysis

Data fusion

Data analysis

Sensor fusion

Chemical elements

Distributed computing

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