Multisensor statistical interval estimation fusion

Yunmin Zhu; Gan Yu; X. Rong Li

doi:10.1117/12.458392

6 March 2002 Multisensor statistical interval estimation fusion

Yunmin Zhu, Gan Yu, X. Rong Li

Author Affiliations +

Proceedings Volume 4731, Sensor Fusion: Architectures, Algorithms, and Applications VI; (2002) https://doi.org/10.1117/12.458392
Event: AeroSense 2002, 2002, Orlando, FL, United States

Abstract

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.

Citation Download Citation

Yunmin Zhu, Gan Yu, and X. Rong Li "Multisensor statistical interval estimation fusion", Proc. SPIE 4731, Sensor Fusion: Architectures, Algorithms, and Applications VI, (6 March 2002); https://doi.org/10.1117/12.458392

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