Optimal sensor dimension reduction in estimation fusion

Enbin Song; Yunmin Zhu; Jie Zhou

doi:10.1117/12.601969

28 March 2005 Optimal sensor dimension reduction in estimation fusion

Enbin Song, Yunmin Zhu, Jie Zhou

Proceedings Volume 5813, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2005; (2005) https://doi.org/10.1117/12.601969
Event: Defense and Security, 2005, Orlando, Florida, United States

Abstract

When there exists the limitation of communication bandwidth between sensors and a fusion center, one needs to optimally pre-compress sensor outputs--sensor observations or estimates before sensors' transmission to obtain a constrained optimal estimation at the fusion center in terms of the linear minimum error variance criterion. This paper will give an analytic solution of the optimal linear dimensionality compression matrix for the single sensor case and analyze the existence of the optimal linear dimensionality compression matrix for the multisensor case, as well as how to implement a Gauss-Seidel algorithm to search for an optimal solution to linear dimensionality compression matrix.

Citation Download Citation

Enbin Song, Yunmin Zhu, and Jie Zhou "Optimal sensor dimension reduction in estimation fusion", Proc. SPIE 5813, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2005, (28 March 2005); https://doi.org/10.1117/12.601969

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