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Proceedings Paper

Linearly constrained least squares approach for multisensor data fusion
Author(s): Yifeng Zhou; Henry Leung
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Paper Abstract

In this paper, we present a linearly constrained least squares (LCLS) algorithm for multisensor data fusion. While fusion is considered in the scope of linear combination, the objective of the LCLS algorithm is to minimize the energy of the linearly fused information based on empirical sensory information. Statistical performance analysis of the LCLS algorithm will be carried out including the consistency and asymptotic covariance of the estimates. Effectiveness of the proposed fusion algorithm will be evaluated numerically based on fusion of signals and images.

Paper Details

Date Published: 16 June 1997
PDF: 12 pages
Proc. SPIE 3067, Sensor Fusion: Architectures, Algorithms, and Applications, (16 June 1997); doi: 10.1117/12.276122
Show Author Affiliations
Yifeng Zhou, Telexis Corp. Canada (Canada)
Henry Leung, Defence Research Establishment Ottawa (Canada)

Published in SPIE Proceedings Vol. 3067:
Sensor Fusion: Architectures, Algorithms, and Applications
Belur V. Dasarathy, Editor(s)

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