Linearly constrained least squares approach for multisensor data fusion

Yifeng Zhou; Henry Leung

doi:10.1117/12.276122

16 June 1997 Linearly constrained least squares approach for multisensor data fusion

Yifeng Zhou, Henry Leung

Proceedings Volume 3067, Sensor Fusion: Architectures, Algorithms, and Applications; (1997) https://doi.org/10.1117/12.276122
Event: AeroSense '97, 1997, Orlando, FL, United States

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.

Citation Download Citation

Yifeng Zhou and Henry Leung "Linearly constrained least squares approach for multisensor data fusion", Proc. SPIE 3067, Sensor Fusion: Architectures, Algorithms, and Applications, (16 June 1997); https://doi.org/10.1117/12.276122

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