20 March 1998 Maximum-likelihood approach for multisensor data fusion applications
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Abstract
In this paper, we proposed a maximum likelihood fusion approach for multisensor fusion applications. The proposed approach was based on a parametric modeling of the noise covariance and formulated in the transformed noise subspace. It could solve the fusion problems when the sensor noises are correlated and the scaling coefficients unknown. The approach could also deal with nonstationary signals. We showed that in the optimization process, the computation of the noise parameters and the scaling coefficients were separable leading to a reduced optimization dimensionality and computational complexity. Computer simulations were used to demonstrate the effectiveness of the proposed fusion approach.
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Yifeng Zhou, Yifeng Zhou, Henry Leung, Henry Leung, } "Maximum-likelihood approach for multisensor data fusion applications", Proc. SPIE 3376, Sensor Fusion: Architectures, Algorithms, and Applications II, (20 March 1998); doi: 10.1117/12.303678; https://doi.org/10.1117/12.303678
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