Approximate Chernoff Fusion of Gaussian Mixtures Using Sigma-Points

Date

2014-07-10

Author

Gunay, Melih
Orguner, Umut
Demirekler, Mübeccel

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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Covariance intersection (CI) is a method used for consistent track fusion with unknown correlations. The well-known generalization of CI to probability density functions is known as Chernoff fusion. In this paper, we propose an approximate approach for the Chernoff fusion of Gaussian mixtures based on a sigma-point approximation of the underlying densities. The resulting general density fusion rule yields a closed form cost function and an analytical fused density for Gaussian mixtures. The proposed method is applied to a simple but illustrative density fusion problem and compared to exact numerical Chernoff fusion.

Subject Keywords

Architectures, Algorithms

URI

https://hdl.handle.net/11511/55154

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Department of Electrical and Electronics Engineering, Conference / Seminar