A Bayesian approach to information fusion for evaluating the measurement uncertainty

@article{Sommer2009ABA,
  title={A Bayesian approach to information fusion for evaluating the measurement uncertainty},
  author={Klaus-Dieter Sommer and Olaf K{\"u}hn and Fernando Puente Le{\'o}n and Bernd R. L. Siebert},
  journal={Robotics and Autonomous Systems},
  year={2009},
  volume={57},
  pages={339-344}
}
The Bayesian approach to uncertainty evaluation is a classical example for information fusion. It is based on both, the knowledge about the measuring process and the input quantities. Appropriate probability density functions for the input quantities may be obtained by utilizing the principle of maximum information entropy and the Bayes theorem. The knowledge about the measurement process is represented by the so-called model equation which forms the basis for the fusion of all involved input… CONTINUE READING

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