Abstract
The Kalman Filter developed in the early sixties by R.E. Kalman [57, 58] is a recursive state estimator for partially observed non-stationary stochastic processes. It gives an optimal estimate in the least squares sense of the actual value of a state vector from noisy observations.
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Andrade-Cetto, J., Sanfeliu, A. A The Kalman Filter. In: Environment Learning for Indoor Mobile Robots. Springer Tracts in Advanced Robotics, vol 23. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11418382_6
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DOI: https://doi.org/10.1007/11418382_6
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