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Data Fusion
- 📜 A New Approach to Linear Filtering and Prediction Problems by R. E. Kalman
The Kalman Filter is a prediction-correction algorithm named after Rudolf E. Kálmán (1930-2016), by which we calculate recursively a dynamical system state at time t_{k} using state at previous time u_{k-1} and new information b_{k} only. This technique is presented as a generalization of the least squares model for problems with varying mean and additive noise.
The Kalman Filter was first applied to the problem of trajectory estimation for the NASA Apollo space program (in the 1960s) and incorporated in the Apollo space navigation computer. It is also used in the guidance and navigation systems of the NASA Space Shuttle and the attitude control and navigation systems of the International Space Station. In other words, it is mostly used for positioning and navigation systems, but it can be generalized to any time series under suitable conditions. —@eramirem