The Kalman Filter is one of the most important and common estimation algorithms that is an iterative technique of dynamic linear modelling, used mainly for estimating the parameters. The Kalman Filter produces estimates of hidden variables based on inaccurate and uncertain measurements, also provides a prediction of the future system state based on past estimations. The filter is named after Rudolf E. Kálmán (May 19, 1930 – July 2, 2016).
Reference Definition by Wikipedia: Kalman Filtering, also known as linear quadratic estimation (LQE), is an algorithm that uses a series of measurements observed over time, containing statistical noise and other inaccuracies, and produces estimates of unknown variables that tend to be more accurate than those based on a single measurement alone, by estimating a joint probability distribution over the variables for each timeframe. The filter is named after Rudolf E. Kálmán, one of the primary developers of its theory.
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