An optimal recursive Bayesian filter that estimates the state of a linear dynamic system from a series of noisy measurements. It minimizes the mean squared error of the estimated state by combining a model-based prediction step with a measurement update step, weighting each by their respective uncertainty covariances to yield the minimum-variance unbiased estimate.