Application to the Kalman Filter
Paul-André Monney · Contributions to statistics · 2003
One of the most important result in estimation theory in the last forty years is the Kaiman filter for discrete dynamical systems [23]. Beside its theoretical appeal, this result has drawn considerable attention from practitioners and it has lead to an amazing number of applications, like, among others, marine navigation systems [3], space flight navigation, e.g. the Apollo missions to the moon [6], and telephone load forecasting [50]. The Kaiman filter is typically derived from the dynamic model by using the minimum variance principle [8], or by applying Bayes rule [4], or by assuming a special form of the estimation function [5].