A tutorial introduction to Kalman filtering

Presents an elementary introduction to Kalman Filtering starting from the simplest of all estimation problems, namely that of estimating a time independent scalar quantity from a number of noisy measurements. From this the author moves on to consider the case when the quantity to be estimated is a function of time, and then generalises the results to the estimation of a time dependent vector. Finally he indicates how the resulting Kalman Filter equations can be applied to an elementary but nevertheless real problem in navigation.<>