ABSTRACT
Integrated aircraft navigation systems are concerned with combining data from various navigational sensors to arrive at a refined estimate of the position, velocity and other kinematic parameters of one or more air vehicles, along with error bounds for these estimates. The most frequent problem is one of filtering, i.e. estimating the state of a system at a given time based on observational data up to that time, although problems of prediction and smoothing also arise. Consequently, since the 1970s the field has become one of the classic areas of application of Kalman filters and kindred linear smoothing techniques.
