Application of Kalman filter to oversampled data from global position system for flight path reconstruction

Many applications exist that exploit Global Positioning System (GPS) as a source of position and velocity data. A main problem of the GPS data is its inconsistency on higher sampling frequencies. The usage of enhanced Kalman Filter usage to fill the gaps between the GPS data samples is presented. The presented Kalman filter is enhanced to contain the velocity data on the output. The output velocity data meet the condition of integration and differentiation between the values of the position and the velocity