Analysis and Simulation of Discrete Kalman Filtering Applied to a GPS Receiver

The NAVSTAR Global Position System (GPS) is a world wide, highly accurate, all weather, radionavigation system. The use of GPS signals for positioning and navigation is important not only to military users but also to civilian users requiring an accurate positioning service. The applicaiton of GPS technology has expanded to many areas in the past few years. The future might see not only missiles guided by GPS signals but also the family vehicle navigated by GPS. One of the most widely used techniques to improve the positioning accuracy of GPS is Kalman filtering. Kalman filters were first described by R.E. Kalman in his 1960 paper. Since then Kalman filters have been used in many different fields. They are particularly useful in solving radionavigation problems because of the recursive nature of the filter and also because the assumption of a Gaussian noise distribution accurately models the noisy measurements of radionavigation signals. This paper provides a general overview of GPS and analyzes the application of discrete Kalman filtering techniques used to improve the accuracy of navigation. A mathematical model of a GPS receiver is computer simulated. Results of the simulation demonstrate the vast reduction in position error due to the Kalman filter.