Development of GPS Receiver Kalman Filter Algorithms for Stationary, Low-Dynamics, and High-Dynamics Applications
Defence Science and Technology Group Edinburgh, South Australia Australia
Pagination or Media Count:
This report presents algorithms that can be utilized in a GPS receiver to convert satellite-to-receiver pseudo-ranges to receiver position estimates. The report discusses a method that is used to determine instantaneous estimates of receiver position and then goes on to develop three Kalman filter based estimators, which use stationary receiver, low dynamics, and high dynamics models for the receiver motion, respectively. These particular dynamic models are utilized because they are commonly used in actual GPS receivers, and cover a wide range of applications. While the standard form ofthe Kalman filter, of which the three filters just mentioned are examples, is theoretically correct, it can be susceptible to numerical round-off errors, which can in some cases result in poor performance or, in the worst case, filter divergence. This issue, and its solution, is investigated, and another version of the high dynamics filter, which addresses this problem, is presented. Matlab code was developed to test the performance of each of the filters and simulations were performed. The results of the simulations are also presented.
- Military Forces and Organizations
- Navigation and Guidance
- Statistics and Probability