Nonlinear iterative algorithm for GPS positioning with bias model

This work presents the results obtained in our research about the application of advanced signal processing to GPS based position estimation. This technique can be used to improve the robustness and accuracy characteristics of the low-cost standalone GPS receivers. A new nonlinear model including the errors computed using navigation messages (acquired from the satellite transmitted data) for position estimation is developed. A new GPS positioning method based on an iterative algorithm, and the new model are proposed. The method uses an algorithm that iteratively uses unscented Kalman filters and smoothers to compute the position estimates. The first experimental results, and comparison of the results obtained with different algorithms are also presented. First results show that our approaches provide better estimation than other solutions. Future research directions are also discussed.