Inverse problems in GPS positioning and numerical computation(I): Regularization method

This paper presents the results obtained in our research about application of advanced signal processing to GPS based position estimation. In order to improve the positioning precision of standalone GPS, we introduced the Regularization algorithm. They all get approximate GPS receiver position with the help of Bancroft method and computed observation error covariance matrix using algorithm of the Calilo data processing software. Regularization, which take into account characteristic of observation data and optimum choice of regularization parameter. The experiment results indicate that it can enhance the ability stand up to bad errors, which have profound significance on real-time and fast positioning.