Inverse problems in GPS positioning and numerical computation(II): Kaiman Filter 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 Kaiman Filter 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. Kaiman Filter, which the correction to approximate GPS receiver position is as the filtering state vector and we take into account the state of GPS receiver and clock bias in static positioning. Results show the Kaiman Filter provide good estimation. Future research directions are also discussed.