Comparing the Extended and the Sigma Point Kalman Filters for Orbit Determination Modeling Using GPS Measurements

摘要

The purpose of this work is to compare the extended Kalman filter (EKF) against the nonlinear sigma point Kalman filter (SPKF) for the satellite orbit determination problem, using GPS measurements. The comparison is based on the levels of accuracy improvement of the orbit dynamics model. The main subjects for the comparison between the estimators are accuracy of models and results. Based on the analysis of such criteria, the advantages and drawbacks of each estimator are presented. In this work, the orbit of an artificial satellite is determined using real data from the Global Positioning System (GPS) receivers. In orbit determination of artificial satellites, the dynamic system and the measurements equations are of nonlinear nature. It is a nonlinear problem in which the disturbing forces are not easily modeled. The problem of orbit determination consists essentially of estimating parameter values that completely specify the body trajectory in the space, processing a set of information (measurements) related to this body. Such observations can be collected through a ground tracking network on Earth or through sensors, like space GPS receivers onboard the satellite.