Observable Degree Analysis of Geostationary Satellites´ Navigation System Based on Singular Value Decomposition

In this paper, the observable degree analysis for geostationary satellites´ navigation system with measurement biases of ultaviolet sensors is considered. Using GNSS measurements and starlight angular distances, the navigation system adopts extended Kalman filter to calibrate measurement biases of the UV sensor by augmentation of bias parameters. Then the observable degrees of system states are analyzed based on the SVD of the observability matrix, the observable degree of the measurement bias of the yaw axis is extremely poor. Thus, the reduced-order extended Kalman filter is designed by neglecting the poor observable parameter. Finally, the results of the simulation indicate that the precision of reduced-order algorithm is similar with the original algorithm. Therefore, the observable degree analysis method in this paper is feasible.