Parallel filters for autonomous navigation using relative measurements between satellites
ZHANG Ai
LI Yong
Abstract：In order to reduce the influence of observation outliers on autonomous navigation using relative measurements between satellites, an parallel unscented Kalman filter based on orbital elements estimation is proposed in this paper. The parallel unscented Kalman filtering system is composed of two parallel filters. Firstly, the outliers in observation are identified by the parameter estimation of sub filter. Then the system states which are position and velocity of satellites are corrected in the major filter. A two satellites formation based on relative position measurements is selected as the basic system configuration. This paper also investigates the parameter selections of the parallel filter and compares the filtering results on different parameters combination. Numerical simulations show that the algorithm can effectively reduce the influence of series outliers in the autonomous navigation system when observations change rapidly. Compared with the traditional algorithm, the parallel unscented Kalman converges in less time with high accuracy.
Keywords：Kalman filterautonomous navigationparameter estimationparallel computing
Publication Date：2018-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：8( 761-768 )