Autonomous orbit determination system for earth satellites

Kerry D. Hicks; William E. Wiesel

doi:10.2514/3.20876

Analysis of Filtering Methods for Satellite Autonomous Orbit Determination Using Celestial and Geomagnetic Measurement

Mathematical Problems in Engineering ◽

10.1155/2012/267875 ◽

2012 ◽

Vol 2012 ◽

pp. 1-16 ◽

Cited By ~ 17

Author(s):

Xiaolin Ning ◽

Xin Ma ◽

Cong Peng ◽

Wei Quan ◽

Jiancheng Fang

Keyword(s):

Kalman Filter ◽

Orbit Determination ◽

Unscented Kalman Filter ◽

Satellite Orbit ◽

Filtering Method ◽

Unscented Particle Filter ◽

Autonomous Orbit Determination ◽

Determination System ◽

Orbit Dynamic ◽

Satellite Orbit Dynamic

Satellite autonomous orbit determination (OD) is a complex process using filtering method to integrate observation and orbit dynamic equations effectively and estimate the position and velocity of a satellite. Therefore, the filtering method plays an important role in autonomous orbit determination accuracy and time consumption. Extended Kalman filter (EKF), unscented Kalman filter (UKF), and unscented particle filter (UPF) are three widely used filtering methods in satellite autonomous OD, owing to the nonlinearity of satellite orbit dynamic model. The performance of the system based on these three methods is analyzed under different conditions. Simulations show that, under the same condition, the UPF provides the highest OD accuracy but requires the highest computation burden. Conclusions drawn by this study are useful in the design and analysis of autonomous orbit determination system of satellites.

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Autonomous Orbit Determination System of Navigation Satellite Based on Spaceborne GPS Technology

Security and Communication Networks ◽

10.1155/2022/7463315 ◽

2022 ◽

Vol 2022 ◽

pp. 1-10

Author(s):

Li Yang ◽

Haote Ruan ◽

Yunhan Zhang

Keyword(s):

Orbit Determination ◽

Unscented Kalman Filter ◽

Satellite Orbit ◽

Filter Method ◽

Variance Matrix ◽

Champ Satellite ◽

Autonomous Orbit Determination ◽

Determination System ◽

Coarse Error ◽

Kalman Filter Method

In recent years, many low-orbit satellites have been widely used in the field of scientific research and national defense in China. In order to meet the demand of high-precision satellite orbit in China’s space, surveying and mapping, and other related fields, navigation satellites are of great significance. The UKF (unscented Kalman filter) method is applied to space targets’ spaceborne GPS autonomous orbit determination. In this paper, the UKF algorithm based on UT transformation is mainly introduced. In view of the situation that the system noise variance matrix is unknown or the dynamic model is not accurate, an adaptive UKF filtering algorithm is proposed. Simulation experiments are carried out with CHAMP satellite GPS data, and the results show that the filtering accuracy and stability are improved, which proves the algorithm’s effectiveness. The experimental results show that the Helmert variance component estimation considering the dynamics model can solve the problem of reasonable weight determination of BDS/GPS observations and effectively weaken the influence of coarse error and improve the accuracy of orbit determination. The accuracy of autonomous orbit determination by spaceborne BDS/GPS is 1.19 m and 2.35 mm/s, respectively.

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