ADAPTIVE KALMAN FILTERING ALGORITHM FOR SMALL SATELLITE ATTITUDE DETERMINATION BY USING GPS/GYRO INTEGRATED SYSTEM

摘要

Spacecraft attitude determination system using GPS and rate gyro, which has the characteristics of high accuracy, high reliability and low cost, is a typical attitude determination mode for small satellite. This system uses the measurement information from GPS, rate gyro and spacecraft attitude dynamics to estimate the attitude information and measurement errors of GPS and gyro by filtering algorithms. And, Kalman filtering is a wide used real time recursive algorithm in the filtering algorithms. The methods for spacecraft attitude determination using GPS are discussed in this paper. The models of attitude determination using GPS/rate gyro integrated system for small satellite are established. Three Kalman filtering algorithms including state augment, measurement difference and adaptive Kalman filtering method are analyzed. An adaptive Kalman filtering algorithm, which has the characteristic of time varied noise statistic following and overcoming the shortage of the traditional Kalman filtering algorithm, is presented. Some simulation works of the GPS/rate gyro integrated attitude determination system using these algorithms are carried out. The simulation results show that the adaptive Kalman filter can not only mitigate the effect of the uncertain of noise statistic on Kalman filter, but also be used to estimate the errors of the system model, which improves the performance of the attitude determination system compared with the traditional Kalamn filtering algorithm.