A New Approach for Small Satellite Gyroscope and Star Tracker Fusion

Abstract

This paper discusses the use of hybridization of measurements from different sensors (namely the gyroscope and star tracker) in order to estimate the attitude of a satellite. In this study, an adaptive fuzzy logic algorithm is developed in order to add robustness to the existing extended Kalman-filtering method of sensor fusion. Models of the sensor are developed and a simulation is programmed in Matlab in order to examine the effectiveness of the new algorithm. Results from the simulations show that the fuzzy logic algorithm allows for better pointing accuracy during the period of Star tracker unavailability. This method used the EKF filter effectively and optimally when the system parameters and noises are known. However in practice some of these parameters are uncertain, leading to the ineffectiveness when applied to system with high accuracy requirements or complex system. In order to overcome this constraint, fuzzy algorithm can be used to evaluate the reliability of the each component then estimate the appropriate tuning parameters. This approach will facilitate small satellite attitude fault-tolerance estimator.