An adaptive segmented information fusion method for attitude determination of nano-spacecrafts

Strapdown stellar-inertial integrated attitude determination based on low-cost micro-electromechanical system (MEMS) gyroscopes and a complementary metal-oxide-semiconductor transistor active pixel star sensor is one of the most effective methods for nano-spacecrafts attitude determination. However, the accuracy of attitude determination is low because of non-linearity of the system. Thus, an adaptive segmented information fusion method based on the UKF is presented by taking UKF+QUEST and UKF+optimal REQUEST as two modes of information fusion that can be adaptively switched between. Initially, the gyro drift estimation error is inaccurate, and the UKF+QUEST mode is adopted to quickly estimate the gyro drifts. When the mean-square error matrix of the UKF tends to stabilization, the information fusion mode is adaptively switched to the UKF+optimal REQUEST dual-filter model. The hybrid simulation results show this method not only has higher accuracy in attitude determination but also can quickly estimate gyro drifts.

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