科研之友
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摘要
To improve the accuracy of the starlight navigation algorithm, a two-step Kalman filter algorithm is proposed. Through first-step star navigation filter preprocessing, a rough satellite position estimation is obtained. The position estimation is introduced into the earth oblateness error correction algorithm and the earth oblateness error in the earth sensor is corrected effectively and autonomously. Then, using the corrected earth sensor outputs to form accurate star angular distance observation information, the starlight navigation algorithm is reused and the navigation messages are precisely determined. The simulation results show that by the two-step Kalman filter algorithm, the accuracy of the geocentric vector measured by the earth sensor is 0.001 °, the three-axis position estimation errors of satellite are 3000 m, and the three-axis velocity estimation errors of the satellite are 4 m/s. Compared with the traditional uncorrected starlight navigation algorithm, the accuracy has been improved by more than 80%.
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