Abstract
At present, the fusion of position and attitude information and accurate real-time target tracking are problems to be solved in measurement and service of geographic information. Aiming at the errors of GPS positioning and star sensor attitude determination, this paper proposes a GPS/star sensor integrated navigation data fusion and error compensation method (GAKF), in which GPS attitude estimation is used in Kalman filter. The attitude of GPS is calculated and fused with the star sensor data, and the integrated navigation error compensation is performed through Kalman filtering to correct the position and attitude errors. Experiments show that this method can effectively reduce position and attitude errors. Compared with traditional integrated navigation methods, it can avoid the cumulative error of the inertial navigation attitude measurement, thus improve the monitoring and service capabilities of GPS and star sensor integrated navigation positioning and attitude determination.
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This work was supported in part by the Open Research Fund of National Key Laboratory of Satellite Navigation System and Equipment Technology under grant NO. GEPNT-2017KF-08.
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Zhang, L., He, C., Wang, B., Chen, Z. (2022). Data Fusion and Error Compensation Method for GPS/Star Sensor Integrated Navigation Using GPS Attitude Estimation. In: Liang, Q., Wang, W., Liu, X., Na, Z., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2021. Lecture Notes in Electrical Engineering, vol 878. Springer, Singapore. https://doi.org/10.1007/978-981-19-0390-8_1
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DOI: https://doi.org/10.1007/978-981-19-0390-8_1
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