Abstract
The INS/CNS (Inertial Navigation System/Celestial Navigation System) composite navigation system error models and different error filtering estimation methods are studied in the paper. To avoid the difficult parameter selection of the standard UKF’s (Unscented Kalman Filter) sigma points weights calculation, a new sampling point weights calculation method is presented. The new sampling point weights are only related to the state vector’s probability density function. Furthermore, both of EKF (Extended Kalman Filter) and the new UKF are used to analyze the impact of the initial installation error on the filtering accuracy. Numerical simulation results show that when the star sensor has large installation misalignment angles, the new UKF can improve the nonlinear errors more effectively than EKF.
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Guo, Z., Xie, J., Chen, Z., Wu, B., Ji, D., Yu, Y. (2022). The On-line Filtering Technology of INS/CNS Composite Navigation. In: Yan, L., Duan, H., Yu, X. (eds) Advances in Guidance, Navigation and Control . Lecture Notes in Electrical Engineering, vol 644. Springer, Singapore. https://doi.org/10.1007/978-981-15-8155-7_356
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DOI: https://doi.org/10.1007/978-981-15-8155-7_356
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