Abstract:On-board atomic clock is one of the core equipment of navigation satellite system. Its performance and clock bias prediction accuracy directly determine the accuracy of navigation and positioning timing services. Aiming at the problem that it is difficult to determine the weight of the neutron model of the satellite clock bias combined forecast model, the entropy weight method is introduced into the Beidou satellite clock bias combined forecast. Perform phase-frequency combined detection of outliers such as gross errors and clock jumps in satellite clock bias data, and use sliding Lagrangian interpolation to repair them to obtain a “clean” clock bias sequence. Based on the grey model and the quadratic polynomial model, a combination model of clock bias based on information entropy, a new evaluation index, is constructed, and a combined forecast model of Beidou satellite clock bias entropy weight is established. Using the Beidou precision clock bias data product released by the IGS Data Center of Wuhan University, the short term forecast and medium-long term forecast experiments are carried out for multiple consecutive days. The multi-day average test results verify that the entropy weight combination model has certain advantages over the traditional combination model in terms of the accuracy and stability of the Beidou satellite clock bias prediction.
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