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Erschienen in:
2020 | OriginalPaper | Buchkapitel
Unification of Multi-GNSS Bias Reference and Parameter Optimization of ISB/IFB Random Model
verfasst von : Longping Zhang, Junyi Xu, Hanzhang Yu, Xiancai Tian, Deqiang Han
Erschienen in: China Satellite Navigation Conference (CSNC) 2020 Proceedings: Volume III
Verlag: Springer Singapore
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Abstract
When multi-GNSS system data fusion is performed, differences in signal structure and transmitting frequency between different systems can seriously affect the precision orbit determination or positioning performance. In this paper, the unification method of multi-GNSS bias reference is derived, and the ISB /IFB random model is constructed based on the first-order Gaussian Markov process. The observation equation is solved by the virtual observation value, and the multi-GNSS ISB/IFB multi-day and single-day sequences are obtained, analyzed and evaluated. The result of MGEX test data shows that the multi-day ISB/IFB of each GNSS system is very steady but with obvious stratification, and the time series of each satellite in the same system shows good consistency. The dynamic sequence of single-day BDS and Galileo ISB is steady, and the amplitude is basically within 1 ns; the multi-day GLONASS IFB of albh tracking station is between −2 ns and 3 ns, and the STD of single-day GLONASS IFB is within 0.4 ns.