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• W4313462175 abstract "In order to make full use of multi-GNSS constellations for time transfer, we propose a multi-GNSS combination method based on the fault-tolerant federated Kalman filter. First, the single-constellation all-in-view (AV) or common view (CV) solutions were evaluated with their current constellation on long and short baselines. We show that Galileo basically provides time transfer performance that is better than other constellations. Then, taking the TAIPPP link as a reference, the bias determined as the average difference between each single-constellation AV/CV solution and TAIPPP was obtained. After all single-constellation solutions had been aligned to the TAIPPP link, the fault-tolerant federated Kalman filter was used to combine the constellations into one global solution, which was compared with the standard-deviation-weighted solutions, TAIPPP, and Galileo-only solutions. The results show that fault-tolerant federated Kalman combined solutions agree with the results of other time comparison methods, and its frequency stability is the highest for averaging times less than 1×104 s. On the long baseline of NTSC-PTB and NTSC-SP, the standard deviation gain factors for the double clock differences (DCD) of fault-tolerant federated Kalman combined solutions versus Galileo-only solutions against the TAIPPP link are 2.96 and 1.82, respectively. On the short baseline of SP-PTB and TP-PTB, the gain factors are 3.00 and 1.18, respectively. Finally, the robustness of the fault-tolerant federated Kalman filter was analyzed. And the results indicate that when the subsystem fails, the fault-tolerant federated Kalman filter can quickly detect and isolate the fault, which ensures the accuracy of the global combined solutions and improves the robustness of the system." @default.
• W4313462175 created "2023-01-06" @default.
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• W4313462175 date "2023-05-01" @default.
• W4313462175 modified "2023-10-18" @default.
• W4313462175 title "A combination of multi-GNSS time transfer based on the fault-tolerant federated Kalman filter" @default.
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• W4313462175 doi "https://doi.org/10.1016/j.asr.2022.12.043" @default.
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