Ionosphere delay is one of the main sources of noise affecting global navigation satellite systems, operation of radio detection and ranging systems and very-long-baseline-interferometry. One of the most important and...Ionosphere delay is one of the main sources of noise affecting global navigation satellite systems, operation of radio detection and ranging systems and very-long-baseline-interferometry. One of the most important and common methods to reduce this phase delay is to establish accurate nowcasting and forecasting ionospheric total electron content models. For forecasting models, compared to mid-to-high latitudes, at low latitudes, an active ionosphere leads to extreme differences between long-term prediction models and the actual state of the ionosphere. To solve the problem of low accuracy for long-term prediction models at low latitudes, this article provides a low-latitude, long-term ionospheric prediction model based on a multi-input-multi-output, long-short-term memory neural network. To verify the feasibility of the model, we first made predictions of the vertical total electron content data 24 and 48 hours in advance for each day of July 2020 and then compared both the predictions corresponding to a given day, for all days. Furthermore, in the model modification part, we selected historical data from June 2020 for the validation set, determined a large offset from the results that were predicted to be active, and used the ratio of the mean absolute error of the detected results to that of the predicted results as a correction coefficient to modify our multi-input-multi-output long short-term memory model. The average root mean square error of the 24-hour-advance predictions of our modified model was 4.4 TECU, which was lower and better than5.1 TECU of the multi-input-multi-output, long short-term memory model and 5.9 TECU of the IRI-2016 model.展开更多
We demonstrate a novel and stable frequency transfer scheme over ground-to-satellite link based on real-time carrier-phase detection and compensation.We performed a zero-baseline measurement with the designed system,a...We demonstrate a novel and stable frequency transfer scheme over ground-to-satellite link based on real-time carrier-phase detection and compensation.We performed a zero-baseline measurement with the designed system,an uninterrupted frequency standard signal is recovered in the reception station without additional post-correction of delay error caused in the route,which is because the phase error of the entire route is tracked and compensated continuously in real-time.To achieve this goal,we employed two carriers in the system and the differential signal is transferred in order to eliminate the instability results from the local oscillator at the satellite transponder as well as the common-mode noise induced in the transfer route and microwave components.The stability of 3×10^(-16) with an integration time of 1 day was achieved and the time fluctuation during one day was measured to be about±20 ps.Error sources and possible solutions are discussed.Our zero-baseline method shows a promising result for real-time satellite-based time and frequency transfer and deserves further research to find whether it works between long-baseline stations.展开更多
基金Project supported by the National Key Research and Development Program of China(Grant No.2016YFA0302101)the Initiative Program of State Key Laboratory of Precision Measurement Technology and Instrument。
文摘Ionosphere delay is one of the main sources of noise affecting global navigation satellite systems, operation of radio detection and ranging systems and very-long-baseline-interferometry. One of the most important and common methods to reduce this phase delay is to establish accurate nowcasting and forecasting ionospheric total electron content models. For forecasting models, compared to mid-to-high latitudes, at low latitudes, an active ionosphere leads to extreme differences between long-term prediction models and the actual state of the ionosphere. To solve the problem of low accuracy for long-term prediction models at low latitudes, this article provides a low-latitude, long-term ionospheric prediction model based on a multi-input-multi-output, long-short-term memory neural network. To verify the feasibility of the model, we first made predictions of the vertical total electron content data 24 and 48 hours in advance for each day of July 2020 and then compared both the predictions corresponding to a given day, for all days. Furthermore, in the model modification part, we selected historical data from June 2020 for the validation set, determined a large offset from the results that were predicted to be active, and used the ratio of the mean absolute error of the detected results to that of the predicted results as a correction coefficient to modify our multi-input-multi-output long short-term memory model. The average root mean square error of the 24-hour-advance predictions of our modified model was 4.4 TECU, which was lower and better than5.1 TECU of the multi-input-multi-output, long short-term memory model and 5.9 TECU of the IRI-2016 model.
基金Project supported by the National Key Research and Development Program of China (Grant No. 2016YFA0302101)the Initiative Program of State Key Laboratory of Precision Measurement Technology and Instruments
文摘We demonstrate a novel and stable frequency transfer scheme over ground-to-satellite link based on real-time carrier-phase detection and compensation.We performed a zero-baseline measurement with the designed system,an uninterrupted frequency standard signal is recovered in the reception station without additional post-correction of delay error caused in the route,which is because the phase error of the entire route is tracked and compensated continuously in real-time.To achieve this goal,we employed two carriers in the system and the differential signal is transferred in order to eliminate the instability results from the local oscillator at the satellite transponder as well as the common-mode noise induced in the transfer route and microwave components.The stability of 3×10^(-16) with an integration time of 1 day was achieved and the time fluctuation during one day was measured to be about±20 ps.Error sources and possible solutions are discussed.Our zero-baseline method shows a promising result for real-time satellite-based time and frequency transfer and deserves further research to find whether it works between long-baseline stations.
