With emergence of the BeiDou Navigation Satellite System(BDS), the Galileo Satellite Navigation System(Galileo), the Quasi-Zenith Satellite System(QZSS)and the restoration of the Global Navigation Satellite System(GLO...With emergence of the BeiDou Navigation Satellite System(BDS), the Galileo Satellite Navigation System(Galileo), the Quasi-Zenith Satellite System(QZSS)and the restoration of the Global Navigation Satellite System(GLONASS), the single Global Positioning System(GPS) has been gradually expanded into multiple global and regional navigation satellite systems(multi-GNSS/RNSS). In view of differences in these 5 systems, a consolidated multi-GNSS/RNSS precise point positioning(PPP) observation model is deduced in this contribution. In addition, the performance evaluation of PPP for multi-GNSS/RNSS is conducted using a large number of the multi-GNSS experiment(MGEX) station datasets. Experimental results show that multi-GNSS/RNSS can guarantee plenty of visible satellites effectively. Compared with single-system GPS, PDOP, HDOP, and VDOP values of the multi-GNSS/RNSS are improved by 46.8%, 46.5% and 46.3%, respectively. As for convergence time, the static and kinematic PPP of multi-GNSS/RNSS are superior to that of the single-system GPS, whose reliability, availability, and stability drop sharply with the increasing elevation cutoff. At satellite elevation cutoff of 40 °, the single-system GPS fails to carry out continuous positioning because of the insufficient visible satellites, while the multi-GNSS/RNSS PPP can still get positioning solutions with relatively high accuracy, especially in the horizontal direction.展开更多
The tropopause is a transitional layer between the troposphere and the stratosphere. The exchange of chemical constituents of the atmosphere (namely masses of air, water vapor, trace gases etc.) and energy between the...The tropopause is a transitional layer between the troposphere and the stratosphere. The exchange of chemical constituents of the atmosphere (namely masses of air, water vapor, trace gases etc.) and energy between the troposphere and the stratosphere occurs through this layer. We suppose that just exchanges that are taking place at the tropopause heights are strongly influenced by the Global Change forcing. For this reason it is particularly urgent to accumulate temporal data the most accurate possible and with a certain continuity series to understand comprehensively what is happening to our climate. It is well known that Radio Occultation technique applied using Global Navigations Satellite Systems (GNSS-RO) is a powerful tool to detect the tropopause heights. It can be done working on the level 2 data provided by GNSS-RO payload: i.e. atmospheric profiles of pressure and temperature. We propose to measure tropopause using GNSS-RO level 1 data;i.e. the bending angles (BA) of the GNSS signal through the atmosphere. We fit the BA profiles applying in the integral relationship of BA as refractivity profile of background the Hopfield dry model of atmosphere which depends on the fourth degree of the height above the Earth. Through the layers in which tropopause is contained, the residuals between the background model and the observed BA have an anomalous trend. The residuals in this zone form anomalous non-gaussian bumps that we have exploited just to determine the relevant parameters of the tropopause. Such bumps are due to the wrong theoretical assumption made by Hopfield for the re-construction of the dry refractivity that the temperature lapse rate of the atmosphere is constant. But we know that the definition of tropopause according the World Meteorological Organization (WMO) is just the height where a sudden change of the temperature lapse rate usually occurs. Thus in the present work we have determined tropopause heights with new algorithms which exploit the bumps occurring along the BA profiles achieved by GNSS-RO. We have used the huge amount of data provided by several space missions devoted to GNSS-RO (namely COSMIC, METOP, etc.) for tuning the algorithms, performed a validation and provided a robust statistical soundness. The same GNSS-RO observations are helpful also to reconstruct the Mapping Function commonly applied in geodetic applications. Global mapping functions built with GNSS-RO and their evolution in time can be an interesting parameter helpful for climate investigations as well.展开更多
To realize the automatic detection of solar radio burst(SRB)intensity,detection based on a modified multifactor support vector machine(SVM)algorithm is proposed.First,the influence of SRB on global navigation satellit...To realize the automatic detection of solar radio burst(SRB)intensity,detection based on a modified multifactor support vector machine(SVM)algorithm is proposed.First,the influence of SRB on global navigation satellite system(GNSS)signals is analyzed.Feature vectors,which can reflect the SRB intensity of stations,are also extracted.SRB intensity is classified according to the solar radio flux,and different class labels correspond to different SRB intensity types.The training samples are composed of feature vectors and their corresponding class labels.Second,training samples are input into SVM classifiers to one-against-one training to obtain the optimal classification models.Finally,the optimal classification model is synthesized into a modified multifactor SVM classifier,which is used to automatically detect the SRB intensity of new data.Experimental results indicate that for historical SRB events,the average accuracy of SRB intensity detection is greater than 90%when the solar incident angle is higher than 20°.Compared with other methods,the proposed method considers many factors with higher accuracy and does not rely on radio telescopes,thereby saving cost.展开更多
基金Supported by the National Natural Science Foundation of China (No. 41604018)the Fundamental Research Funds for the Central Universities(No. 2019B17514)+1 种基金Postgraduate Research&Practice Innovation Program of Jiangsu Province (No. nos. sjky19_05132019B60114)
文摘With emergence of the BeiDou Navigation Satellite System(BDS), the Galileo Satellite Navigation System(Galileo), the Quasi-Zenith Satellite System(QZSS)and the restoration of the Global Navigation Satellite System(GLONASS), the single Global Positioning System(GPS) has been gradually expanded into multiple global and regional navigation satellite systems(multi-GNSS/RNSS). In view of differences in these 5 systems, a consolidated multi-GNSS/RNSS precise point positioning(PPP) observation model is deduced in this contribution. In addition, the performance evaluation of PPP for multi-GNSS/RNSS is conducted using a large number of the multi-GNSS experiment(MGEX) station datasets. Experimental results show that multi-GNSS/RNSS can guarantee plenty of visible satellites effectively. Compared with single-system GPS, PDOP, HDOP, and VDOP values of the multi-GNSS/RNSS are improved by 46.8%, 46.5% and 46.3%, respectively. As for convergence time, the static and kinematic PPP of multi-GNSS/RNSS are superior to that of the single-system GPS, whose reliability, availability, and stability drop sharply with the increasing elevation cutoff. At satellite elevation cutoff of 40 °, the single-system GPS fails to carry out continuous positioning because of the insufficient visible satellites, while the multi-GNSS/RNSS PPP can still get positioning solutions with relatively high accuracy, especially in the horizontal direction.
文摘The tropopause is a transitional layer between the troposphere and the stratosphere. The exchange of chemical constituents of the atmosphere (namely masses of air, water vapor, trace gases etc.) and energy between the troposphere and the stratosphere occurs through this layer. We suppose that just exchanges that are taking place at the tropopause heights are strongly influenced by the Global Change forcing. For this reason it is particularly urgent to accumulate temporal data the most accurate possible and with a certain continuity series to understand comprehensively what is happening to our climate. It is well known that Radio Occultation technique applied using Global Navigations Satellite Systems (GNSS-RO) is a powerful tool to detect the tropopause heights. It can be done working on the level 2 data provided by GNSS-RO payload: i.e. atmospheric profiles of pressure and temperature. We propose to measure tropopause using GNSS-RO level 1 data;i.e. the bending angles (BA) of the GNSS signal through the atmosphere. We fit the BA profiles applying in the integral relationship of BA as refractivity profile of background the Hopfield dry model of atmosphere which depends on the fourth degree of the height above the Earth. Through the layers in which tropopause is contained, the residuals between the background model and the observed BA have an anomalous trend. The residuals in this zone form anomalous non-gaussian bumps that we have exploited just to determine the relevant parameters of the tropopause. Such bumps are due to the wrong theoretical assumption made by Hopfield for the re-construction of the dry refractivity that the temperature lapse rate of the atmosphere is constant. But we know that the definition of tropopause according the World Meteorological Organization (WMO) is just the height where a sudden change of the temperature lapse rate usually occurs. Thus in the present work we have determined tropopause heights with new algorithms which exploit the bumps occurring along the BA profiles achieved by GNSS-RO. We have used the huge amount of data provided by several space missions devoted to GNSS-RO (namely COSMIC, METOP, etc.) for tuning the algorithms, performed a validation and provided a robust statistical soundness. The same GNSS-RO observations are helpful also to reconstruct the Mapping Function commonly applied in geodetic applications. Global mapping functions built with GNSS-RO and their evolution in time can be an interesting parameter helpful for climate investigations as well.
基金The National Key Research and Development Plan of China(No.2018YFB0505103)the National Natural Science Foundation of China(No.61873064)。
文摘To realize the automatic detection of solar radio burst(SRB)intensity,detection based on a modified multifactor support vector machine(SVM)algorithm is proposed.First,the influence of SRB on global navigation satellite system(GNSS)signals is analyzed.Feature vectors,which can reflect the SRB intensity of stations,are also extracted.SRB intensity is classified according to the solar radio flux,and different class labels correspond to different SRB intensity types.The training samples are composed of feature vectors and their corresponding class labels.Second,training samples are input into SVM classifiers to one-against-one training to obtain the optimal classification models.Finally,the optimal classification model is synthesized into a modified multifactor SVM classifier,which is used to automatically detect the SRB intensity of new data.Experimental results indicate that for historical SRB events,the average accuracy of SRB intensity detection is greater than 90%when the solar incident angle is higher than 20°.Compared with other methods,the proposed method considers many factors with higher accuracy and does not rely on radio telescopes,thereby saving cost.
