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Keywords = single-frequency occultation process

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17 pages, 5547 KB  
Article
First Galileo Single-Frequency Occultation Process and Precision Analysis of FengYun3E
by Ming Yang, Xiangguang Meng, Haoran Tian, Yueqiang Sun, Qifei Du, Weihua Bai, Bowen Wang, Xianyi Wang, Peng Hu and Guangyuan Tan
Remote Sens. 2023, 15(18), 4410; https://doi.org/10.3390/rs15184410 - 7 Sep 2023
Cited by 2 | Viewed by 1688
Abstract
This article proposes a single-frequency occultation method whose core is the reconstruction of a second frequency measurement. We process the actual received Galileo E1 single-frequency occultation observation data of FengYun3E to meet the urgent need for single-frequency Galileo occultation inversion of FengYun3 E/F/G/H [...] Read more.
This article proposes a single-frequency occultation method whose core is the reconstruction of a second frequency measurement. We process the actual received Galileo E1 single-frequency occultation observation data of FengYun3E to meet the urgent need for single-frequency Galileo occultation inversion of FengYun3 E/F/G/H satellites. Galileo single-frequency occultation events are globally distributed evenly and have stable quantities. The refractive index products and dry temperature products inverted from the single-frequency occultation data are reliable at altitudes of 5–30 km. The Galileo E1 single-frequency occultation process can effectively improve the output of FengYun3E/GNOS occultation products. These results validate the feasibility and correctness of using FengYun3/GNOS for the actual Galileo single-frequency occultation process. The atmospheric occultation products of Galileo single-frequency occultation increase the quantity of global occultation products and serve as a beneficial supplement to global numerical weather prediction data sources. Full article
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14 pages, 3292 KB  
Article
Verification and Accuracy Analysis of Single-Frequency Occultation Processing Based on the BeiDou Navigation System
by Ruimin Li, Qifei Du, Ming Yang, Haoran Tian, Yueqiang Sun, Xiangguang Meng, Weihua Bai, Xianyi Wang, Guangyuan Tan and Peng Hu
Atmosphere 2023, 14(4), 742; https://doi.org/10.3390/atmos14040742 - 19 Apr 2023
Cited by 2 | Viewed by 1920
Abstract
GNSS single-frequency occultation processing technology has the advantage of simple instrumentation, but it is not clear about the accuracy of the Beidou-based single-frequency occultation processing. This paper verifies the single-frequency occultation processing algorithm of the BeiDou navigation system (BDS) and analyzes its accuracy [...] Read more.
GNSS single-frequency occultation processing technology has the advantage of simple instrumentation, but it is not clear about the accuracy of the Beidou-based single-frequency occultation processing. This paper verifies the single-frequency occultation processing algorithm of the BeiDou navigation system (BDS) and analyzes its accuracy based on occultation observation data from the FY3E satellite. The research aimed to verify the single-frequency ionospheric relative total electron content (relTEC), analyze the accuracy of the reconstructed second frequency B3’s excess phase Doppler, and analyze the accuracy of the refractive index products. Results: (1) As for relTEC and excess phase Doppler, the correlation coefficient between single-frequency occultation processing and dual-frequency occultation processing is greater than 0.95. (2) The relative average deviations of the excess phase Doppler of B3 are mostly less than 0.2%, and the relative standard deviations are mostly around 0.5%. (3) The bias index and root mean square index of single/dual-frequency inversion have good consistency compared with ERA5 data. All the results show that the single- and dual-frequency inversion refractive index products have comparable accuracies, and the accuracy of the standard deviation of single-frequency inversion refractive index products over 25 km being slightly lower than that of dual-frequency inversion refractive index products. Full article
(This article belongs to the Special Issue GNSS Meteorology: Algorithm, Modelling, Assessment and Application)
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14 pages, 3062 KB  
Communication
Galileo Ionospheric Correction Algorithm Integration into the Open-Source GNSS Laboratory Tool Suite (gLAB)
by Angela Aragon-Angel, Adria Rovira-Garcia, Enrique Arcediano-Garrido and Deimos Ibáñez-Segura
Remote Sens. 2021, 13(2), 191; https://doi.org/10.3390/rs13020191 - 7 Jan 2021
Cited by 9 | Viewed by 4550
Abstract
Users of the global navigation satellite system (GNSS) operating with a single-frequency receiver must use an ionospheric correction algorithm (ICA) to account for the delay introduced on radio waves by the upper atmosphere. Galileo, the European GNSS, uses an ICA named NeQuick-G. In [...] Read more.
Users of the global navigation satellite system (GNSS) operating with a single-frequency receiver must use an ionospheric correction algorithm (ICA) to account for the delay introduced on radio waves by the upper atmosphere. Galileo, the European GNSS, uses an ICA named NeQuick-G. In an effort to foster the adoption of NeQuick-G by final users, two implementations in C language have been recently made available to the public by the European Space Agency (ESA) and the Joint Research Centre (JRC) of the European Commission (EC), respectively. The aim of the present contribution is to compare the slant total electron content (STEC) predictions of the two aforementioned implementations of NeQuick-G. For this purpose, we have used actual multi-constellation and multi-frequency data for several hundreds of stations distributed worldwide belonging to the Multi GNSS Experiment (MGEX) network of the International GNSS Service (IGS). For each first day of the month during year 2019, the STECs of the two NeQuick-G versions were compared in terms of accuracy, consistency, availability, and execution time. Our study concludes that both implementations of NeQuick-G perform equivalently. Indeed, in over 99.998% of the 2125 million STECs computed, the output is exactly coincident. In contrast, 0.002% of the whole set of STECs for those rays are tangent to the Earth, the behavior of both implementations differs. We confirmed the discrepancy by processing radio-occultation actual measurements from a COSMIC-2 low Earth orbit satellite. We selected the JRC version of the Galileo ICA to be integrated into the GNSS LABoratory (gLAB) tool suite, because its open license and its processing speed (it is 13.88% faster than the ESA version). NeQuick-G outperforms the GPS ICA in STEC residuals up to 12.15 TECUs (percentile 96.23th) and in the 3D position errors, up to 5.76 m (percentile 99.18th) for code-pseudorange positioning. Full article
(This article belongs to the Section Remote Sensing Perspective)
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22 pages, 3031 KB  
Article
Meeting Earth Observation Requirements for Global Agricultural Monitoring: An Evaluation of the Revisit Capabilities of Current and Planned Moderate Resolution Optical Earth Observing Missions
by Alyssa K. Whitcraft, Inbal Becker-Reshef, Brian D. Killough and Christopher O. Justice
Remote Sens. 2015, 7(2), 1482-1503; https://doi.org/10.3390/rs70201482 - 29 Jan 2015
Cited by 74 | Viewed by 10338
Abstract
Agriculture is a highly dynamic process in space and time, with many applications requiring data with both a relatively high temporal resolution (at least every 8 days) and fine-to-moderate (FTM < 100 m) spatial resolution. The relatively infrequent revisit of FTM optical satellite [...] Read more.
Agriculture is a highly dynamic process in space and time, with many applications requiring data with both a relatively high temporal resolution (at least every 8 days) and fine-to-moderate (FTM < 100 m) spatial resolution. The relatively infrequent revisit of FTM optical satellite observatories coupled with the impacts of cloud occultation have translated into a barrier for the derivation of agricultural information at the regional-to-global scale. Drawing upon the Group on Earth Observations Global Agricultural Monitoring (GEOGLAM) Initiative’s general satellite Earth observation (EO) requirements for monitoring of major production areas, Whitcraft et al. (this issue) have described where, when, and how frequently satellite data acquisitions are required throughout the agricultural growing season at 0.05°, globally. The majority of areas and times of year require multiple revisits to probabilistically yield a view at least 70%, 80%, 90%, or 95% clear within eight days, something that no present single FTM optical observatory is capable of delivering. As such, there is a great potential to meet these moderate spatial resolution optical data requirements through a multi-space agency/multi-mission constellation approach. This research models the combined revisit capabilities of seven hypothetical constellations made from five satellite sensors—Landsat 7 Enhanced Thematic Mapper (Landsat 7 ETM+), Landsat 8 Operational Land Imager and Thermal Infrared Sensor (Landsat 8 OLI/TIRS), Resourcesat-2 Advanced Wide Field Sensor (Resourcesat-2 AWiFS), Sentinel-2A Multi-Spectral Instrument (MSI), and Sentinel-2B MSI—and compares these capabilities with the revisit frequency requirements for a reasonably cloud-free clear view within eight days throughout the agricultural growing season. Supplementing Landsat 7 and 8 with missions from different space agencies leads to an improved capacity to meet requirements, with Resourcesat-2 providing the largest incremental improvement in requirements met. The best performing constellation can meet 71%–91% of the requirements for a view at least 70% clear, and 45%–68% of requirements for a view at least 95% clear, varying by month. Still, gaps exist in persistently cloudy regions/periods, highlighting the need for data coordination and for consideration of active EO for agricultural monitoring. This research highlights opportunities, but not actual acquisition rates or data availability/access; systematic acquisitions over actively cropped agricultural areas as well as a policy which guarantees continuous access to high quality, interoperable data are essential in the effort to meet EO requirements for agricultural monitoring. Full article
(This article belongs to the Special Issue Remote Sensing in Food Production and Food Security)
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