Simulators and Test Equipment

Petovello, Mark G.; Curran, James T.

doi:10.1007/978-3-319-42928-1_18

Cited by 3 publications

(2 citation statements)

References 18 publications

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“…We used RTK GNSS instruments composed of base stations and mobile stations to carry out field measurements. The mobile station simultaneously receives the observation data from the base station broadcast, and the mobile station antenna receives the observation data from the satellite, which forms the RTK observation model [33]. Its horizontal precision is 2.5 mm ± 2 ppm and its vertical precision is 5 mm ± 2 ppm.…”

Section: Base Data and Data Processingmentioning

confidence: 99%

Gully Erosion Susceptibility Mapping in Highly Complex Terrain Using Machine Learning Models

Yang

Wang

Pang

et al. 2021

IJGI

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Gully erosion is the most severe type of water erosion and is a major land degradation process. Gully erosion susceptibility mapping (GESM)’s efficiency and interpretability remains a challenge, especially in complex terrain areas. In this study, a WoE-MLC model was used to solve the above problem, which combines machine learning classification algorithms and the statistical weight of evidence (WoE) model in the Loess Plateau. The three machine learning (ML) algorithms utilized in this research were random forest (RF), gradient boosted decision trees (GBDT), and extreme gradient boosting (XGBoost). The results showed that: (1) GESM were well predicted by combining both machine learning regression models and WoE-MLC models, with the area under the curve (AUC) values both greater than 0.92, and the latter was more computationally efficient and interpretable; (2) The XGBoost algorithm was more efficient in GESM than the other two algorithms, with the strongest generalization ability and best performance in avoiding overfitting (averaged AUC = 0.947), followed by the RF algorithm (averaged AUC = 0.944), and GBDT algorithm (averaged AUC = 0.938); and (3) slope gradient, land use, and altitude were the main factors for GESM. This study may provide a possible method for gully erosion susceptibility mapping at large scale.

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Section: Base Data and Data Processingmentioning

confidence: 99%

Gully Erosion Susceptibility Mapping in Highly Complex Terrain Using Machine Learning Models

Yang

Wang

Pang

et al. 2021

IJGI

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“…For best compatibility of real and simulated Swarm GNSS observations, a software‐based, measurement‐level simulation approach (Petovello & Curran, 2017) has been adopted in our study. It is limited to offline simulations, but enables full control of all simulation models and does not suffer from corresponding restrictions of common GNSS radio‐frequency signal simulators.…”

Section: Multi‐gnss Measurement Simulation For Spaceborne Receiversmentioning

confidence: 99%

Precise real‐time navigation of LEO satellites using GNSS broadcast ephemerides

Hauschild

Montenbruck

2021

Navigation

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The availability of orbit information with high precision and low latency is a key requirement for many Earth‐observation missions, predominantly in the field of radio occultation. Traditionally, precise orbit determination solutions of low‐Earth orbit (LEO) satellites are obtained offline on ground after downloading GNSS measurements and auxiliary spacecraft data to the processing center. The latency of this processing depends on the frequency of LEO downlink contacts and the availability of precise GNSS orbit and clock products required for the orbit determination process. These dependencies can be removed by computing the precise orbit determination solution on board the satellite using GNSS broadcast ephemerides. In this study, both real data and simulated measurements from a representative LEO satellite are processed in a flight‐proven Kalman‐filter algorithm. The paper studies the use of GPS, Galileo and BeiDou‐3 for real‐time orbit determination in different combinations with simulated measurements. Results show that use of dual‐frequency observations and broadcast ephemerides of Galileo and BeiDou‐3 leads to a significant reduction of 3D rms orbit errors compared to GPS‐only processing. An onboard navigation accuracy of about one decimeter can be achieved without external augmentation data, which opens up new prospects for conducting relevant parts of the science data processing in future space missions directly on board a LEO satellite.

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