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GNSS -- global navigation satellite systems : GPS, GLONASS, Galileo, and more
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TLDR
The next generation of positioning models for positioning and data processing will depend on the design of the satellite itself, as well as on the satellite orbits it is placed in.Citations
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Journal ArticleDOI
Precise Point Positioning Using Triple GNSS Constellations in Various Modes.
Akram Afifi,Ahmed El-Rabbany +1 more
TL;DR: It is shown that combining the GPS, Galileo, and BeiDou observations in the post-processing mode improves the PPP convergence time by 25% compared with the GPS-only counterpart, regardless of the linear combination used.
Journal ArticleDOI
Fast and precise positioning using mafa method and new gps and galileo signals
TL;DR: In this article, the authors presented the foundations of MAFA method, as well as its application to the processing of new GPS and Galileo signals, and presented numerical tests have been carried out on the basis of data obtained from a hardware GNSS signal simulator as there are currently too few Galileo satellites on orbit.
Book ChapterDOI
Monitoring Landslide Activities in the Three Gorges Area with Multi-frequency Satellite SAR Data Sets
TL;DR: Wang et al. as mentioned in this paper investigated the applications of several methods using Synthetic Aperture Radar (SAR) datasets in landslide monitoring in the Three Gorges area, and qualitative correlation analyses indicated that variation of reservoir water level, particularly the rapid water-level decrease due to discharge, should be identified as a key driving factor for landslide deformation.
Book ChapterDOI
Batch and Recursive Model Validation
TL;DR: Since batch and recursive estimation are common methods of GNSS data processing, the validation and integrity monitoring of both will be discussed in this chapter.
Journal ArticleDOI
Classification and legality analysis of bowling action in the game of cricket
TL;DR: A system to detect the legality of the bowling action based on real time multidimensional physiological data obtained from the inertial sensors mounted on the bowlers arm is presented and achieves very high accuracy in the correct classification of bowling action.