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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.
Abstract
Reference systems.- Satellite orbits.- Satellite signals.- Observables.- Mathematical models for positioning.- Data processing.- Data transformation.- GPS.- Glonass.- Galileo.- More on GNSS.- Applications.- Conclusion and outlook.

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Journal ArticleDOI

goGPS: open-source MATLAB software

TL;DR: The main modules of goGPS are described along with some examples to show the user how the software works, and the software is continues to evolve, improving its functionalities according to the updates introduced by the collaborators.
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Vertical deformations from homogeneously processed GRACE and global GPS long-term series

TL;DR: In this paper, the mean annual signals computed from the GPS and GRACE series are compared and statistically analyzed: they determine the stability (precision) of GRACE-derived, monthly vertical deformation data to be ~1.2 mm, using the data from three GRACE processing centers.
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Tightly coupled integration of GPS precise point positioning and MEMS-based inertial systems

TL;DR: A new integrated navigation system, which integrates GPS precise point positioning (PPP) with low-cost micro-electro-mechanical sensors (MEMS) inertial system, for precise positioning applications and it is shown that decimeter-level positioning accuracy is achievable with both undifferenced and BSSD integrated systems.
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PPP models and performances from single- to quad-frequency BDS observations

TL;DR: The results show that the multi-frequency BDS observations will greatly improve the PPP performances and theoretical comparison of the models, positioning performances, precise time and frequency transfer, ZTD, inter-frequency bias (IFB), and differential code bias (DCB) are presented and evaluated.
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Stochastic Park-and-Charge Balancing for Fully Electric and Plug-in Hybrid Vehicles

TL;DR: A stochastic balancing algorithm is presented to reduce the potential for excessively long queues to build up at some charging stations, although other charging stations are underutilized, and is fully decentralized and facilitates a plug-and-play type of behavior.