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Cool! I had a similar topic for my master thesis where I predict GNSS Shadowing and HDOP Maps to plan HDOP optimal routes.

Here is a working implementation to do GNSS shadowing with GPS, Galileo, and Glonass using OpenstreetMap 3D Export of buildings and terraing.

https://github.com/xaedes/GNSS-Shadowing

It is written in C++ and has a working python binding. But the interface is extremely polished. The ideas behind it are simple though: Satellite trajectories are computed using SGP4 from publicly available TLE files. The current ones will be downloaded from cmake. Some coordinate system transformations later a simple software shadow rasterization (in layered 2D map) algorithm is performed with 3D data pulled in from .obj files that are generated from OpenStreetMap. Dilution of Precision values are calculated from visible satellites for each rasterization point. The shadow information can also be used to do shadow matching.

Maybe someone has a use for this^^




Edit: It should mean: "the interface isN'T extremely polished". Not the opposite. Messed up my last edit and didn't see the mistake until now, sry^^


Hey, this is excellent work! Feel free to email me at iland at uber.com if you are interested in working on GNSS Shadowing at Uber.


Hi, this is a bit of a random one, but I have product that relies on GPS accuracy, and would love to hear if you guys have any ideas on how I can improve this, as well as my current implementation. Mind if I drop you an email? Cheers.




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