How Can Orekit Handle Elevation Variations More Effectively in Complex Geographical Calculations?

I’ve been exploring Orekit for some time now, and I’m really impressed by how it simplifies a lot of satellite-based calculations. It’s such a useful tool for those of us who are trying to understand orbital mechanics, especially when dealing with complex satellite tracking tasks. However, as I’ve been using it, I noticed something that seems to be a bit of a challenge for me when dealing with geographical coordinates, specifically the role of elevation.

One issue I encountered is when trying to calculate precise positioning over varied terrains, especially when the elevation changes drastically. It feels like Orekit handles flat or relatively even terrains quite well, but when it comes to locations where the elevation shifts dramatically, such as mountainous regions or areas with complex topographies, the tool doesn’t always give the clarity I’m hoping for. I’ve been thinking about how this could be managed better within the framework of Orekit.

For instance, I’m particularly curious about how Orekit treats elevation data when performing ground station visibility calculations. From what I understand, it uses reference frames and geodetic coordinates, which is great for many calculations. But how does it handle stations located at significantly higher elevations, or stations that experience varying altitudes? I wonder if anyone else has noticed this potential gap or found creative ways to adjust the tool to factor in these variances more seamlessly.

I’m also thinking about the timing of passes over these high-elevation areas. For example, wouldn’t it make sense that satellites passing over high-altitude ground stations would appear to have longer visibility due to their elevated location? I’m not sure how Orekit factors this in – or if it does at all – but I’d love to know more from anyone who has insights or experience in this area.

One of the things that inspired me to think more deeply about elevation is how important it is when determining accurate satellite coverage for regions with substantial altitude variations.

Elevation, in geographic terms, refers to the vertical distance of a point on the Earth’s surface from mean sea level. This measurement is critical because it impacts so many aspects of satellite visibility and communication. Whether for satellites or ground-based calculations, understanding elevation is essential.For instance, an accurate elevation tool for hikers and travelers can be vital for navigating mountainous terrains, just as accurate elevation data plays a crucial role in ensuring precision in satellite communications. The tool does a great job with many aspects, but I started to wonder how I could adjust my approach when considering areas that aren’t close to sea level. It made me think positively about how important elevation is in so many fields, especially in satellite and geographical calculations.

That said, another concern I have relates to the computation of Line of Sight (LoS) for ground stations that are not only at higher altitudes but also positioned near obstacles like hills or mountains. How does Orekit take into account natural barriers that might obscure the satellite’s signal, particularly when the terrain is highly uneven? Does the tool give enough flexibility for users to input custom elevation profiles, or does it rely on standardized global models that might not be as accurate for certain regions?

It would also be useful to understand how atmospheric refraction impacts satellite signals when factoring in elevation changes. Higher elevations generally have thinner atmospheres, and I’ve heard that this could potentially alter the refraction of satellite signals. Does anyone know if Orekit compensates for this, or do I need to manually adjust the parameters based on elevation for better results?

I’d love to hear from others about how you’ve dealt with elevation in your own work with Orekit, especially in scenarios where precise location matters. Have you run into similar situations? What steps have you taken to adjust for elevation in your calculations? Are there additional features within Orekit that I’m missing which could help streamline this process?

It would be really helpful to get some feedback on how other users are navigating these terrain-related challenges. Maybe I’m not using all the tools Orekit offers, or perhaps there are best practices I haven’t thought of yet. I’d really appreciate hearing your thoughts and experiences.

Thanks in advance for any advice!

Using Azimuth and Elevation data, you can build a custom Elevation Mask for an ElevationDetector.
See ElevationMask (OREKIT 12.1.3 API)

However I have not implemented this before, maybe someone else can provide an example?

Hello, I am also quite new to Orekit and so perhaps not the best to answer, but the short answer is that yes, of course Orekit has all this flexibility. I don’t know if there are associated tools that will automagically load Bing Maps for terrain data (if some facility or open source project exists to do so, I would be interested), but I believe everything you are asking is done via the ElevationDetector. Azimuth-Elevation constraints around a ground station are done via the ElevationMask class. See the test method testEventForMask() here for an example: orekit/src/test/java/org/orekit/propagation/events/ElevationDetectorTest.java at master · treeform/orekit · GitHub. To my eye it appears the mask is created similarly as is done in STK, with the azimuth described from 0 to 360 degrees (although be aware that Orekit uses radians everywhere!) with the specified elevation angle applying from one azimuth degree entry to the next. So yes, for any given point you can describe the lat/lon and altitude along with an AzEl mask of the surrounding terrain. Considering atmospheric refraction can be done as well with the detector; it is not active by default. Hope that helps.

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I should add that if you are using the Python wrapper, I can save you a bit of Python-Java interop pain by noting that the pyhelpers module has a method called to_elevationmask which handles the incantation for you. python_files/pyhelpers.py · master · Orekit Labs / Orekit Python Wrapper · GitLab

from orekit.pyhelpers import to_elevationmask is all you need to access it, and it helpfully converts input degrees to the required radians.

Most likely it is no accident that this is among the few included helper methods; sometimes the required interop magic is not so obvious.

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