I’ve been working with @BSE to try to use SatNOGS observations to understand how the orientation of EQUiSat is changing during a pass. We think we can compare the simultaneous receptions of a single packet at multiple ground stations to infer how the rotation of the spacecraft is aiming the antenna.
I’ve written a blog post describing the idea at http://blogs.brown.edu/umbricht/2018/11/08/triangulation/
-mikeu
Part two of my blog post on simulating the rotation of the satellite and the antenna pattern intersecting the satnogs ground stations. https://blogs.brown.edu/umbricht/2018/11/14/slicing-the-network/
Both posts are very interesting! Thanks for sharing them.
I would be very interested to know if there is anything that could help your analysis and make the calculations easier.
There are two changes under planning and implementation that probably could help. The first one is to send waterfall as data and not as an image and the second one is to add in metadata more accurate timestamps of the demoded data and the ones of the start and the end of the observation.
Thanks! The lossy compression of the image will reduce the information available in the observation so having the raw data would be a great help. We could download the audio and analyze it but this would save us a step and might also be of use to others.
We’re planning to scan the data for an elongated point spread function. This is a very unique signature (ie. 12.5 khz by x milliseconds every y seconds) that stands out above the background noise. It would also make it easier to see an extremely weak signal detection that is not obvious visually in the waterfall plots. Theoretically it could even be used to automatically vet an observation if you know the expected transmitter bandwidth, packet duration, and tx interval. The dB volume within that psf ellipse compared to the average background noise gives a robust measure of snr for each reception.
We’re still working on a method to demod the proprietary encoding of the XDL Micro transmitter. For now we are just looking at detection versus missed packets. Then we’ll estimate signal strength as it changes during a pass for each station.