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Showing content with the highest reputation on 02/22/2021 in Posts

  1. You’d be forgiven for thinking that receiving data transmissions from orbiting satellites requires a complex array of hardware and software, because for a long time it did. These days we have the benefit of cheap software defined radios (SDRs) that let our computers easily tune into arbitrary frequencies. But what about the software side of things? As [Dmitrii Eliuseev] shows, decoding the data satellites are beaming down to Earth is probably a lot easier than you might think. Well, at least in this case. The data [Dmitrii] is after happens to be broadcast from a relatively old fleet of satellites operated by the National Oceanic and Atmospheric Administration (NOAA). These birds (NOAA-15, NOAA-18 and NOAA-19) are somewhat unique in that they fly fairly low and utilize a simple analog signal transmitted at 137 MHz. This makes them especially good targets for hobbyists who are just dipping their toes into the world of satellite reception. [Dmitrii] doesn’t spend a lot of time talking about the hardware in this post, only to say that he’s using a SDRPlay with what he describes as a poor antenna. He provides a link for information on building a more suitable antenna, but the signal is strong enough that an old set of “Rabbit Ears” will do in a pinch. From there he goes over how you can predict when one of the NOAA birds will be passing overhead, and explains how to configure your SDR software to capture the resulting signal. From there, it’s a step-by-step guide on how to make sense of the recorded WAV file. With the help of the scipy library, it’s surprisingly easy to load the WAV file and generate some visualizations of the signal within. Since it’s analog, it only takes a bit more work with the Python Imaging Library (PIL) to convert that into a 2D image. [Dmitrii] notes that using the putpixel function isn’t the most efficient way to do this, and gives some tips on how you could speed up the process greatly, but for the purposes of the demonstration it makes for more easily understood code. Of course, there are already mature software packages that will decode this data for you. But there’s something to be said for doing it yourself, especially since these NOAA satellites won’t be around forever. The new satellites that replace them will certainly be using a more complex protocol, so the clock is ticking if you want to try your hand at this unique programming exercise. source: Decoding NOAA Satellite Images In Python | Hackaday
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