Improved signal processing for LilacSat-2 VLBI

Last week I published my results about the LilacSat-2 VLBI experiment. There, I mentioned that there were some things I still wanted to do, such as studying the biases in the calculations or trying to improve the signal processing. Since then, I have continued working on this and I have tried out some ideas I had. These have given good results. For instance, I have been able to reduce the delta-range measurement noise from around 700m to 300m. Here I present the improvements I have made. Reading the previous post before this one is highly recommended. The calculations of this post were performed in this Jupyter notebook.

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Amateur VLBI experiment with LilacSat-2

On 23 February, Wei Mingchuan BG2BHC published on Twitter the first Amateur VLBI experiment. This consisted of a GPS-synchronized recording of signals from LilacSat-2 using USRPs in groundstations at Harbin and Chongqing, which are about 2500km apart. Wei has made a Github repository containing the recording (in MATLAB file format) and some signal processing in MATLAB. I have done some signal processing of my own with the recording and published my results in a Jupyter notebook. Here I describe some general aspects about VLBI and its use in Amateur radio, and some specific details of the signal processing I have done.

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Studying IONEX files

Many Amateur radio operators are familiar with the effects of the ionosphere at HF frequencies. However, the effects of the ionosphere are also noticeable at much higher frequencies. In particular, at L band, which is used by most satellite navigation systems. Thus, GNSS receivers can be used to measure ionospheric parameters. These measurements are usually distributed as TEC maps in IONEX files.

Here I describe some basic ionospheric physics, how a GNSS receiver can measure the ionosphere, and give some Python code to study TEC maps in IONEX files. Then I use TEC maps to study the CODAR ionospheric observations I did in December last year.

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