Raw I/Q capture of GRAVES reflections caused by 2023 Perseids
<p>Raw I/Q capture of the radar reflections originating from the <em>Grand Réseau Adapté à la Veille Spatiale</em> (GRAVES) radar in the 143.050 MHz frequency, and caused by the meteor ionisation trails during 2023 Perseids meteor shower. The file format is 2 x float32 (cf64), little endian and the sample rate is <span class="math-tex">\(f_s=1.92\text{ Msps}\)</span>.</p> <p>The capture was obtained from an <a href="https://es.aliexpress.com/i/1005003181244737.html">AntSDR E310</a> in 2r2t mode, tuned to 143.3 MHz. The antenna consisted of a minimal array of two <span class="math-tex">\(\lambda/2\)</span> vertical dipoles, with a <span class="math-tex">\(\lambda/2\)</span> spacing between both, with a design frequency of 143.050 MHz. The location of the antenna was 40.45342176913288º N, -3.408497019619436º E</p> <p>The file was produced with SigDigger's "Pluto/ANTSDR 2RX combined source", provided by the <a href="https://github.com/BatchDrake/AntSDRPlugin">AntSDR plugin</a>. This custom signal source modulates the samples of RX1 and RX2 by <span class="math-tex">\(-f_s/4\)</span> and <span class="math-tex">\(f_s/4\)</span> respectively, and sums both. This results in a spectrum that, once visualised from SigDigger, seems duplicated around the central frequency.</p> <p>This representation enables simple manipulation of both coherent channels with the existing software infrastructure: if we wanted to compare the phases of a channel at frequency <span class="math-tex">\(f_0\)</span> coming from both antennas, we would see the signal coming from RX1 at <span class="math-tex">\(f_0-f_s/4\)</span> and the signal coming from RX2 at <span class="math-tex">\(f_0+f_s/4\)</span>. It would suffice by multiplying the samples by two NCOs that cycle over phases <span class="math-tex">\(0,\pm\pi/2,\pi,\mp\pi/2\)</span> and applying an appropriate low-pass filter and decimation to the output of both.</p>
ShareScore
36/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 8
- Engagement
- 0
Topics
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