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Range-Velocity-Acceleration matched filterbank output for the Svalbard Radar. The colors scale ranges from SNR=0 to 100. The x-axis is range (100 to 3000 km), and the y-axis is time (0 to 200 seconds). The coherent integration length is ten 1.92 ms transmit pulses, with 20 ms inter-pulse periods. How many space debris objects can you see? I can see about 9. This to indicate that my new analysis is working quite well, as this would result in about 160 detections per hour. |
I've been writing some code to do Range-Velocity-Acceleration matched filtering of moving space objects from Arecibo radar data. The processing is heavier than the usual EISCAT beampark analysis. The Arecibo coded long pulse requires analysis with 150 meter range resolution. I estimate that I will need to use 300 CPU hours to analyze one hour of actual data. This is why I've parallelized the code with MPI, so I can run it on the Stallo cluster. Most of the code runs on Python (mpi4py), but I had to implement the critical part using a little snippet of C. I've already managed to successfully submit a test job, but I'm doing a few more tweaks before I kick off the big run.
The code seems to be working, but I want to make sure that everything works right. I'm therefore reanalyzing Svalbard (32 m dish, 500 MHz frequency) data, and comparing the results with Jussi Markkanen's analysis. Here's a plot from the Svalbard re-analysis. This particular 200 second time window caught quite a few detections. The hourly rate would be 300 debris detections per hour!
Avoid surprises — interviews need preparation. Some questions come up time and time again — usually about you, your experience and the job itself.thanks a lot.
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