Analyzing Space Debris With the Svalbard Radar

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!

Comments

  1. Greetings. I know this is somewhat off-topic, but I was wondering if you knew where I could get a captcha plugin for my comment form? I’m using the same blog platform like yours, and I’m having difficulty finding one? Thanks a lot.

    AWS Interview Questions And Answers

    AWS Tutorial |Learn Amazon Web Services Tutorials |AWS Tutorial For Beginners


    AWS Online Training | Online AWS Certification Course - Gangboard

    AWS Training in Toronto| Amazon Web Services Training in Toronto, Canada

    ReplyDelete
  2. We have good game slots best casino games in history Get winnings here and now.

    ReplyDelete
  3. Разноцветная светодиодная лента или как ее еще называют светодиодная лента rgb наверое одно из лучших изобретений которое придумали люди, очень забавная штука.

    ReplyDelete
  4. Resources like the one you mentioned here will be very useful to me ! I will post a link to this page on my blog. I am sure my visitors will find that very useful
    AWS training in chennai | AWS training in annanagar | AWS training in omr | AWS training in porur | AWS training in tambaram | AWS training in velachery

    ReplyDelete
  5. it is really wonderful and awesome thus it is very much useful for me to understand many concepts and helped me a lot. it is really explainable very well and i got more information from your blog.
    python training in chennai

    python course in chennai

    python online training in chennai

    python training in bangalore

    python training in hyderabad

    python online training

    python training

    python flask training

    python flask online training

    python training in coimbatore


    ReplyDelete

Post a comment

Popular Posts