Advanced Meteor Analysis

NB : Although you can do fireball data reduction on the Pi, it is very slow. I therefore strongly recommend you install the RMS libraries on your PC or Mac instead. To perform multistation analysis you will also need the WMPL libraries. Installing RMS and WMPL is explained in the github repos for each of the products (here and here).

Manual Reduction

Sometimes the RMS software will miss a meteor, or it will be too bright / complex to analyse. However you can manually reduce the data using tools built into RMS.

The following is condensed from Denis Vida’s excellent video tutorial here.

  • Create a new folder on your PC – lets call it c:\manual
  • Copy the FF file, platepar file and .config file from your Pi to this folder. If there’s a fireball file (FR file) copy this too.
  • enable the RMS python environment.
  • In the RMS directory run the following
    python -m Utils.SkyFit2 C:\manual\ -c c:\manual\.config
  • This will open the manual meteor analysis window.

  • Firstly, you should check the platepar.
  • The initial screen shows you where the platepar thinks you are pointing. If the red markers are nicely on top of the real stars, all is fine. Otherwise you should recalibrate the platepar.
  • Use the mouse scroll wheel to zoom in and check. If the patepar is inaccurate follow this process:
    • If necessary, use the keys a/d/w/s to move the map around. Other keys rotate and stretch the view.
    • When pretty close, press Ctrl-R to enter star-picking mode, then Shift-Z to create a mini zoom window.
    • Click on a star. You should see two crosses appear, a yellow one on the real star and a blue one on the red circle that the software thinks is the corresponding star in the map.
    • If the right reference star was selected, press enter.
    • If the wrong star was selected, press escape and try again. Aim to get both star and target in the circles in the zoom window. Avoid double stars where the software might get confused.
    • Repeat this for at least 20 stars, covering all parts of the sky.
    • After you have about 20 stars matched, press Ctrl-Z to recalculate the plate. Press Alt-tab to switch back to the window you started SkyFit2 from and you should see the results of the fit. Aim for a accuracy of < 1 pixel and a few arcminutes.
    • If the plate looks good. Press Ctrl-S to save it. Otherwise you can right click to deselect stars, or left-click to add more.
    • Once you’ve finished doing the platepar, press Ctrl-R to exit star-picking mode.

  • Now you can do manual reduction.
  • Select the Manual Reduction tab.
  • We are going to identify each frame that contains the meteor and mark the location of the “centroid”. The centroid is the middle point of the visible meteor as best we can estimate it. We will also mark the area covered by the trail so we can estimate magnitude.
    • You will notice that when you move the mouse around the message bar at the bottom shows the RA and Dec, Alt and Az etc. This indicates that the platepar has been loaded.
    • Use the cursor keys to find the first frame which shows the meteor. Up and Down arrows move 25 frames at a time. Left and right move one frame. You can zoom in with the mouse scroll wheel.
    • Press Ctrl-R to enter point picking mode. Now zoom in on the area containing the meteor.
    • Left click where you think the centroid is. The software will try to guess. If the guess is clearly wrong, hold the Ctrl key and click again and the marker will move.
    • Hold down shift and left-click to shade in the meteor track that’s visible in this frame. Shift-right-click will rub out.
    • Go to the next frame and repeat. Do this for each frame containing the meteor.
    • When done, press Control-S. This will save a new FTPDetectInfo file containing the meteor position and brightness.
    • You can now quit SkyFit2

Output of Manual Reduction

  • Manual reduction creates the following files:
    • A new FTPdetectinfo file ending in “_manual”, and a revised platepar, containing the revised RMS data and alignment data.
    • A file ending in “.ecsv”. This is a common data format that can be used to share data with other networks. The ECSV file can be used with other ECSV files in the Multistation analysis mentioned below.
  • If you want to, you can merge the revised FTPdetect and platepar into the original FTPdetect and platepars_all files, though its a bit tricky. You will need to find the section in the original FTPdetect file that contains the details of this specific event and replace them, then do the same in the platepars_all_recalibrated.json file. Make copies before you start so that you can restore them if you make a mistake. If the event was missed by RMS, then you can add a new section to each file by following the pattern of existing sections.

Multistation Analysis

This is the manual process for calculating orbits and trajectories. To do this analysis you need data from at least two cameras in different geographic locations.

Method 1: Using WMPL

WMPL Is written by the Meteor group at the University of Western Ontario (UWO). This team were part of the group who set up the Global Meteor Network and the library uses more up to date analytics than UFO.

  • Download the WMPL from github here. Carefully follow the instructions to install it.
  • Create a folder to contain your data.
  • Within this folder, create one folder per camera, named with the camera name.
  • Within each camera folder, create a folder named for the night the data was captured. The folder name must follow the same convention as the RMS ArchivedFiles folders
  • Note that the folder names must be in this format. If the structure is incorrect, or folder names diverge from this, the data will be ignored. (The precise time is not important, but it must be present in the foldername. )
  • So for example if you have data for UK0001 and UK0002 and UK0003 for the night of 2021-08-13 you would have the following folders
    c:\mydata\UK0001\UK0001_20210813_210000
    c:\mydata\UK0002\UK0002_20210813_210000
    c:\mydata\UK0003\UK0003_20210813_210000
    And each folder would contain the FTPDetect file and platepar for that camera for that night.
  • If you only have data from one day, you’ll also need to create an empty dummy folder for the previous day. Choose one of the cameras and create a dummy folder eg e:\mydata\UK0001\UK0001_20210812_210000.
  • Copy the ftpdetect file and platepars_all_recalibrated.json for each camera and night into relevant folder along with any ECSV files you may have obtained. No other files are needed
  • You can process multiple nights, just create more night-folders and put the required files into them. You can even keep the old data, the tool remembers which data it has already processed and will ignore it unless there are new detections of the same event.
  • Now open a command prompt, change folder to the location of WMPL, and activate its python virtual environment.
  • There are two ways you can now proceed:
    using CorrelateRMS
    • This uses the FTPdetect and platepars files and is best used for combining RMS data.
    • Run the correlation process as follows:
      python -m wmpl.Trajectory.CorrelateRMS c:\mydata -l
    • The -l (minus-ell) parameter requests graphical output as well as a table of data.
  • Using ECSV
    • This uses the ECSV files and is best if you have data from other networks or have manually reduced every dataset you want to analyse.
    • Run the correlation process as follows:
      python -m wmpl.Formats.ECSV -l -x -w c:\mydata
    • By default, ECSV will try to run 100 simulations. This may take a long time so you can reduce it using the -r parameter eg “-r 20” would restrict it to 20 simulations.
  • Either process will evaluate your data, identify any matching events, solve for their trajectories and orbits, and create output in a new folder. CorrelateRMS will create a folder called “trajectories”, ECSV uses a different name but it will be obvious.

Method 2: using UFOOrbit

NB: UFOOrbit is closed source software that is not transparently maintained, While its regarded as reasonably accurate, the mathematics is obscure and believed to be very out of date.

  • Create a folder to hold the analysis data.
  • Copy all the CSV files to this location
  • Open UFOOrbit, and click the […] symbol next to “Read M.csv”.
  • Select the folder containing your CSV files, then click “Read M.csv”
  • This will load and process the data. If you have any matches, then you’ll see this in the title bar, and you can select and view the output.

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