Welcome to the Global Meteor Network's wiki page!
The Global Meteor Network (GMN) is a world wide organization of amateur and professional astronomers alike, whose goal is to observe the night sky using low-light video cameras and produce meteor trajectories in a coordinated manner. Here you will find information on the purpose and structure of the GMN, assembling and operating your own meteor camera, contributing to the development of RMS the GMN software, as well as information on how your observations as a citizen scientist can contribute to the further understanding of our solar system's formation and evolution.
- 1 Global Meteor Network Overview
- 2 Meteor Detection Station
- 3 Operating and maintaining your GMN station
- 4 Assembling your camera
- 5 What can I do with my GMN station?
- 5.1 Video Tutorial - Using SkyFit to perform astrometric and photometric calibration
- 5.2 Video Tutorial - Manually reducing observations of fireballs and computing their trajectories
- 5.3 Generating a Google Earth KML file to show your station's field of view
- 5.4 Using UFO Orbit program to estimate meteor trajectories
- 5.5 Urban meteor observing
- 6 Optional RMS Software Installation
- 7 FAQ
- 8 IstraStream
- 9 For More Information
Global Meteor Network Overview
Meteor Detection Station
What is an RMS GMN station?
A RMS-based GMN station that is the subject of this Wiki consists of a Raspberry Pi (RPi) single board computer, a low light level security video camera, and the RMS software package. The camera is securely mounted in a weatherproof housing, pointed at the sky, and connected to the RPi with a POE (Power Over Ethernet) cable. [insert block diagram or Photos here] The RPi is connected to the Internet via WiFi, and to be a part of GMN network, you’ll need a fairly powerful Raspberry Pi (RPi 3B+, RPi 4 or better) and a reasonably fast Internet connection. The internet connection is primarily required to enable data upload to a central server each morning as well as provide automatic updates for the RMS software.
Nightly, the RPi starts recording video from the camera shortly after local sunset continuously compressing and storing the video data locally. Each morning before sunrise, after capture is complete, the RPi analyzes the video and extracts your nightly station’s meteor observations. These extracted video “clips” of detected meteors are then archived and uploaded to a server. The clips can total hundreds of megabytes on a “busy” night (e.g., in a heavy meteor shower, or a night with a lot of false detections--progress is being made on the detection software). The server finds meteors which were observed with more than one station and this enables the server to triangulate the meteor trails in 3D and calculate the orbits of the meteors.
How do I obtain a camera?
Build my own camera system
Can I use a commercial all-sky camera?
Generally no due to the lack of sensitivity. But see this recent experiment
Operating and maintaining your GMN station
Please note that GMS is a nascent operation and you may share some growing pains if you choose to be involved -- we're still working out some bugs and making improvements here, which may be an opportunity to help if you have programming skills! ;-) So note that the workload of day-to-day operation can be non-zero, and might take a little bit of your time.
Ideally, you'll want to monitor your RMS RPi system(s) daily to look for freezes or glitches or other problems... like birds nesting or soiling the camera window, people accidentally unplugging the power cord, mice (or cats or dogs!) chewing on the camera Ethernet cable, etc.
Although we are getting close, this is not a "power up and forget about it" system yet. However, by its very nature, the GMS network is inhabited by a lot of people who are willing to help newcomers getting started. So, here are some clues for daily operation of your RMS camera.
So what does the meteor camera do over the course of 24 hours?
The RMS Python based system calculates the sundown to sunrise interval and schedules video camera capture all night long. Depending on the video camera and capabilities of the RPi, the camera captures 25 or more frames per second between evening and morning twilight. During the continuous image capture, the station begins processing captured image data, doing a pre-screening to target frames with a suitable number of stars (usually around 20) that makes it worth looking for meteor detections. Once data capture has finished, the station switches into processing all the promising frames for detections, then refining the astrometric accuracy of every positive detection. Using the station platepar (plate parameters) calibration file, processing iterates to find the best astrometry and photometry solution for each detected meteor. Once this process has analyzed each detection, summary files are created. These summary files include text file data presentation in several widely accepted formats (CAMS and UFOorbit), as well as graphic plots of detection frequencies throughout the night, a set of thumbnail images of detections, a set of thumbnail images of data captured throughout the night, a single image with all detections stacked together, plots of photometry, astrometry, and camera pointing drift in arc minutes throughout the course of the night as the mount or building flexes, a flat file for correcting images, and a plot of all detections showing any identified radiants. Finally all results are combined into a single compressed archive, which is automatically uploaded each morning to the central server. Optionally, you can create a mp4 movie showing a time lapse of the night’s captured images. Each morning you can review the result files on the RPi, and copy anything you want to your computer or tablet.
Archiving data and backing up configuration
Data backup is as much or as little as you like. Your primary data is automatically uploaded to the central server every morning when data processing is done. We've built some automated tools that can help to back up any additional data to a thumb drive inserted into the RPi.
Viewing the data
Tools and Utilities
- RealVNC or AnyDesk remote connect tool allows station access from anywhere. Access from outside your network is enabled by use of an OpenVPN connection address available to meteor stations.
- Samba data directory access, allows you to copy data results directly from your RPi to your computer or tablet.
- CMN_binViewer can be used to view standard fits image files containing meteor detections. It runs on the RPi, and is also available under Windows.
- FOV3D Meteor camera Field of View visualization tool helps you in aiming your camera so that it may intersect the field of view of nearby stations.
- UFO Orbit allows you to process data from multiple stations and generate unified radiants of two or more stations seeing the same meteor. It can plot the shared object ground path, orbital characteristics, and can output a summary file of all objects seen by more than one station, which can be used for further analysis.
- RMS software can be installed under Windows to allow much of the RMS python-based code to be executed on your computer, so it can be run against meteor station data you have transferred to your computer from the RPi.
- You can run RMS Python jobs on the RPi to sample the image files captured all night long and condense them into a mp4 movie. This creates a sometimes mesmerizing summary that can run for over 2 minutes in length for winter time data.
Assembling your camera
What can I do with my GMN station?
Optional RMS Software Installation
Flash a pre-built image
Please note: Images are available of RMS software pre-installed into Raspbian. Raspbian is the operating system typically used on the Raspberry Pi (RPi) computer. In most cases, there is no need to install RMS into Raspbian yourself, because it is much easier to use the most recent RMS Raspbian image. The current publicly released image of RMS pre-installed into the Jessie Raspbian release is here
This Jessie RMS image is well suited to the RPi hardware version 3+ or earlier, although use of v1 is not recommended.
Work is underway to make a Buster Raspbian release RMS image intended for the RPi v4 hardware, and we hope to have this image available soon. It is being tested now, and should be ready for release in a few weeks. We recommend the RPi v4 with 2 or 4 GB of RAM for Buster RMS.
Many station operators find that a 128 GB microSD card is preferred, although smaller 64 GB cards will also work. The image is flashed to the microSD card using the Etcher utility for Windows, which can be found here
Please note that the pre-installed RMS software images incorporate an auto-updating feature, so that the RMS software is updated to the current release whenever your Raspberry Pi RMS is booted. This way, your station is always running the most recent set of updates. For installations into other Linux or windows environments, executing the command:
will update to the most recent RMS release.
The code was designed to run on a RPi, but it will also run an some Linux distributions. We have tested it on Linux Mint 18 and Ubuntu 16. For information on installing into other Linux releases, check portions of the section listed below for installing on RPi, and also check installation instructions found on GitHub
Install for Windows (Note: Capture and detection will not work under Windows)
What should I back up when re-flashing an SD card?
The .config, platepar and mask files that are in the RMS source directory. If your SD card fails or becomes corrupted, these files can be fetched from the server as they are uploaded every day together with the data.
What are the values in FTPdetectinfo_* file designated as hnr mle bin Pix/fm Rho Phi?
Some of these values are not used in RMS (hnr mle bin), but they are in CAMS, so they are here to conform to the standard. Thus they are all zeros. The others are:
- Pix/fm - Average angular speed of the meteor in pixels per frame.
- Rho, Phi - Parameters that define the line of the meteor in polar coordinates, see here for more details. Rho is the distance of the line from the centre of the image, and phi is the angle of the line as measured from the positive direction of the Y axis (basically a line going from the center of the image to the top of the image), the positive angles are measured clockwise (I think, the CAMS standard might define these parameters a bit differently, the Y axis is flipped).
The intensity is the sum of all pixel intensities of the meteor on a given frame. Let's say I represent an area around the meteor on a given frame like this, where the numbers are pixel intensities on an 8-bit image (so they can range from 0 to 255):
and the pixels values inside the red boundary represent the meteor blob on the frame, the intensity would be the sum of all numbers inside the red boundary. This value is later used to compute the magnitude. The magnitude is computed as: mag = -2.5*log10(intensity sum) + photometric_offset. The photometric offset is estimated in SkyFit by fitting the line with slope -2.5 through pairs of known magnitudes of stars and logartihms of their pixel intensity sum. The photometric offset is basically the intercept of that line. The constant slope of -2.5 comes from the definition of stellar magnitudes.
The IstraStream.com is an independent hosting site which is part of our world wide GMN. It is primarily a host for data from cameras sold by IstraStream, but other station operators can request that their data be included. At this time, data is hosted from RMS stations in over 10 countries, with a geographic span including Europe, North and South America.
For More Information
- Moorhead, A. V., Clements, T. D., & Vida, D. (2020). Realistic gravitational focusing of meteoroid streams. Monthly Notices of the Royal Astronomical Society, 494(2), 2982-2994.
- Kukić, P., Gural, P., Vida, D., Šegon, D. & Merlak, A. (2018) Correction for meteor centroids observed using rolling shutter cameras. WGN, Journal of the International Meteor Organization, 46:5, 154-118.
- Vida, D., Mazur, M. J., Šegon, D., Kukić, P., & Merlak, A. (2018). Compressive strength of a skirting Daytime Arietid-first science results from low-cost Raspberry Pi-based meteor stations. WGN, Journal of the International Meteor Organization, 46, 113-118.
- Vida, D., Gural, P., Brown, P., Campbell-Brown, M., Wiegert, P. (2019) Estimating trajectories of meteors: an observational Monte Carlo approach - I. Theory. arXiv:1911.02979v4 [astro-ph.EP 21 Apr 2020]
- Vida, D., Gural, P., Brown, P., Campbell-Brown, M., Wiegert, P. (2019) Estimating trajectories of meteors: an observational Monte Carlo approach - II. Results. arXiv:1911.11734v1 [astro-ph.EP 26 Novr 2019]
- Vida, D., Mazur, M. J., Šegon, D., Zubović, D., Kukić, P., Parag, F., & Macan, A. (2018). First results of a Raspberry Pi based meteor camera system. WGN, Journal of the International Meteor Organization, 46, 71-78.
- Vida, D., Zubović, D., Šegon, D., Gural, P., & Cupec, R. (2016). Open-source meteor detection software for low-cost single-board computers. In Proceedings of the International Meteor Conference (IMC2016), Egmond, The Netherlands (pp. 2-5).