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Alpha complete!
01/27/2017 at 07:19 • 0 commentsAfter a few months hiatus, I've resumed work. The project is now (essentially) alpha complete. This means that it can detect meteors, save those detections to a server, collect different meteor events, sort them into coincident events, and triangulate their position. Great news!
Despite there being other software out there capable of doing what I'm setting up here, I've decided to go forward with design.
There's still lots of work that needs to be done however. Multi frame tracking isn't done (we take an average of all event frames), so we haven't calculated landing trajectories or entry orbits. There's still no proper local server for setup and remote server for processing. Also the config needs to be moved from an .ini file to a sqllite database to facilitate setup and configuration. Also there's very little in the way of false positive management. Nothing to account for airplanes or sattelites.
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Choosing the camera
07/11/2016 at 03:36 • 0 commentsCurrently the best camera option I have is the raspberry pi camera. With a long enough exposure I can get actual images of the stars. It's only really sensitive enough for fireball type meteors however which isn't great.
I've tested with a DSLR, but its considerable overkill and the Pi has trouble processing the large images.
Facing these issues I searched ebay for an inexpensive low light USB camera and found the AR0130. Unfortunately, this camera is not as good as advertised and the images were of poor quality.
I think that a standard digital camera may be a good option and I'm going to start hunting through those.
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Relative Completeness
07/07/2016 at 23:08 • 0 commentsI decided to move forward getting the basic system complete. It is now capable of capturing meteor events and storing them to a local database. The local databases can be compiled and parsed by a server side system that detects which meteor events correspond. Basic functionality is as follows:
1. Get all events
2. Compile events per user into sequences that are of the same meteor
3. Compare these sequences between users using time between events to create collections that happened at the same time.
3. Further reduce collections by calculating the shortest line between two skew lines and if this is less than a threshold, these sequences are of the same meteor
4. Calcuate shortest lines for all permutations between skew lines for each camera that saw the same meteor. For all of the shortest lines reduce them to a single x,y,z point that lies in the middle.
5. Average the points together.
6. That is (approximately) where the meteor is in the sky!
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Update 2
06/27/2016 at 22:14 • 0 commentsThanks to the user texane, I've been directed to a much more thorough and well built version of what I'm trying to accomplish (https://github.com/fripon/freeture). I've sent them some messages with the hope that I can contribute some of what I've done here.
That being said, I'm still going to try getting all of the pieces working (at the most basic level at least). I'm going to use this as a learning experience with the hope that the techniques I use, while simple, may at least be of use to others.
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Log Entry #1 - Introduction
06/25/2016 at 00:47 • 0 commentsThis is a project I've had kicking around for a little while now, but am only recently starting to hit hard. Many of the basic components are already functional. The system will run, detect meteors (as well as any bright flashing light in the sky), and log them to a database.
All that's needed is a computer and a OpenCV compatible USB camera.
Next steps for the project are:
- Gather more data
- Refine detection algorithms (robustify against clouds, airplanes, moon, etc)
- Camera calibration
- Build up triangulation algorithms
- From here there is calculating landing zones and orbital trajectories
- Build up server
- API, frontend, and backend
-Algorithm for determining location and orientation based on star location and time (see astrometry.net)
- Any other cool things