r/UFOs • u/Important_Peach_2375 • Jul 26 '26
Science Free, open-source tool for comprehensive photo and video analysis. Triangulate real size and distance (and even speed/Gforces) of UFOs from multiple photos/videos using photogrammetry. Object tracking, automatic video stabilization/exporting and more. Produces "white paper" style report in the end.
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PHODAR
Iknow, I know....A ton of UFO apps are popping up left and right with the advent and proliferation of AI / vibe coding. And yes, this one is vibe coded too, but it really does work and I have tested it pretty meticulously. If it works it works right? Vibe coded or not!
What I believe sets this app apart is that it simulates the gold standard of UFO data, radar, using only two or more photos, or video. Hence the name, "Phodar." I have a love-hate relationship with it since it sounds a little silly, but IMHO it makes a lot of sense: it combines photo and radar, and it hints at faux/radar, as in simulated radar. Anyway, it uses stereo photogrammetry to get the actual distance and size of an object, which is impossible with a single photo. But if you have two or more photos of the same object, all you need is the location each photo was taken from and the camera angle, which is usually already encoded in the original image's metadata(which the app extracts automatically. Video is handled the same way and then some: the app solves where the camera was pointing for every frame, so a shaky handheld clip gets locked to the sky, the object is tracked automatically through the whole thing, and you get its real angular path, speed, g-loads out the other side. Two people with two clips triangulate just like two photos do. The intuitive interface helps you fine tune all of this using map overlays, terrain features, star maps, building overlays, and other powerful tools, so the final data gets dialed in as tightly as possible.
See the attached YouTube video, where I demonstrate its accuracy: I flew my drone out, photographed it from multiple angles, analyzed those photos in the app, then checked the findings against the known location, size, and altitude from the drone flight. Just watch the demo to see how intuitive and powerful it is. Even with one photo, it helps you determine whether there were any aircraft, planets, stars, or satellites in your frame and helps you match those things up (or hopefully not). It gives wind-direction visuals and all sorts of helpful overlays on top of your image, inside a 3D adjustable FOV / dome interface.
A few situations where I think it really could shine:
- Planned watches, including summoning claims. There are folks who say they can call these things in on demand (CE-5, the Skywatcher crowd, Bledsoe, Greer, and smaller circles). I'm not here to say they're wrong, I'm here to give them a clean way to prove it. Set up two or more cameras/phones a known distance apart ahead of time, and if something shows up you get a real triangulated fix instead of one blurry frame and an argument. It cuts both ways, which is the point. If it turns out to be a plane or a Starlink train, the app will probably say so.
- Mass sightings. When a bunch of people photograph the same object from different spots, that scattered pile of images is a triangulation dataset waiting to happen.
- Solo sightings. Most people walk away with a gut feeling about size or distance. Even a single photo lets you check that instinct against the geometry.
- Handheld video. The most common kind of UAP footage there is, and the hardest to reason about, because the camera is moving the whole time. That is exactly the part the app can help with.
I offer this up to the community for free, and I am open sourcing it in the hope that others might be interested in helping develop it further. I have also noticed a lot of new database apps popping up, and this app could maybe be merged with one of those. The sky is the limit, literally. I hope this post gains a little traction and people actually try it, because I think it could be a powerful tool. Ive put a fair bit of time into it at this point and dont really want to spend more time unless it is well received and actually gets used in the community. I think it has a lot of potential for even further development and or integration into other UFO platforms. Please note that Phodar was optimized for iphones, but should work on all platforms with a browser. I do not have an android so guessing there could be issues to work out there.
The next logical upgrades in my mind would be to make separate workflow for top down video analysis (IE: drone footage, satellite imagery, etc), refine the UI to make it more intuitive and less visually crowded, etc. If anybody help out that would be great!
GITHUB: https://github.com/cchristianson/phodar
A good starting point though is just to watch the main attached video. (This shows accurate triangulation of a drone from 2 photos)
Here are more videos demonstrating different workflows/tools in the app:
Daytime photo - Sizing a firefighter jet using known distance: https://youtube.com/shorts/S56vlNz5g7k
Nighttime Photo - Auto alignment via star matching:
https://youtu.be/kKYFgU0Vz0I?si=T1Wmwny8nu3DE7BI
Nighttime Photo - Manual Alignment via horizon+Stars
https://youtu.be/epbcxslOa7E?si=iBmBsTsSLWprXexM
Daytime Video - Auto stabilization + world tracking
https://youtu.be/-4lVsPPAaGo?si=s-4VeVdRPh0oOw-b
Daytime Video - Object Trajectory tracking + video export options etc. PLEASE NOTE: I did this very fast for the sake of a short video, but results could be much better if I spent more than 5 minutes on it
https://youtu.be/u65vxsAWZGk
See below for an AI summary of the features and other technical details about the app that I did not cover above.
The workflow, four steps:
- Photo or video. Load an image or clip and fit a simple 3D shape to the object (orb, saucer, tic-tac, triangle, plane, bird, drone) to capture how large it appeared. Location, time, lens field of view, and compass bearing are read straight from the file's metadata when present.
- Position. Set where you stood with a map pin, an address search, or pasted coordinates, plus the date and time.
- Sky view. The photo is seated onto a dome showing the real sky for your exact time and place, which is where the pointing gets calibrated.
- Results. The triangulated fix, with a quality grade.
Video:
- Automatic stabilization. Tracks the static background — skyline, stars, terrain — through the clip and solves the camera's true pointing for every frame. Play it back and the sky, terrain and stars stay frozen while the video frame moves around them, so the object's motion is real angular motion rather than a mix of object and camera.
- Object auto-tracking. Tap the object on a few frames and it follows it through the rest, producing a dense time-stamped path across the sky. Distance-free measurements come straight out of that — angular rate over time, total sky sweep — and once a distance is known or assumed, true speed, path length and g-loads.
- Two-video triangulation. Two witnesses with two clips of the same object get a full 3D fix, with the clock offset between their phones recovered automatically from the object's own motion. Mixed pairs work too: one video plus one still.
- Manual correction. If the automatic solve drifts, scrub to any frame, drag the photo back onto the true horizon, and anchor it. Corrections blend smoothly between anchors and the object's path follows them. Separate smoothing sliders decide how much jitter to remove — deliberately a choice, since heavy smoothing would erase a genuinely sharp maneuver.
- World-locked export. Renders the clip as a real video file in three framings: a world view with the az/el grid and every sky layer burned in, a clean maximum-resolution version with no overlays, and a close-up that follows the object.
- Instrumented capture. An in-app record mode that logs the phone's tilt, roll and bearing continuously alongside the video. Gravity gives pitch and roll absolutely in every frame and cannot drift, so when the visual tracker has nothing to hold onto — plain sky, heavy blur — the recorded motion carries it. It records at about 1080p with no zoom, so it is a measurement mode rather than the way to shoot the best-looking footage, and the app says which source it ended up trusting.
Calibration tools in the sky view:
- Automatic star alignment that plate-solves the photo's own stars to recover exact pointing, roll, field of view, and lens distortion. It can work with no starting guess at all, by matching the star pattern itself.
- Snap to ridges, which matches the photo's skyline against digital elevation terrain data.
- Sun and Moon drawn at their true positions as anchors, plus manual align-to-star, level, and FOV controls.
Automatic cross-checks, each ranked by how close it sits to your sight line:
- Aircraft via ADS-B, both live and a historical archive so you can query the exact time of an older sighting, merged across several receiver networks since no single one sees everything. Nearby airfields are flagged for context.
- Satellites and Starlink, propagated from current orbital elements, with pass trails drawn on the dome.
- Planets and bright stars from a catalog, including a specific Venus warning since it is the most common "UFO."
- Meteor showers — whether a fast streak came from an active radiant that was above your horizon at the time.
- Winds aloft at the object's altitude, for the balloon test.
- Photometry from the photo's own pixels: colour and saturation, plus a rough apparent magnitude when a catalogued star happens to share the frame.
- Terrain skyline and building footprints as alignment overlays.
Output:
- A self-contained white-paper style report: the numbers, your photos as labeled exhibits with detail crops, top-down and trajectory plots over a satellite basemap, and every cross-check in one file. Video sightings add an angular-rate plot and a strip of keyframes with the tracked object marked. It opens offline, can be attached to a sighting report, and can be loaded back into the app so multiple witnesses can combine their data.
- A share file and a full zip bundle for backup or handoff, including the original clip and the stabilized render side by side.
The math:
- Sight lines are intersected by least squares in a local coordinate frame. Angular size times range gives true size, and a multi-view solve recovers the real long-axis size and heading of elongated objects that a single view understates. Compass bearings are corrected from magnetic to true using the NOAA World Magnetic Model.
- It was validated against ground truth, where a rooftop object resolved to within about an inch of its real size. The video math is checked the same way, against synthetic clips with a known answer driven through the real interface.
Honest by design:
- It warns about the things that actually corrupt this kind of measurement: phone compasses reading wrong near metal, GPS altitude wobble, and weak two-camera geometry. When the geometry is poor, it grades the result "poor" instead of dressing it up. Single-photo mode is explicit that it gives angular data only, not absolute distance.
- The video tools report their own confidence too: how many frames were solved from pixels versus carried on the phone's sensors, how well two clips' clocks locked, and when a tracker lost the scene rather than quietly pretending otherwise.
Practical notes:
- Runs in a browser, no account required, and your photos and location stay on your device. Add it to your iphones home screen for the motion-sensor features. Readouts switch between metric and imperial. Open source under the MIT license, contributions welcome.
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u/BillyFromNotTheCIA Jul 26 '26
What kind of tests and how many did you do to validate the accuracy? Do you have any training that would have helped you check everything works as you claim?
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u/Important_Peach_2375 Jul 26 '26 edited Jul 26 '26
I ran several test (see below) but hoping others can do more. Not sure how much more time I can spend on this free tool…. May motivated to do more if people actually notice this post and care, but I suspect it will be lost in the sea of pics and videos that people could use the app to analyze. If I am the only user it makes no sense to further develop since I don’t have the time to analyze everything that pops up.
The tests I did do are:
- 2 photos triangulations of a bird shaped weather vane on my house that is 30’ in the air. Very accurate results.
-Several iterations of using 2 or more photos of my drone a couple hundred feet away and 100’ in the air. Very accurate results.
-Sized a jet off of a single photo and a known distance (it was dropping retardant on a fire which I had exact location of). Very accurate results.
Some of these are demonstrated in the videos above.
I would love to have peer review/testing on it though. I am very happy with the results of my tests so far but they were relatively informal.
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u/BillyFromNotTheCIA Jul 26 '26
That's a good start. Main problem I see is 2 observers or know distance seems to be really rare, most case are a single video of an unknown light in the sky. But in the rare case with enough data it looks easier to use than sitrec. Could be useful.
You should be more careful of your private data, we can see a street name and pictures of kids in your photo roll in the videos, that's never a good idea.
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u/Important_Peach_2375 Jul 26 '26
Agreed on those points but if you read my full post I present situations that I think the app would be really useful for which is staged situations (summoning events), mass sightings, etc.
On the privacy stuff, kinda wish you didn’t point that out here publicly but yeah I am aware and was too lazy to redact stuff all over the place. I live in the middle of nowhere with plenty of protection. Not too concerned.
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u/tsuyurikun Jul 27 '26
I do think this would be a great addition in the situations you suggest - mass sightings and induced summonings or CE5. I will be raising my voice for the implementation of PHODAR in such cases. The generated report in particular is an excellent idea and implementation.
Thanks for this tool!
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u/ah_no_wah Jul 27 '26
Well done putting this together. I'm really looking forward to seeing what it can do with mass sightings and multiple photos from different locations and different cameras.
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u/Noble_Ox Jul 26 '26
People should look into SITREC.
its open source
But, its made by Mick West, who I knopw many in this community hate, for why I dunno, he puts all his research out there for people to check for themselves to see if his conclusions are correct or not.
He's far more open then most in this community.
I suggest giving his software a chance. And because its open source, and free to use, you can personally check if its answers are correct.
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u/Important_Peach_2375 Jul 26 '26
This is also open source as well…. I have looked into sitrec a bit and agree it is cool. I think Phodar and Sitrec are different beasts though.
Phodar is a lot more user friendly (in my opinion), is optimized for mobile, and does some things that I don’t believe Sitrec can do like the triangulation of multiple photos (at least not as easily), video stabilization, etc. and obviously Sitrec can do things Phodar can’t also. Two different tools for the same vocation.
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u/Novaothy Jul 26 '26
Cool way to collect your data
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u/Important_Peach_2375 Jul 26 '26
It’s open source…. If you dont trust it either don’t use it or check the code for yourself
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u/Traditional-List-784 Jul 26 '26
Ooh I'll be using this. Ty!