Excellent write up and an enjoyable read! Reminds me of the “good old times” where posts on HN were written by humans and with a specific writing style like yours. You could’ve used a little bit more of geoguessing to narrow down results, or do a brute force visual check on the last hundred or so ;-)

For drones and missiles, this technique is known as Terrain Contour Matching. If terrain contour are measured optically, navigation is independent of RF jamming, unlike GNSS.

https://en.wikipedia.org/wiki/TERCOM

Super fun! Interestingly, this is how JPL was able to significantly reduce the Mars 2020 landing radius on Mars. Cameras onboard take pictures of the terrain and match that to maps to figure out where the lander is. https://www-robotics.jpl.nasa.gov/what-we-do/flight-projects...

OpenStreetMap data really is a godsend for such OSINT purposes. Works much better in populated areas too, with more features like roads, shops, electric lines that can be used to search.

This is awesome. I worked on something similar a few months ago. It is a general purpose navigation system based on TERCOM and dead reckoning - https://github.com/deepanwadhwa/anumaan

I find it highly ironic that his is the second article on the main page right after "avoid building technologies that could be used by a police state".

A help with this is the sun is to the left and it seems to be midday, so you could answer the "cardinal direction" question just from the picture with "west ish", which is what it turns out to be.

People liking this post will probably like this [1] and especially these [2] from the channel. All solved using algorithms and map data.

[1] https://www.youtube.com/@colsto

[2] https://www.youtube.com/watch?v=eY-W9gmwxhg https://www.youtube.com/watch?v=nzytWZPyuEw https://www.youtube.com/watch?v=rkmXs_7hELg

Really great article! OP, you did an awesome job breaking down a complex problem into manageable chunks and synthesizing the solution.

Excellent read, I loved it.

Incidentally, the image seems to be the one the resort uses on their website! https://oanresort.wixsite.com/chuuk

What do you mean by no LLM generation if an LLM did all the coding based on reading through the .py files? Pangram isn't kind to "your" text either.

It’s interesting that most top contenders don’t pass the eyeball halo check, seems like there’s room to optimize that filter in code.

I read all the process, literally awesome, i don't do OSINT (i know only what is this) and i think that's very cool

Awesome write up! This is now one of my favorite articles on HN.

Good article! Off-topic, Is Palantir doing the same thing with its internal software to geolocate?

This is beyond impressive. Very good work!

> NOTE: this is a genuine human work, didnt use LLM generation.

I'm sorry, but I don't believe this. The article reads like LLM text post-edited by an AI prompted to "write like a non-native English speaker, replace you for u, make errors, etc".

The other pages on your site are cough, "the smoking gun". For instance, your "Suckless, single binary, zero-dependency CUDA/C++ inference engine for NVIDIA's DVLT. Reconstructs 3D scenes from a handful of images (depth + rays + camera pose => point cloud), no python, no torch, no framework." project.

@yassa How long did this take?

> NOTE: this is a genuine human work, didnt use LLM generation.

A million upvotes from me.

That's kind of seed finder but in real life

What about tides? Would the outline of the island be different based on the time of day.

great blog and great writeup

Nice, but Rainbolt would do it in under a minute ;)

this is really cool. fun little problem turned into great write-up, and i love that you included the code snippets. thanks for sharing

Good job, Yassa. This is how you get a job in the AI age.

really impressive, could that be the way to locate yourself without GPS? assuming we know more/less where we are

Not glamorous but it works

Loved it.

impressive

All of this to not use Google images

This is the real takeaway