Geolocation by aeroplane sound Doppler shift

GM4AJK

Senior Member.
For those MBers that like the geolocation exercises here's a rather fancy technique I just saw on a YouTube video:

External Quote:
This video examines the amount of location information carried by inaudible background sounds, using the Doppler effect to locate a reference recording within ~100m, and only needing (in some cases) less 1-min of audio. This video raises awareness of these capabilities and closes by discussing preventative measures one could take.

Methodology: Aircraft position, altitude, and velocity data were sourced from ADS-B data and filtered in Python using ICAO type-code classification for propeller vs jet types. For each candidate location on a 200m grid, the closest point of approach (CPA) and sound propagation delay were computed from 3D slant distance, using a digital elevation model (DEM).

Doppler curve spectrogram measurements constrained each event's velocity and CPA slant distance. Candidates were then filtered by the 920-second offset between two flyovers, plus a silence constraint. The exact Doppler curve each candidate would hear was modelled, using emission-time radial velocity from interpolated ADS-B data.

Modelled doppler curves were scored against the observed spectrogram using a locked two-event scoring method. This corrected for measurement error on CPA time & fundamental frequency, while preserving the purely physics-derived temporal offset between the two events.

The pipeline was repeated again for a single 1-min clip of known time, US-wide search, and again, successfully scored the true location 1st.

Lastly, preventative measures were assessed, including rationale behind why common signal processing fixes fail (high-pass filtering, drowning out, and phone call compression/noise reduction).

This video is an educational demonstration of acoustics, signal processing, and data analysis using publicly available data. No code or tools are being released.

That last comment, "No code or tools are being released"... sounds very much like a challenge ;)


 
It's a cool "I wish I had thought of that" idea. And I think it would be pretty easy for an AI agent to implement once the idea is described. I'll let it have a bash at putting it in Sitrec.
That would be interesting and useful.

Additionally, remember all those "New Jersey Drone" videos? Well, using this technique would probably allow for much better evidence, when matched with the flight, that it's actually a plane, as it's said to be.
 
It's already done the basic spectral analysis (sitrec already had one), and identified flyover curves.

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This just showed up on my feed and I went to Metabunk immediately to see if there was already a discussion.
I sat down with my cocktail after seeing this earlier to day out in the shop and was going to share it. I thought I was going to be so clever. Of course Mick already has a version in development.
 
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