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.