From the recordings.

Real recordings, measured frequency curves, and candidate maps. Each figure shows a different part of the search; a high score alone does not establish a location.

Livermore, California

The automatic MP3 search and a configured run of the same recording. Both produced ranked candidates without accepting a location. Read the experiment.

Automatic real MP3 analysis with the observed Doppler curve and ranked locations on a Livermore satellite map — Recorded audio and ranked candidates. The run remained inconclusive.

Configured Livermore search showing a recorded flyover and a bounded map of candidate microphone positions — The same recording with configured event settings. No location was accepted.

Reading the frequency.

Measured tones and the aircraft models fitted to them.

Recorded aircraft Doppler ridge and a fitted straight-pass curve — A moving tone in the recording, with a fitted straight-pass curve.

Observed aircraft spectrogram with a best-fitting sound propagation model — A trajectory-based prediction over the recorded spectrogram.

Second recorded flyover with cyan Doppler model over the descending frequency ridge — A flight-path prediction laid over another recorded frequency ridge.

Finding the flyovers.

Automatic discovery across an entire recording, then a closer look at grouped acoustic traces.

Whole-recording discovery showing candidate moving-frequency traces over recording time — Moving-frequency proposals found by the detector; proposals are not confirmed aircraft.

Frequency traces grouped into a canonical acoustic episode over 60 seconds — Related tones are grouped so harmonics do not count as independent flyovers.

Searching the map.

Each point is a possible microphone location. Color shows the fit score; the star marks the highest score.

Read the method

Geographic grid colored by location fit score, with the highest-scoring position marked by a red star — Color encodes fit score, not location probability.

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What connects these figures?Understand the method