Classification of Aircraft Type Using Seismic Data in Alaska
Description:
Recent work has shown that seismic data, particularly at frequencies above 10 Hz, often contain abundant acoustic-seismic coupled signals from aircraft. These signals have characteristic time-frequency signatures due primarily to the aircraft’s sound doppler effect and engine features. We use a set of 306 seismic nodal sensors deployed in central Alaska in February and March 2019 to estimate the closest time, closest distance, and speed for a set of 1770 known flights passing within 2 km of a seismic sensor. By estimating these three parameters, we are able to determine the base frequencies (up to 250 Hz) that characterize the aircraft. Our uncertainties can be reduced by taking into account temperature and wind conditions, which affect the sound speed between the aircraft and seismic sensor. The Alaska data set of diverse aircrafts—propeller planes, helicopters, 1940s Curtiss C-46 Commandos, 747 Boeing jets—provides an excellent opportunity to establish and refine procedures for characterizing aircraft from passively recording seismic and acoustic sensors. Our final catalog provides a frequency classification of 141 unique aircraft types that were recorded by our seismic sensors, and our method could be applied in a straightforward manner to other datasets.
Session: Data-driven and Computational Characterization of Non-earthquake Seismoacoustic Sources [Poster]
Type: Poster
Date: 4/16/2025
Presentation Time: 08:00 AM (local time)
Presenting Author: Isabella
Student Presenter: Yes
Invited Presentation:
Poster Number: 83
Authors
Isabella Seppi Presenting Author irseppi@alaska.edu University of Alaska Fairbanks |
Carl Tape Corresponding Author ctape@alaska.edu University of Alaska Fairbanks |
David Fee dfee1@alaska.edu University of Alaska Fairbanks |
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Classification of Aircraft Type Using Seismic Data in Alaska
Session
Data-driven and Computational Characterization of Non-earthquake Seismoacoustic Sources