Researchers at the University of Alaska Fairbanks have made a groundbreaking discovery, demonstrating that instruments traditionally used for earthquake detection can also identify the type of aircraft flying overhead. This innovative approach utilizes seismic data to analyze the sound waves generated by aircraft, allowing scientists to determine their specific types, such as a Cessna 185 Skywagon.
The research, led by graduate student Bella Seppi, was published on November 18, 2023, in The Seismic Record. Seppi explained that although aircraft sound waves produce ground vibrations to a lesser extent than earthquakes, they can still be detected using seismometers. “Aircraft signals are a lot higher frequency than anything else that’s prominent in the spectrum that seismometers are recording,” she stated.
How Seismometers Capture Aircraft Sounds
Seismometers operate by recording ground motion, which includes vibrations caused by sound waves, also known as acoustic waves. These instruments can detect the Doppler-shifted frequencies of aircraft sounds when displayed in a spectrogram. Higher frequencies indicate an aircraft approaching the seismometer, while lower frequencies reveal one moving away, similar to the sound of an approaching ambulance whose pitch rises as it nears.
The research utilized data collected from nearly 1,200 recordings over a span of 35 days, using 303 seismometers installed along the Parks Highway in Alaska. These sensors, positioned approximately 1 kilometer apart, were originally set up to monitor aftershocks from the 2018 magnitude 7.1 Anchorage earthquake and to analyze subsurface structures. Their higher sampling rate of 500 per second allows them to capture a wider frequency range, making it possible to identify aircraft by type.
Despite the ability to generate a spectrogram from seismic data, Seppi faced the challenge of isolating an aircraft’s true frequency by removing the Doppler effect. This involved creating a “frequency comb,” representing the aircraft’s base frequency and its associated harmonics.
Building a Catalog of Aircraft Frequencies
To identify specific aircraft types, Seppi recognized the necessity of constructing a catalog of frequency patterns for different aircraft. She compiled data from Flightradar24, which provides real-time information about in-flight aircraft, including type, location, altitude, and speed. By correlating flight times from this source with the seismic data, she was able to create Doppler curves for each aircraft’s sound waves.
Through mathematical analysis, Seppi removed the Doppler effect to acquire each aircraft’s true frequency pattern. This process led to the creation of a frequency comb catalog, categorizing aircraft by type, including piston, turboprop, and jet. “What surprised me the most is how consistent a lot of the frequency signals are,” she remarked.
The implications of this research are significant, with potential applications extending beyond identification. Seppi noted that this methodology could also assist in predicting the environmental sound impacts of different aircraft types, particularly over sensitive areas.
As the research progresses, future efforts will focus on determining the distance from which an aircraft can be detected and how data from multiple seismometers can provide additional flight information. Co-authors of the study include Carl Tape and David Fee, both affiliated with the Geophysical Institute at UAF.
This innovative approach to aircraft identification through seismic data represents a significant advancement in both aviation research and environmental monitoring, paving the way for enhanced understanding of the acoustic footprints of various aircraft types.
