Seismic instruments, traditionally employed for earthquake detection, have been repurposed by researchers at the University of Alaska Fairbanks to identify the types of aircraft flying overhead. This innovative method leverages the ground vibrations caused by sound waves produced by aircraft, enabling scientists to analyze seismic data to determine specific aircraft types, such as the Cessna 185 Skywagon.
The research, published on November 18 in *The Seismic Record*, highlights a significant advancement in air traffic monitoring. Lead researcher and graduate student Bella Seppi explained that the frequencies generated by aircraft are considerably higher than those of typical seismic events. She noted, “Aircraft signals are a lot higher frequency than anything else that’s prominent in the spectrum that seismometers are recording.”
Understanding Seismic Detection of Aircraft
Seismometers detect ground motion, capturing vibrations from various sources, including aircraft. These vibrations manifest as acoustic waves and can be visualized in a spectrogram, illustrating frequency changes over time. The Doppler effect, which causes the pitch of sounds to rise as an object approaches and fall as it moves away, plays a crucial role in this analysis. For instance, much like the sound of an approaching ambulance, the frequency shifts recorded by seismometers indicate the aircraft’s proximity.
Seppi’s study utilized data from approximately 1,200 recordings collected over a span of 35 days from 303 seismometers. These devices, positioned about 1 kilometer apart along the Parks Highway, were initially installed to monitor aftershocks from the 2018 magnitude 7.1 Anchorage earthquake. The sensors’ rapid sampling rate of 500 Hz allowed for a more extensive frequency range, which is essential for accurate aircraft identification.
Building an Aircraft Frequency Catalog
To identify different aircraft types, Seppi encountered the challenge of lacking a comprehensive catalog of aircraft frequency patterns. She sourced data from Flightradar24, a platform that provides real-time information on in-flight aircraft, including type, altitude, and flight path. By correlating flight data with the seismic recordings, Seppi was able to extract the Doppler curves of the aircraft’s sound waves.
The next step involved eliminating the Doppler effect to reveal the aircraft’s true frequency pattern, known as its “frequency comb.” This pattern comprises the base frequency and its harmonics, which typically reflect the object’s vibrations. Seppi grouped the frequency combs of various aircraft types—piston, turboprop, and jet—based on the data obtained.
“What surprised me the most is how consistent a lot of the frequency signals are,” Seppi remarked, indicating the potential reliability of this method for future applications.
Future Implications and Research Directions
Seppi’s technique opens avenues for further research and practical applications. By developing a frequency comb from seismic recordings, researchers could compare it against a catalog of known aircraft frequency patterns for identification. Additionally, insights regarding the aircraft’s direction and speed can be derived from the spectrogram curves.
Future efforts will focus on determining the maximum distance at which aircraft can be detected and utilizing multiple seismometers to gather comprehensive flight data. Co-authors of the study include geophysics professor Carl Tape and research professor David Fee, both affiliated with the UAF Geophysical Institute.
This innovative approach not only enhances aircraft identification but may also be instrumental in assessing the potential sound impacts of aviation over environmentally sensitive areas. As Seppi stated, “This new method has many uses,” emphasizing its significance in both scientific research and practical applications.
