Researchers at Zhejian University in China have developed a method of tracking unfamiliar drones using crowdsensing, leveraging consumer smartphones to detect the Wi-Fi signals of nearby drones.
The researchers created a database of known MAC addresses and SSIDs from all commercial drone manufacturers, allowing them to distinguish between drones and other Wi-Fi sources.
If the new Cost-Effective Crowdsensing System for Detecting and LocAlizing Drones (CEDAR) system detects a MAC address or SSID that is not in the database, the researchers can analyze the mobility patterns of the Wi-Fi signal to assess the likelihood it came from a drone.
The researchers found the system can detect drones within 350 meters and with an average accuracy of 87%, when no preliminary MAC addresses or SSIDs are found in the database.
From IEEE Spectrum
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Abstracts Copyright © 2019 SmithBucklin, Washington, DC, USA
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