Drones, especially small, multirotor models, pose a serious military threat because they are fast and difficult to detect. Open-source VolAnti, developed by Agam Rossen, detects drones by using the sound of their propellers, which can be separated from background noise, and can provide early warning against fiber-optic drones that do not emit radio frequencies. The system processes data from a four-microphone array on the ESP32-S3 using a 2048-point FFT that runs every 32 ms, searching for propeller speeds in the 70 Hz-2000 Hz range. One of the four algorithms does not use an adaptive noise floor, so as not to miss stationary drones. The files are available on GitHub.
Why it matters
VolAnti’s key difference is that, instead of searching for electronic signals for detection, it evaluates the acoustic signatures produced by drones. This can provide an additional layer of early warning in situations where vehicles connected via fiber-optic links that do not emit radio frequencies could be missed by traditional signal-based methods. Because the project is open source, its hardware and software approach can be examined, adapted and developed for different needs. However, the system’s performance in real-world environments depends on how accurately it can distinguish targets under conditions such as environmental noise, similar sound sources and the target remaining stationary. The files published on GitHub provide a basis for evaluating these questions through independent trials.