This project has been a month in the making, and 9 fully functional units will be sent tomorrow to an undisclosed civilian site across the Israel - Lebanon border. All of my findings are shared online to anyone on the globe who could benefit from them, or make their own units.
I'm an engineering student at the University of York, originally from Israel, studying in England.
I too often have been hearing about tragic cases involving civilians in war zones being chased and attacked by small FPV drones mounted with an explosive. Especially around the north of Israel, Ukraine and Russian. My intentions for this project were clear: create a device small, portable and cheap enough for civilian use, that could drastically change the outcome of a drone infiltration through early alerting.
I decided to dedicate a month of my summer to go back to the university labs and to work on this as personal project.
These drone attacks are not run on normal wireless drones, instead they are run on small FPV drones that are connected to the operator through a long spool of fibre optic cable. This simply means that drone detection through Radio, the current industry standard, is not applicable.
My solution was to build an acoustic detector. A device that uses 4 MEMS microphones to capture the drone's propellers' emitted noise as they cut through the air, runs that data through several algorithms to enhance the SNR, reduce noise (directional, possible confusers), recognises their comb looking shape when plotted by frequency, and alert the user through multiple outputs (display, beeper, buzzer, led) along with alerting all nearby units using a LoRa module also fitted in the device.
The units have been tested against a custom drone rig, housing the exact same specs as the drones used in the Israel-Lebanon border (four 2807 motors, 7 in tri blades, FPV airframe), which was stationed 104.2m away from the device in a street with passer-by's and mild wind. That test ran successfully and the device was able to detect the drone.
This device was built for detection and alerting only, so no jamming.
Every online resource i could think of in regarding this project exists in the Github, along with a neat website that shows off more media with explanations, also housing a live detector simulation that runs in the browser: https://volantitech.com/#simulator
Too often today you hear about the use of small FPV drones mounted with an explosive for targeting civilians. As someone originally from israel myself but living and studying in England, i hear about this quite a lot. I decided to dedicate a month of my summer to go back to the university labs in order to work on this personal project, to send units to where I know they could help, and to share all of my findings to anyone on the globe who could benefit from them.
Nearly all current drone detection listens for the radio link, but a fibre-optic FPV drone doesn't have one: data travels through a glass thread, control goes up it, and the spectrum stays fully silent, but it cant hide the sound of its four propellers. A prop with B blades at R revolutions per second cuts the air at B×R Hz, and because the chop isn't a sine you get a comb of harmonics at every multiple. That comb is what this scores.
How: four ICS-43434 MEMS mics on one I2S clock, summed. At 79 mm across the array is a tenth of a wavelength at 400 Hz, so it's effectively a point: about 6 dB of SNR for free, no directionality. I tried beamforming and dropped it, steering does nothing below 2 kHz at this size. Then a 2048-point FFT every 32 ms on an ESP32-S3, an adaptive floor that learns quiet things in 6 s and loud bursts in under a second, and a comb score for every candidate rate from 70 to 2000 Hz. The best rate has to win six frames in a row within 2%.
The bit I'm most happy with: a hovering drone is a steady sound, and a steady sound is exactly what a fast adaptive floor learns and erases. So four detectors run on the same spectrum with different floors, one with no floor at all. That slow one is what fired at 104 m on Sunday, on a street with traffic and some people talking or walking by.
Numbers: 104.2 m measured, 0.23 s to alert on the fast tier, zero false alarms outdoors so far (speech right next to the mic indoors can fool it). £50–80 in parts boxed, £35–45 on a breadboard with the same firmware. Hardware CERN-OHL-W, firmware Apache-2.0, and tier 1 is pinned by golden vectors so the board and my laptop agree to the last decimal place.
Closest prior art is Batear (github.com/batear-io/batear): one mic on a dev board with Home Assistant integration. This is a four-mic array on a purpose-built board with measured field range. Different bets, and I'd point people at both.
Detection and alert only, so no jamming. It was built for a civilian community near the Israel-Lebanon border, and the first 9 units will soon be there.
The whole detector runs in the browser if you want to put a drone at a distance and add wind: https://volantitech.com/#simulator