01
A class an operator can act on
The sensor returns a class, a confidence, and a frequency. That is the difference between a siren and a decision.
Class. Confidence. A cue the formation can use.
Mind & Signal puts adaptive classification and super-resolution direction finding on a passive RF sensor sized for the vehicle, a Class 2 UAS, and the soldier. That sensor hands a trusted class, range, and a tight bearing to the C2 and effector at hand.
The problem
Distributed sensing, at the price of a radio.
Drone warfare rewards the side that can put a sensor on every vehicle and, ultimately, on the soldier. Mind & Signal is aimed at that density and cost profile: classification that keeps up when the waveform changes, and a direction cue precise enough for the rest of the counter-UAS stack.
02
Libraries go stale
Known commercial waveforms can be matched. Hopped and obfuscated links cannot wait on a static signature catalog.
03
DF needs a filter
Super-resolution direction finding is powerful and easily overloaded in a dense band. Classification tells the array which energy is worth a precise angle.
Our lane
Sense, classify, point the rest of the stack.
Passive receive. Convolutional discrimination. Super-resolution direction finding. The output is a class and a bearing the radar, the command post, and the effector can use immediately.
Detect
Passive RF across the bands commercial and adapted drones actually use.
Classify
Spectrogram in, class and confidence out. Retrain when the waveform moves.
Localize
Multi-element arrays and super-resolution angle of arrival for a tight cue.