Sensing Architecture
Three passive modalities. One fusion layer. This is the system design doctrine.
Where terrain blinds radar, passive acoustic still hears
Concept schematic. Illustrative terrain and geometry, not a fielded measurement or a real node layout.
Radar needs line of sight, so terrain ridges leave a shadow over the low ground behind them: valleys, rivers, canyons.
A low and slow RF-silent drone flies into that blind zone, with no emitter to detect and no radar return.
Passive acoustic does not need line of sight, so the distributed nodes still hear the track and confirm it.
What EchoCore AI decides from agreement and silence
Which sensors stay silent matters as much as which ones trigger. Each evidence combination maps to a typed disposition with a capped claim ceiling, not a raw alert.
Each row maps to a maximum claim type on the lattice presence < bearing < position < track < identity, with a capped confidence ceiling. A Remote ID broadcast that contradicts the measured physics never becomes a confident track; it raises a spoofing alert.
Where EchoNet is strongest
Radar, RF, and EO/IR each go blind in a specific way: low and slow targets, RF-silent platforms, bad line of sight. EchoNet is the passive layer built for exactly those cases. The gaps below are where it does its strongest work.
Ground clutter and low-altitude blind zones
Radar degrades against low, slow, small targets. Ground clutter and beam geometry leave gaps, and hostile UAS fly low on purpose to sit inside them. The acoustic layer does not rely on reflected signals, so it is meant to cover the cases where radar return is unreliable.
RF-silent and tethered platforms are invisible
RF detection is blind to platforms that emit nothing. Fibre-tethered, autonomous, and pre-programmed UAS carry no RF signature, and more sensitivity does not close that gap. The acoustic and thermal layers aim to detect physical presence regardless of emission state.
Line-of-sight and lighting dependencies
EO/IR sensors need clear line of sight, adequate light, and precise aiming; they are suited to confirmation more than wide-area search. Without a cue from another sensor, their coverage is narrow. EchoNet is designed to work day and night, through terrain masking and weather, with omnidirectional acoustic coverage per node.
Centralized sensors are single points of failure
A centralized sensor is a high-value target. Jam, spoof, or knock out one node and entire coverage zones go dark. The distributed mesh is meant to hold coverage under partial node loss.
Where EchoNet Fits
EchoNet does not replace radar. It is the persistent passive layer for the gaps radar cannot see, and it cues the systems that respond.
Maturity & Path Forward
EchoNet is a developmental program. Today it is a TRL 4-5 software testbed and fusion engine with a rigorous synthetic-evaluation methodology. The account below separates what is built and demonstrated in simulation, what is in active development, and what we are preparing for the CUAS Sandbox field event at Suffield.
Founder-led, judged by the work
EchoCore AI Inc. is a founder-led company in Calgary, Canada. We would rather be judged by what runs than by a roster of names: a trust-bounded fusion engine, a deterministic synthetic testbed, and a golden loop that re-runs byte-for-byte from a seed. Everything on this site is something we built, and evaluators can re-run it from a seed. The full reproducibility package is available on request.