ECHONETv1.0
>Initializing distributed sensor array.....
>Establishing network coordination layer...
>Loading C2 interface protocol.............
>Verifying node synchronization............
>System ready..............................
DISTRIBUTED SENSING NETWORK0%
ECHOCORE AI INC.

 

The passive layer radar was never built to cover.

Passive
Three sensing modalities. Zero RF emissions. No jamming surface.
Distributed
No single point of failure. Coverage survives node loss.
Cross-Validating
Acoustic + thermal + RF fusion catches what single sensors miss.
Complementary
Complements radar and EO layers. Operates as a standalone network where needed.
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System Complementarity

Why EchoNet Complements Existing Systems

Existing CUAS architectures have well-defined coverage gaps. EchoNet is designed to operate exactly where each conventional layer reaches its limits.

RADAR LIMITATION

Ground clutter and low-altitude blind zones

Radar performance degrades against low, slow, small targets due to ground clutter and beam geometry. Hostile UAS increasingly exploit this by flying intentionally low to evade radar coverage. EchoNet's acoustic layer does not depend on reflected signals; it operates effectively where radar return is unreliable.

RF-DETECTION LIMITATION

RF-silent and tethered platforms are invisible

Conventional RF detection is completely blind to RF-silent UAS: fibre-tethered, autonomous, and pre-programmed platforms emit no RF signature to detect. No amount of RF sensitivity closes this gap. EchoNet's acoustic and thermal layers detect physical presence regardless of emission state.

EO/IR LIMITATION

Line-of-sight and lighting dependencies

EO/IR sensors require unobstructed line of sight, adequate lighting, and precise aiming; they cannot search, only confirm. Without directional cueing from another sensor, EO/IR coverage is extremely narrow. EchoNet operates day and night, through terrain masking and adverse weather, with omnidirectional acoustic coverage per node.

ARCHITECTURAL LIMITATION

Centralized sensors are single points of failure

High-value centralized sensors are high-value targets. Jamming, spoofing, or physical neutralization of one node degrades entire coverage zones. EchoNet's distributed mesh maintains coverage under partial node loss.

System Design

Sensing Architecture

Three passive modalities. One intelligent fusion layer.

Layer 01

Acoustic Layer

Primary Detection
50–100m (target-dependent)85%+ lab benchmarkPassive

MEMS microphone array with CNN-based drone signature classification. Primary passive detection layer: always-on, terrain-tolerant, and effective in environments where radar line-of-sight is obstructed.

50–100m detection range (FPV-class drones)
CNN classification, 85%+ benchmark accuracy (controlled conditions; field validation ongoing)
Operates independent of RF emissions
Effective in urban canyons and forested terrain
Layer 02

Thermal Layer

Close-Range Confirmation
20–30m (sensor-dependent)Passive

Close-range infrared confirmation layer. Operates in coordination with the acoustic layer to verify presence and bearing of suspected threats at short range.

20–30m confirmation range (extensible with higher-grade IR sensors subject to deployment budget)
Acoustically cued for directional threat verification
Filters vehicles, birds, and static heat sources
Operates day and night, independent of lighting
Layer 03

RF Layer

High-Altitude Awareness
3–5km (emitter-dependent)400MHz–6GHzPassive

Wideband passive SDR receiver covering 400MHz–6GHz. Maintains awareness beyond the acoustic and thermal envelope, including drones operating at longer ranges and higher altitudes where acoustic detection degrades.

3–5 km detection range (emitter-dependent)
Passive receive-only, zero RF emissions
Band classification: 433MHz / 2.4GHz / 5.8GHz / sub-6GHz emitters
No interference with existing CUAS assets
Layer 04

AI Fusion Core

Cross-Validation Intelligence
3 inputs5 threat verdictsReal-time fusion

The fusion layer is what transforms three individually imperfect sensors into a reliable decision system. Threat type is determined not just by what triggers, but by what doesn't.

Acoustic + Thermal + RF → high-confidence RF-emitting UAS
Acoustic + Thermal, no RF → likely fibre-tethered or RF-silent platform
RF only → distant high-altitude emitter, beyond acoustic range
Acoustic only → probable false alarm, low priority
Threat Intelligence

What the Fusion Layer Sees

Threat type is determined by which modalities agree, and which don't.

ACOUSTIC
THERMAL
RF
VERDICT
ACOUSTIC✓ Detected
THERMAL✓ Detected
RF✓ Detected
High-confidence RF-emitting UAS
ACOUSTIC✓ Detected
THERMAL✓ Detected
RF✗ Silent
RF-silent / fibre-tethered UAS: elevated threat
ACOUSTIC✗ Silent
THERMAL✗ Silent
RF✓ Detected
Distant high-altitude emitter: cue radar
ACOUSTIC✓ Detected
THERMAL✗ Silent
RF✗ Silent
Possible RF-silent low-altitude threat, monitor with elevated priority

Fusion logic reduces false alarms and identifies threat class, especially RF-silent low-altitude threats that RF-only systems cannot see.

System Role

Where EchoNet Fits

EchoNet is not a radar replacement. It is the persistent passive layer that fills the gap radar cannot see, and then cues the systems that can respond.

What Radar Covers
  • High-speed fixed-wing threats (>200 km/h)
  • High-altitude fixed-wing aircraft
  • Long-range volume search (5–15 km)
  • Wide-area volume search
Where EchoNet Operates
  • Large-scale border surveillance: northern frontier and remote terrain
  • Forward operating bases and critical infrastructure perimeters
  • Low-cost, low-flying RF-silent UAS threats
  • Forested and unmonitored geographies where conventional sensors cannot scale
What EchoNet Cues
  • Radar slew-to-cue on threat bearing
  • EO/IR camera pointing and tracking
  • Operator alert with threat classification
  • C2 handoff with sensor confidence score
Interoperability

Integration & Interoperability

EchoNet is not a closed system. The architecture prioritizes integration readiness at every layer, from sensor output to command interface, ensuring compatibility with existing and future operational frameworks.

Architecture-ready for integration with external C2 systems. Not a standalone endpoint: a distributed sensing extension designed to feed into existing operational data flows.

Structured Data Output

Network outputs are structured for downstream consumption by command and control platforms. Data formats are designed with interoperability as a primary architectural constraint.

C2 Protocol Compatibility

Architecture designed for compatibility with digital C2 data flow standards including CoT and SAPIENT-type message structures. Integration pathways do not require modification of upstream systems.

API-Based Integration Layer

An API-based data layer enables modular connection to external processing, display, and decision-support systems without requiring proprietary middleware.

Non-Disruptive Integration

EchoNet is architected as a complementary sensing layer. Deployment augments existing sensor coverage without requiring replacement or reconfiguration of installed systems.

CUAS Sandbox 2026

Suffield Demonstration Objectives

The following objectives define the scope of EchoNet's validation activities at CFB Suffield. Each objective targets a discrete capability claim within current TRL parameters.

Event
CUAS Sandbox 2026
Host
DND / CAF
Location
CFB Suffield, Alberta
Timeline
September 2026
Suffield Demonstration Scope
Will Demonstrate

Multi-node acoustic detection, thermal confirmation cueing, RF emitter awareness, and AI fusion verdict output across a 6–8 node deployment.

Success Criteria
Acoustic detection of FPV-class UAS at 50–100m range
Thermal layer provides directional confirmation following acoustic cue
Position tracking of RF-emitting UAS with frequency band classification
Fusion verdict output includes threat type and confidence score
OBJ-01

Distributed Geometry Validation

Validate multi-node deployment configurations against defined coverage geometries, including linear boundary and perimeter scenarios.

OBJ-02

Multi-Node Synchronization

Demonstrate reliable coordination between distributed sensing nodes under field conditions, validating network-level consistency and data coherence.

OBJ-03

RF-Silent Detection Pathway Validation

Validate detection capability through non-RF sensor pathways, addressing threat profiles that bypass conventional RF-dependent detection architectures.

OBJ-04

Tethered UAS Threat Recognition

Assess network response to tethered platform threat profiles, leveraging sensor diversity and distributed geometry to identify disturbance signatures.

Technology Maturity

Maturity & Path Forward

EchoNet components are at TRL 5; system-level integration targets TRL 6 at the 2026 Sandbox. The following reflects an accurate account of what has been validated, what is under active refinement, and what will be tested at Suffield.

Current TRL
5 → 6
TRL 1TRL 5–6TRL 9
Validated
Distributed node architecture design and simulation
Network topology modeling for linear and perimeter geometries
Multi-node data fusion logic and correlation algorithms
Passive detection pathway identification and feasibility assessment
C2 output data structure and format specification
CNN-based acoustic classifier for UAS propeller signature recognition (lab-validated)
Under Refinement
Hardware prototype integration and field calibration
Real-environment multi-node synchronization under variable conditions
Detection confidence threshold refinement across sensor modalities
High-sensitivity MEMS microphone array: custom PCB and firmware redesigned for UAS-relevant spectral bands
To Be Tested at Suffield
End-to-end system performance under operational field conditions
Coverage geometry validation against defined boundary scenarios
Multi-node coordination under Red Team UAS threat simulation
Development Roadmap
2026 Q3
CUAS Sandbox
Field validation at CFB Suffield. Architecture-level demonstration under operational conditions.
2026 Q4
Post-Sandbox Refinement
Integration of field feedback. Sensor fusion algorithm refinement and hardware iteration.
2027
TRL 6 → 7 Transition
Expanded real-world trials. Mobile platform integration and production architecture design.
2028
Multi-Scenario Operational Readiness
Validated across CUAS26 operational scenarios: linear border, forward operating base, and critical infrastructure perimeter.