BLADE Use Case
Multi-sensor drone detection with sub-second alert latency
The Challenge
Small unmanned aerial systems (sUAS) represent the fastest-growing asymmetric threat on the modern battlefield. Current counter-UAS solutions are either too expensive, too heavy, or too dependent on single-sensor modalities that adversaries can easily defeat.
- Single-sensor C-UAS systems create exploitable gaps — RF-only detection fails against autonomous drones; acoustic-only fails in high-noise environments; EO/IR-only fails in adverse weather. Adversaries deliberately exploit these single points of failure.
- Commercial C-UAS platforms cost $5-15M per installation and require dedicated operator teams, making widespread deployment across forward operating bases and patrol bases fiscally impossible.
- False alarm rates of 60-80% in current systems create alarm fatigue, causing operators to ignore or delay response to real threats — the 'crying wolf' problem that has caused documented security breaches.
- Alert-to-response timelines exceed 30 seconds in most deployed systems, leaving insufficient time for kinetic or electronic countermeasures against Group 1-2 UAS threats traveling at 40-80 km/h.
How BLADE Solves It
BLADE ALPHA provides backpack-portable multi-sensor C-UAS detection that fuses acoustic, EO/IR, and RF signatures through on-device AI, delivering classified threat alerts to ATAK in under one second.
Acoustic Detection
Micro-array acoustic sensors detect propeller signatures at ranges up to 500m, providing initial bearing and altitude estimation independent of RF emissions.
RF Scanning
Software-defined radio continuously scans common UAS control and telemetry frequencies (2.4 GHz, 5.8 GHz, 900 MHz), detecting both commercial and modified control links.
Sensor Fusion
BLADE's fusion engine correlates acoustic and RF detections, resolving bearing ambiguities and generating a fused track with confidence scoring for each modality.
Visual Confirmation
EO/IR camera automatically slews to the fused bearing. YOLO-based detection confirms visual contact and classifies the UAS by type (commercial quad, fixed-wing, FPV).
Threat Classification
Local LLM analyzes the fused sensor data against a known-threat database and behavioral patterns to classify intent: reconnaissance, payload delivery, or swarm element.
ATAK Alert Push
Classified threat alert pushed to all ATAK clients within mesh range — including bearing, range, altitude, classification, confidence, and recommended response action.
Track Maintenance
BLADE maintains persistent tracking of the UAS, updating position and classification as the threat evolves. If the UAS is lost on one sensor, others maintain the track.
Engagement Handoff
If kinetic or EW countermeasures are available, BLADE provides targeting data in standard format for seamless handoff to defeat systems.
Deployment Configuration
This use case deploys on a single BLADE tier.
BLADE ALPHA
Backpack-portable configuration for dismounted patrols, observation posts, and hasty defensive positions. Full C-UAS capability in under 5 kg.
Key Capabilities
Purpose-built AI capabilities for this mission set.
Tri-Modal Sensor Fusion
Acoustic, RF, and EO/IR sensors fused through AI models that eliminate single-sensor blind spots and resolve classification ambiguity.
Sub-Second Alerting
From initial detection to classified ATAK alert in under 800ms. Fast enough for kinetic countermeasure engagement of Group 1 UAS.
UAS Classification Library
On-device database of 200+ commercial and military UAS signatures, updated via secure delta-sync. Includes behavioral pattern matching.
Swarm Detection
Multi-target tracking identifies coordinated UAS behavior patterns consistent with swarm tactics, alerting to formation and intent.
Zero RF Emission Mode
Passive-only detection mode using acoustic and EO/IR sensors for operations where RF emissions would compromise unit position.
90%+ False Alarm Reduction
Multi-sensor correlation and AI classification reduce false alarm rates from 60-80% (single-sensor) to under 5% (BLADE fusion).
Performance Metrics
<800ms
Detection to Alert
95%+
Classification Accuracy
<5%
False Alarm Rate
5kg
System Weight
See BLADE in Action
Schedule a classified demo of BLADE for counter-uas detection or download the solution brief to share with your team.