FX–SKY

AI-Enabled Multi-Sensor Airspace Surveillance Systems

THE CHALLENGE

Traditional air defense systems were built for aircraft. Against drones, they become slow, expensive, and outnumbered.

Detection ambiguity

Small drones are hard to separate from background noise across RF, radar, optical, and acoustic sensors individually.

Reaction time

Drones, capable of crossing 1 km in 36 seconds at 100 km/h,   outpace human reaction times.

Cost asymmetry

Low-cost drones can credibly threaten high-value assets, forcing disproportionate responses from expensive defense systems.

Swarm dynamics

Swarm coordination, decoys, and maneuvering overwhelm defense systems designed to engage targets individually.

THE SOLUTION

Rapid counter-drone detection and response through coordinated multi-sensor fusion across passive radar, RF, EO/IR, and acoustic inputs.

THE SYSTEM IN ACTION

FX-SKY fuses fragmented sensor data into a unified airspace picture, and develops a response supported by a network of agents.

THE RESULT

Swarms detected, tracked, and understood as coordinated entities.

Engagement order optimized under simultaneous attack.

Constant learning, upgrading and improving of the system.

Human authority embedded inevery action.

DETECTION AGENT

LSTM-based RF classification, radar micro-doppler analysis.

TRACKING AGENT

Multi-hypothesis tracker with trajectory prediction.

ASSESSMENT AGENT

Drone type, payload estimation, threat scoring, swarm analysis including collective behavior modeling, leader identification.

RESPONSE AGENT

Engagement prioritization, countermeasure selection.

COORDINATION AGENT

Multi-effector orchestration within ROE.

LEARNING AGENT

Continuously learns from outcomes, improving accuracy and effectiveness over time.

VERTICALLY INTEGRATED:
RF, radar, EO/IR (via FX-Ground), and acoustic sensing unified into a single system with on-device compute, fusion, and control. EO/IR serves as the visual confirmation and tracking backbone.

SENSOR FUSION BACKBONE:
RF - wideband passive + GPU
Radar - micro-doppler, drone-optimized
EO/IR - PTZ thermal + visible with auto-slew
Aoustic - microphone array with beamforming

AI-NATIVE ARCHITECTURE:
Specialized AI models for detection, tracking, classification, swarm analysis, and response on fused data. Continuous edge operation with sub-second loops.

NETWORKED COORDINATION AND CONTROL:
Multiple nodes operate as a coordinated system, sharing tracks, threat assessments, and engagement priorities for wide-area coverage and synchronized response.

SWARM NATIVE BY DESIGN:
Collective drone behavior modeled at system level. Patterns identified, trajectories predicted, threats prioritized, and responses sequenced beyond per-target engagement.

DEPLOYMENT SCENARIOS

Designed to integrate into live environments.

Military installations and forward bases

Persistent, multi-sensor airspace monitoring with autonomous counter-drone response within defined rules of engagement.

Critical infrastructure and strategic assets

Continuous protection of high-value sites such as power plants, refineries, and data centers.

Airports and aviation corridors

Low-altitude airspace monitoring around airports to detect, track, and manage unauthorized drones that disrupt flight operations and safety.

Urban security and high-risk events

Rapid deployment airspace control for cities, VIP movements, and public events, enabling fast detection and managed response to unpredictable drone activity.