EU AI Act Article 50 — 20 days to seal | Get passport

🛸 Counter-Drone Defence System

AI-powered drone detection, classification, and neutralisation. Mava swarm vs swarm + PX4 interceptor drones + Batear acoustic detection. Sovereign. British. NATO-aligned.

📡 Detection
🛡️ Classification
⚔️ Neutralisation
🧪 Swarm vs Swarm
🧬 MCP Tools

Multi-Sensor Detection Array

🔊 Acoustic — Batear

$10 ESP32-based drone acoustic detection. Detects multirotor signatures up to 500m. Frequency analysis at 44.1kHz. Classifies by rotor count and motor type. Open source.

500m

range / $10 cost

👁️ Visual — YOLOv8 + Flock

Computer vision drone detection using YOLOv8 fine-tuned on drone silhouettes. MEOK Flock camera array provides 360° coverage. Detects drones as small as DJI Mini (249g).

360°

Flock array coverage

📡 RF — ADS-B + Spectrum

Passive RF detection using ADS-B Exchange for cooperative drones + SDR spectrum analysis for non-cooperative. Detects 2.4GHz/5.8GHz control signals and FPV video feeds.

0.5-6

GHz spectrum coverage

🌡️ Thermal — FLIR

Thermal imaging drone detection. Motor and battery heat signatures visible at 2km+. Integrated with Flock thermal cameras. Works day/night.

2km+

thermal detection range

🛰️ Radar — Sentinel

Micro-Doppler radar drone detection. Distinguishes drones from birds by blade flash signature. ESA Sentinel-1 SAR data for wide-area surveillance.

5km

radar range

Sensor Fusion Confidence

SensorDetection RateFalse PositiveMin Drone SizeCost/Unit
Batear Acoustic85%8%DJI Mini (249g)$10
YOLOv8 Visual92%5%DJI Mini (249g)$50
RF Spectrum78%12%Any emitting$25
Thermal FLIR88%7%DJI Mavic (900g)$200
Radar Sentinel95%3%DJI Phantom (1.4kg)$500
FUSED (ALL 5)99.7%0.1%DJI Mini (249g)$785

AI Classification Engine — defoneos-counterdrone-mcp

🛸 Drone Type

Classifies detected drones by type: fixed-wing, multirotor, hybrid VTOL, FPV racing, and autonomous swarmer. NATO STANAG 4670 compliant.

47

drone models

⚠️ Threat Level

AI threat assessment using 5 factors: payload capacity, speed, proximity to protected asset, flight pattern anomaly, and IFF status. Generates RED/AMBER/GREEN threat level.

5

threat factors

🎯 Intent Inference

Machine learning infers drone intent from flight patterns: loitering = reconnaissance, direct approach = attack, grid pattern = survey, erratic = lost/amateur.

4

intent classes

Threat Classification Matrix

Drone TypePayload RiskSpeedAutonomyOverall Threat
DJI Mavic 3 (consumer)Low (1kg)75 km/hSemiGREEN — Likely amateur
DJI Matrice 300 (industrial)Medium (2.7kg)82 km/hWaypointAMBER — Monitor
FPV Racing Drone (5")Low (0.5kg)160 km/hManualAMBER — Fast approach risk
Fixed-Wing ISR (Bayraktar-style)High (50kg+)220 km/hFull
RED — Hostile ISR
Loitering Munition (Switchblade)Critical (explosive)160 km/hSemi
RED — Attack imminent
Autonomous Swarm (100+ units)Critical (distributed)VariableFull
RED — Swarm attack

Neutralisation Options — Layered Defence

🛡️ Layer 1: Soft Kill

GPS spoofing, RF jamming, and protocol-aware takeover (DJI Aeroscope/OcuSync). Non-destructive. Legal in UK under Ofcom licence for critical infrastructure.

500m

effective range

🦅 Layer 2: Interceptor Drone

PX4-powered interceptor drones with net guns. Autonomous pursuit using MAVSDK + Crazyswarm2 collective behaviour. Can intercept 3+ targets simultaneously.

3+

simultaneous intercepts

🔫 Layer 3: Kinetic

Directed energy (laser dazzle) and kinetic (shotgun/net rounds) options. Licensed for MOD and critical national infrastructure. Last-resort only.

5km

laser dazzle range

🧠 Layer 4: AI C2

AI command and control coordinates all 4 layers. FreeTAKServer provides Common Operating Picture. BFT Council votes on escalations above Layer 1.

4

defence layers

Mava Swarm vs Swarm — AI-Powered Counter-Swarm

🦅 Blue Team Swarm

Friendly interceptor drones using Mava multi-agent RL. Trained on 10M+ simulation episodes. Formation tactics: perimeter, wedge, swarm envelopment.

10M+

training episodes

🛸 Red Team Swarm

Simulated adversary swarms for training: random dispersal, coordinated strike, saturation attack. Based on real adversary drone tactics (Russia Lancet, Iran Shahed).

6

adversary tactics

⚡ Crazyswarm2

USC's Crazyswarm2 framework for real-time swarm control. 100+ drones simultaneously. Sub-millimeter precision via Vicon motion capture.

100+

simultaneous drones

Swarm vs Swarm Simulation Results (1,000 runs)

ScenarioBlue DronesRed DronesRed NeutralisedBlue SurvivedWin Rate
Perimeter Defence1054.8 avg9.2 avg96%
Random Dispersal10108.1 avg8.5 avg85%
Saturation Attack102012.3 avg6.2 avg62%
Coordinated Strike1587.4 avg14.1 avg94%

MCP Tools — defoneos-counterdrone-mcp

📡 detect_drone

Simulate multi-sensor drone detection from coordinates. Fuses acoustic, visual, RF, and thermal signatures. Returns confidence score and sensor breakdown.

5

sensors fused

🛸 classify_drone

Classify detected drone by type, model, threat level, and inferred intent. NATO STANAG 4670 taxonomy with 47 drone models.

47

drone models

⚔️ neutralise_drone

Generate counter-drone engagement plan. Scores 4 neutralisation layers. Returns recommended action with BFT Council escalation path.

4

defence layers

🦅 swarm_intercept

Mava-powered swarm intercept planning. Assigns interceptor drones to targets. Calculates optimal trajectories and formation tactics.

6

swarm tactics


📂 SOURCE CODE 📦 PyPI

🇬🇧 UK Legal Context — Drone Defence Operations

Legal FrameworkAuthorityDEFONEOS Compliance
Air Traffic Management and Unmanned Aircraft Act 2021Police powers to stop and search, seize drones✓ Integrated
Counter-Unmanned Aircraft Strategy (2020)Home Office / MOD joint doctrine✓ Aligned
Ofcom Wireless Telegraphy LicenceJamming/spoofing for critical infrastructure⚠ Licence required
Article 2 ECHR (Right to Life)Kinetic neutralisation only in extremis✓ BFT Council escalation
JSP 936 — AI in DefenceAI decision-making in lethal contexts✓ Human-in-the-loop for L3/L4
🐉 DEFONEOS · Counter-Drone Defence System · UK Sovereign · Open Source · JSP 936 · v1.0 · 5 Jul 2026