Drone Detector With Multi-Sensor Fusion Combining Drone Spoofing Device

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Drone Detector With Multi-Sensor Fusion Combining Drone Spoofing Device
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Features
Specifications
Name: Polaris Hobit AS13
Detection Bandwitch: 433MHz、900MGz、2.4GHz、5.2GHz、5.8GHz
Drone Location: Within 3km
Customization: 360 °
Detection Rate: ≥ 99.9%
Protection Grade: ≥ IP65
Highlight:

ip65 uav detector

,

ip65 drone detector

Basic Infomation
Place of Origin: Shenzhen,China
Brand Name: Polaris
Certification: CE,ISO9002
Model Number: Hobit AS13
Payment & Shipping Terms
Packaging Details: Durable case or box
Delivery Time: In 7 -14 works day
Payment Terms: T/T, Paypal , Etc.
Supply Ability: 50 Pcs/month
Product Description

Drone Detector With Multi-Sensor Fusion Combining Drone Spoofing Device


Introduction


This integrated system employs AI-driven multi-sensor fusion to detect, track, and neutralize unauthorized drones through real-time spoofing protocols. By combining  pulsed Doppler radar , wideband RF spectrum analysis  (70MHz–6GHz) , it achieves 360° detection coverage with 0.8-meter positional accuracy at 8km range. The core innovation lies in its adaptive sensor fusion engine , which leverages spiking neural networks (SNNs) to synchronize radar cross-section data, RF signal fingerprints (e.g., DJI OcuSync protocols), and event-based camera inputs, reducing false positives from birds or environmental clutter by 99.1%.The spoofing subsystem implements cognitive GPS/GLONASS signal emulation , generating adversarial navigation coordinates that override drone autopilot systems while complying with aviation regulations. A dynamic waveform synthesizer​​ simultaneously disrupts 2.4GHz/5.8GHz control links and 1.5GHz GNSS receivers, forcing unauthorized UAVs into controlled descent or return-to-home modes. Proprietary time-synchronized jamming algorithms analyze drone firmware vulnerabilities through live protocol reverse-engineering, enabling sub-500ms response from detection to spoofing activation.Key advancements include a neuromorphic edge computing architecture  that processes 15TB/hour of sensor data via FPGA-accelerated SNNs, enabling real-time fusion of millimeter-wave radar signatures with RF spectral patterns. The system autonomously updates its threat database using generative adversarial networks (GANs)  to simulate emerging drone models and anti-detection tactics. Field-tested in urban environments, it maintains 98.7% spoofing success rate against swarm attacks while preserving legitimate drone operations through blockchain-verified Remote ID authentication.


Basic


Function

Description

UAV detection

Detection spectrum bandwidth

70 MHZ - 6GHZ

detection focus on the 433Mhz/ 900Mhz/2.4Ghz/5.2Ghz/5.8Ghz

Simultaneous screening number of UAV

150pcs

can be customize with 1Ghz -1.4Ghz & 5.1Ghz - 5.9Ghz FPV Bands

The lowest detection height

0 meters

Detection rate

99.99 %

White and Blacklist

Number of identifiable models

 400

including DJI series drones,and it has the autonomous learning ability

the accurate identification of target

Available

for different targets of the same position, same frequency band, same manufacturer, same type of UAV respectively.

in-depth analysis of UAV signal

the identification of unique ID

the black and whitelist to distinguish

Defensive Interference

Interferable frequency bands

900MHz, 433Mhz, 1.5ghz, 2.4ghz, 5.8ghz, 5.2Ghz

 

other customized frequency bands

Remote OAM

Unattended Mode

Automatic detection and strike

 

A variety of OAM features

Firmware updating

used with the remote server

Reset, status inquiry

Self-testing

Parameter configuration

Networking

Multi-device networking

observe the online/abnormal status of each device

 

Remote control through mobile terminals

viewing the operating interface of the device system

receiving alarm information

viewing the black and whitelist

turning on defense function

Data security

High reliability and security

certificate management and data encryption




Interface Showcase

 

As shown in the figure, one can clearly see all the sensors included in the current detection equipment, and the perfectly constructed fraud device it contains.


Drone Detector With Multi-Sensor Fusion Combining Drone Spoofing Device 0


Drone Detector With Multi-Sensor Fusion Combining Drone Spoofing Device 1





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