C-UAV
Counter Drone system
AI Dome
Digital Designer with 10 years of experience based in Rome, Italy
How it works
Overview
The basics
In light of increasing security concerns posed by unauthorized drones, there is an imperative need for an effective surveillance and neutralization system. This proposal details an advanced drone tracking and trigger system designed to identify, track, and safely neutralize drones within a 0.5 km range using a blend of acoustic isolation & triangulation, machine learning technologies, and precise Lidar targeting technology.
The basics
In light of increasing security concerns posed by unauthorized drones, there is an imperative need for an effective surveillance and neutralization system. This proposal details an advanced drone tracking and trigger system designed to identify, track, and safely neutralize drones within a 0.5 km range using a blend of acoustic isolation & triangulation, machine learning technologies, and precise Lidar targeting technology.
Motivation
In the evolving landscape of modern warfare, technology continues to redefine the boundaries and tools of conflict. This past decade has seen a significant shift with the introduction of high-speed, cost-effective unmanned aerial vehicles (UAVs), presenting new challenges for military defenses worldwide. These UAVs, capable of versatile and remote operations, offer a stark economic advantage in warfare: a single F-35 jet, for instance, costs more than fifty thousand of these kamikaze UAVs. This disparity allows aggressors to engage in combat economically and from a distance, posing a substantial threat to both mobile military assets like tanks and critical stationary installations such as sensitive military bases. Furthermore countermeasures such as missiles traditionally used to neutralize these UAVs, often come at a cost up to a hundred times that of a single UAV, compounding the challenge of defending against these cost-efficient aerial weapons.
Motivation
In the evolving landscape of modern warfare, technology continues to redefine the boundaries and tools of conflict. This past decade has seen a significant shift with the introduction of high-speed, cost-effective unmanned aerial vehicles (UAVs), presenting new challenges for military defenses worldwide. These UAVs, capable of versatile and remote operations, offer a stark economic advantage in warfare: a single F-35 jet, for instance, costs more than fifty thousand of these kamikaze UAVs. This disparity allows aggressors to engage in combat economically and from a distance, posing a substantial threat to both mobile military assets like tanks and critical stationary installations such as sensitive military bases. Furthermore countermeasures such as missiles traditionally used to neutralize these UAVs, often come at a cost up to a hundred times that of a single UAV, compounding the challenge of defending against these cost-efficient aerial weapons.
Detection
Our defense architecture comprises two interconnected components powered by artificial intelligence: the detection system and the targeting system. These units collaboratively engage to first identify and then neutralize incoming threats with high efficiency. The detection system utilizes acoustic triangulation to locate approaching threats within a few meters and to measure their direction and speed. Subsequently, the targeting system employs high-precision LiDAR to accurately aim at and autonomously initiate countermeasures against these high-speed identified targets up to .5 km away.
Detection
Our defense architecture comprises two interconnected components powered by artificial intelligence: the detection system and the targeting system. These units collaboratively engage to first identify and then neutralize incoming threats with high efficiency. The detection system utilizes acoustic triangulation to locate approaching threats within a few meters and to measure their direction and speed. Subsequently, the targeting system employs high-precision LiDAR to accurately aim at and autonomously initiate countermeasures against these high-speed identified targets up to .5 km away.
AI Synergy
01
Synergy
This system mirrors the way a human might shoot down an incoming UAV—using the drone's sound to determine its general location and a rifle's scope for precise targeting and firing.
02
Sound
Detection System: Utilizing acoustic triangulation, the detection system locates the UAV and calculates its trajectory. This data aims at the cannon and adjusts the LiDAR scope of the cannon’s barrel. Although this acoustic system is intelligent, it lacks precision from a distance.
02
Sound
Detection System: Utilizing acoustic triangulation, the detection system locates the UAV and calculates its trajectory. This data aims at the cannon and adjusts the LiDAR scope of the cannon’s barrel. Although this acoustic system is intelligent, it lacks precision from a distance.
03
Laser
Targeting System: The targeting system employs highly focused LiDAR for precise targeting and automatic firing at the identified targets. Despite its precision, this system is simple: upon receiving a positive reading, it fires.
By dividing and synergizing these two systems, we create a comprehensive defense solution against UAV threats.
03
Laser
Targeting System: The targeting system employs highly focused LiDAR for precise targeting and automatic firing at the identified targets. Despite its precision, this system is simple: upon receiving a positive reading, it fires.
By dividing and synergizing these two systems, we create a comprehensive defense solution against UAV threats.
04
AI
No human can reliably hit a drone moving at 200 km/hr at a distance of 500m. Our system, divided into two synergistic components, accomplishes this with precision and efficiency by utilizing AI.
The AI technology in our system plays a crucial role in seamlessly integrating and enhancing the capabilities of both the detection and targeting components. In the detection phase, AI algorithms analyze audio data in real time to triangulate the drone's position. They employ advanced acoustic signal processing to filter out ambient noise and focus on the distinct sound signature of UAVs. This allows the system to pinpoint the general location of a fast-moving drone accurately.
For targeting, the AI shifts to processing the data from the LiDAR system, which provides precise distance and velocity measurements. AI algorithms then calculate the optimal firing solution based on the drone's trajectory, speed, and anticipated path. This involves complex predictive modeling, which adjusts the targeting mechanisms with precision far beyond human capabilities. By continuously learning from each engagement, the AI improves its accuracy and response times, ensuring high efficiency in neutralizing threats even under challenging conditions.
04
AI
No human can reliably hit a drone moving at 200 km/hr at a distance of 500m. Our system, divided into two synergistic components, accomplishes this with precision and efficiency by utilizing AI.
The AI technology in our system plays a crucial role in seamlessly integrating and enhancing the capabilities of both the detection and targeting components. In the detection phase, AI algorithms analyze audio data in real time to triangulate the drone's position. They employ advanced acoustic signal processing to filter out ambient noise and focus on the distinct sound signature of UAVs. This allows the system to pinpoint the general location of a fast-moving drone accurately.
For targeting, the AI shifts to processing the data from the LiDAR system, which provides precise distance and velocity measurements. AI algorithms then calculate the optimal firing solution based on the drone's trajectory, speed, and anticipated path. This involves complex predictive modeling, which adjusts the targeting mechanisms with precision far beyond human capabilities. By continuously learning from each engagement, the AI improves its accuracy and response times, ensuring high efficiency in neutralizing threats even under challenging conditions.
About Us
Our team has a strong background in deploying state-of-the-art ML solutions across diverse domains including embedded devices, cloud architecture, control systems, etc. At the moment, we're working on algorithms for real-time model updates and training deep reinforcement learning (RL) models for control calibration using Proximal Policy Optimization (PPO), aiming to enhance the efficiency and effectiveness of control systems in various applications.
Our team has built systems ranging from the F-35 fire control system to deep space telescopes. We know war. We understand the impact technology has on war. And we know how to build stuff.
