UAV Swarm Sensor Network for Adaptive Domain Exclusion Zones
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Solution Overview
Problem
Existing surveillance and defense systems face limitations in creating adaptable and resilient domain exclusion zones due to line-of-sight issues, static deployment, and vulnerability to adversarial attacks, particularly in dynamic environments.
Innovation Solution
A distributed sensor network of cooperatively acting unmanned autonomous vehicles (UAVs) forms a domain exclusion zone using multiple sensors and communication modules for object classification, discrimination, and identification, enabling flexible deployment and resistance to adversarial interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a distributed sensor network using multiple UAVs is deployed to create a domain exclusion zone, then the detection and classification range is enhanced and resilience against adversarial attacks increases, but the device complexity and coordination requirements increase
Solution Approach 1:
The surveillance system is divided into multiple independent UAV units, each equipped with its own sensors and processing capabilities. Each UAV independently performs detection, classification, and identification functions, allowing the system to maintain operational capability even if individual units are compromised or fail. This segmentation distributes the computational and sensing load across multiple nodes.
Solution Approach 2:
Multiple UAVs are combined into a coordinated swarm that shares sensor data and classification results through communication modules. The system merges individual detection capabilities into a collective surveillance network, where each UAV contributes to the overall domain exclusion zone coverage and mutual validation of detected objects enhances reliability.
2Adaptability or versatility
If mobile sensor carriers (UAVs) are used to create adaptable domain exclusion zones, then the adaptability and flexibility of the surveillance system improve, but the stability and line-of-sight reliability deteriorate
Solution Approach 1:
The system transitions from ground-based or fixed sensor deployments to three-dimensional aerial surveillance using UAVs. By operating in the vertical dimension, the mobile sensor carriers can bypass ground obstacles and maintain line-of-sight detection capabilities while dynamically repositioning to adapt to changing surveillance requirements and threat landscapes.
Solution Approach 2:
The surveillance system employs dynamically repositioning UAVs that can autonomously adjust their positions and orientations to maintain optimal detection angles and coverage. The mobile platform allows continuous adaptation of the domain exclusion zone boundaries and sensor pointing directions in response to detected intrusions or changing environmental conditions.
3Measurement precision
If object classification, discrimination, and identification algorithms are implemented on each UAV, then the measurement precision and detection capability improve, but the processing requirements and energy consumption increase
Solution Approach 1:
The UAVs are pre-equipped with trained machine learning models and classification algorithms stored in their onboard processors. This preliminary preparation allows the systems to perform real-time object classification, discrimination, and identification without requiring continuous cloud connectivity or intensive real-time training, thereby reducing operational energy consumption while maintaining high measurement precision.
Data Source
Figure 1~3
AI summary
A distributed sensor network (100) comprises a first plurality of cooperatively acting unmanned autonomous vehicles, UAVs (20; 20a-20f), spatially distributed to create a domain exclusion zone, DEZ (11). Each of the UAVs (20; 20a-20f) includes one or more first sensors (27a; 27b) configured to gather detection signals from any object (30) entering the DEZ (11), a signal processor (25) connected to the one or more first sensors (27a; 27b) and configured to process the detection signals gathered by the one or more first sensors (27a; 27b), to perform object classification, discrimination, and identification, CDI, algorithms on the detection signals, and to output a CDI signal related to the object (30), and one or more communication modules (26) coupled to the signal processor (25) and configured to transmit the CDI signal to other UAVs (20; 20a-20f) in the first plurality of cooperatively acting UAVs (20; 20a-20f).