Distributed UAS Detection Network with Central Aggregator
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Solution Overview
Problem
Current unmanned system detection systems are overly complex, costly, and lack accessibility, situational awareness, and intuitive interfaces, making them impractical for security forces with limited budgets, especially in urban environments where signal fading and sensor deployment become significant challenges.
Innovation Solution
A network of compact, low-cost, fixed and mobile sensing devices with a centralized aggregator for data combination and analysis, featuring configurable software-defined radios and intuitive user interfaces, enabling flexible deployment and interconnectivity to detect and track unmanned aerial systems (UAS) effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current unmanned system detection systems are deployed, then detection capability is provided, but system complexity and cost increase significantly
Solution Approach 1:
The detection system is segmented into multiple independent sensor nodes distributed across the environment. Each node independently performs detection and transmits data to a central aggregator, replacing a single complex system with multiple simpler units that collectively provide comprehensive coverage and detection capability.
Solution Approach 2:
The sensor nodes are designed with universal functionality to detect multiple types of unmanned systems using various detection methods (RFID, acoustic, visual). The configurable software-defined radios enable each sensor to adapt to different detection scenarios, reducing the need for specialized equipment for each threat type.
2Reliability
If current unmanned system detection systems are deployed, then detection capability is provided, but cost increases significantly
Solution Approach 1:
The system employs inexpensive sensor nodes that can be deployed in large numbers without significant cost burden. Each node is designed to be cost-effective and replaceable, allowing broad deployment coverage while maintaining budget constraints for security forces with limited resources.
Solution Approach 2:
Multiple detection functions (RFID detection, acoustic sensing, visual detection) are merged into single sensor nodes, eliminating the need for separate specialized equipment. The centralized aggregator combines data from multiple sensors, providing comprehensive detection capability through integration rather than through expensive individual systems.
3Area of stationary object
If sensors are deployed in urban environments, then detection coverage is improved, but signal fading occurs due to building obstructions
Solution Approach 1:
The detection network is segmented into multiple distributed sensor nodes positioned at different locations throughout the urban environment. This segmentation ensures that at least some nodes maintain line-of-sight or unobstructed detection paths to potential threats, compensating for signal blocking by buildings through spatial distribution.
Solution Approach 2:
The centralized aggregator acts as an intermediary that receives and processes data from multiple sensor nodes. It combines detection data from various locations and uses data fusion techniques to overcome individual signal blocking issues, providing comprehensive situational awareness even when individual sensors experience fading.
4Loss of information
If a centralized aggregator is used for data combination, then situational awareness is enhanced, but data transmission requirements increase
Solution Approach 1:
The system extracts only the essential detection data (presence, location, type of unmanned system) from each sensor node and transmits this condensed information to the centralized aggregator. Non-essential raw data is filtered out at the source, reducing transmission requirements while maintaining the aggregator's ability to provide comprehensive situational awareness through processed information.
Data Source
AI summary
An unmanned aerial system (UAS) detection device includes a sensor having programmed instructions to cause the sensor to scan energy in an electromagnetic spectrum; process the energy in the electromagnetic spectrum into bursts; determine whether the bursts are valid UAS bursts based on burst criteria; and correlate the bursts into a single signal.