Calibrated UWB Radar Pattern Recognition for Concealed Weapon Detection
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Solution Overview
Problem
Existing weapon detection systems, such as metal detectors and UWB radar systems, face challenges in efficiently and cost-effectively identifying concealed weapons in dynamic environments with multiple entrances and exits, often causing bottlenecks and privacy concerns, and require extensive calibration for various weapon types.
Innovation Solution
An ultra-wideband (UWB) radar system using a convolutional neural network (CNN) for pattern recognition, which generates a prediction function through calibration with 'ground truth' data, allowing detection of objects-of-interest (OOIs) by analyzing electromagnetic wave reflections and triggering alerts when pattern recognition exceeds a threshold, without requiring synchronization with multiple arrays.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional metal detectors and x-ray screening systems are deployed at security checkpoints, then weapon detection capability is improved, but operational cost and time consumption increase significantly
Solution Approach 1:
The patent replaces traditional mechanical metal detection systems and x-ray imaging systems with an ultra-wideband radar system that uses electromagnetic wave reflections. The radar transmits UWB pulses and analyzes reflected signals to detect weapons, eliminating the need for physical metal detectors and x-ray machines, thereby reducing operational costs and improving throughput while maintaining detection reliability
2Measurement precision
If multiple UWB radar arrays are synchronized to improve detection accuracy, then measurement precision is improved, but device complexity and computational requirements increase
Solution Approach 1:
The patent employs a single UWB radar array that performs self-calibration and self-detection without requiring synchronization with multiple arrays. The system uses pattern recognition algorithms that analyze reflected electromagnetic waves independently, eliminating the need for complex inter-array synchronization mechanisms while maintaining high detection accuracy through advanced signal processing
3Reliability
If vision-based systems are used to track individuals, then detection capability is improved, but privacy concerns and adaptability to blocked views worsen
Solution Approach 1:
The patent replaces vision-based optical tracking systems with ultra-wideband radar that detects weapons through electromagnetic wave reflections. The radar system can penetrate clothing and detect concealed weapons without requiring direct line-of-sight visual contact, thereby maintaining detection reliability while adapting to situations where individuals are behind or partially blocked by opaque objects, and without raising privacy concerns associated with visual imaging
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system provides efficient, low-power, and privacy-friendly weapon detection capable of identifying OOIs through walls and clothing, with minimal signal loss, reducing bottlenecks and operational costs, and adaptable to changing environments.
Implementation Method 1
a receiver that receives reflected electromagnetic waves from objects in the ROI
Data Source
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Figure 3A~3B
AI summary
A system includes an ultra-wideband (UWB) array having a transmitter that transmits electromagnetic waves as UWB pulses toward a region-of-interest (ROI), and having a receiver that receives reflected electromagnetic waves from objects in the ROI and generates object data, and a pattern recognition device having a processor configured to provide operations. The processor is configured to provide instructions that obtain scanning data from reflected electromagnetic waves from the ROI until an event is triggered, when the event is triggered, access a heuristic created from calibration data that was previously obtained using the ROI and using the UWB array, analyze the scanning data with the heuristic utilizing a pattern recognition function derived from the calibration data, to determine whether an object-of-interest (OOI) pattern is recognized within the scanning data, and if an OOI pattern is recognized, generate an alert.