FMCW Radar Stationary Human Detection via Respiratory Micro-Motion
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Solution Overview
Problem
Conventional human presence sensing systems fail to accurately detect stationary humans, as they rely on detecting large motions and cannot infer presence without movement.
Innovation Solution
A frequency-modulated continuous wave (FMCW) radar system that transmits and receives signals to map images of an area, detect differences, and identify objects by determining if they are animate or inanimate, and specifically if they are breathing, using periodic movement frequencies within human or animal respiratory ranges, and counting the number of legs to differentiate between humans and animals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional motion-based sensors are used to detect human presence, then large motions can be detected, but stationary humans cannot be detected
Solution Approach 1:
The system changes the detection parameter from large-scale motion detection to micro-motion detection of respiratory patterns. By analyzing subtle periodic movements in the 0.1-5 Hz frequency range corresponding to breathing, the system can detect stationary humans that conventional motion sensors miss, while still maintaining the ability to detect larger motions when they occur.
2Measurement precision
If FMCW radar is used to detect micro movements, then stationary humans can be detected, but the system complexity increases
Solution Approach 1:
The system performs preliminary action by capturing a commissioning image of the environment before monitoring begins. This baseline image allows the system to detect only changes from the known static environment, filtering out permanent structures and focusing computational resources on detecting dynamic elements like breathing humans, thereby reducing ongoing processing complexity.
Solution Approach 2:
The detection process is segmented into distinct stages: commissioning image capture, change detection, respiratory pattern analysis, and classification. This segmentation allows each module to be optimized independently and simplifies the overall system architecture by breaking down the complex task of stationary human detection into manageable components.
3Measurement precision
If image mapping and comparison is used to detect changes, then object detection is enabled, but processing time increases
Solution Approach 1:
The system extracts only the essential information needed for detection by comparing change detection data against the commissioning image. Instead of processing entire high-resolution images continuously, it extracts only the differential changes and focuses analysis on those specific regions, significantly reducing processing time while maintaining detection accuracy.
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
Enables accurate detection of human presence without requiring motion, allowing for precise identification of humans and animals through respiratory rate analysis and leg count, improving presence detection accuracy in static conditions.
Implementation Method 1
transmitting commissioning frequency-modulated continuous wave (FMCW) radar signals throughout an area using a radar transceiver of a FMCW radar system
Implementation Method 2
frequency-modulated continuous wave (FMCW) radar signals
Implementation Method 3
detecting movements of the object using the current FMCW radar signals; determining the movements are periodic having a first frequency
Data Source
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AI summary
A method of detecting a presence of an object including: transmitting commissioning frequency-modulated continuous wave (FMCW) radar signals throughout an area using a FMCW radar system; mapping a commissioning image of the area using the commissioning FMCW radar signals; transmitting current FMCW radar signals throughout an area using the FMCW radar system; mapping a current image of the area using the current FMCW radar signals; detecting a difference between the current image and the commissioning image; identifying an object as the difference between the current image and the commissioning image; and determining an identity of the object.