Millimeter-Wave Radar Human Detection with Privacy-Preserving Micro-Doppler
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Solution Overview
Problem
Existing human detection technologies lack efficient methods to identify humans in a target environment without invading privacy, especially in applications combining radar technology with artificial intelligence.
Innovation Solution
A method and device that integrates millimeter-wave radar with artificial intelligence to extract micro-Doppler features from radar signals, using clustering and classification to identify human targets, enabling privacy-preserving human detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional human detection technologies are used, then human detection can be achieved, but privacy is invaded
Solution Approach 1:
The patent extracts only the necessary micro-Doppler features from radar signals for human detection, separating the detection function from comprehensive surveillance. By extracting only motion characteristics rather than full imaging data, the system achieves human detection without invading privacy.
Solution Approach 2:
The patent introduces micro-Doppler features as an intermediary representation between raw radar data and human detection. This intermediary feature set contains sufficient information for identification while being less intrusive than direct imaging or comprehensive data collection.
2Reliability
If radar signals are processed to extract human information, then human detection is enabled, but processing complexity increases
Solution Approach 1:
The patent extracts only the micro-Doppler feature components from complex radar signals, separating useful human identification information from unnecessary data. This extraction approach reduces processing complexity by focusing only on relevant features rather than processing entire signal datasets.
Solution Approach 2:
The patent segments the radar signal processing into distinct stages: micro-Doppler feature extraction, feature classification, and human detection. This segmentation allows each stage to be optimized independently, reducing overall system complexity while maintaining detection capability.
3Measurement precision
If millimeter-wave radar technology is combined with artificial intelligence, then detection accuracy is improved, but system complexity increases
Solution Approach 1:
The patent introduces micro-Doppler features as an intermediary that bridges radar signal processing and artificial intelligence classification. This intermediary layer simplifies the integration by converting complex radar data into standardized feature representations that can be processed by AI models, reducing direct system integration complexity.
Solution Approach 2:
The patent divides the system into separate modules: radar signal processing module, micro-Doppler feature extraction module, and AI classification module. This modular segmentation allows each component to be developed and optimized independently, reducing overall system integration complexity while maintaining high 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 automatic control and monitoring in environments by accurately identifying humans without invading privacy, facilitating applications such as home automation and security.
Implementation Method 1
extracting, from the millimeter-wave radar signal, information of a moving point in the target environment; determining, according to the information of the moving point in the target environment, a micro-Doppler feature of each target
Data Source
AI summary
The present disclosure discloses a human detection method and device, an electronic apparatus, and a storage medium. The method includes: a millimeter-wave radar signal of a target environment (101) is obtained; information of a moving point in the target environment (102) is extracted from the millimeter-wave radar signal; a micro-Doppler feature of each target in the target environment (103) is determined according to the information of the moving points in the target environment, wherein the target is formed by at least one moving point; and a target whose category is human in the target environment (104) is identified according to the micro-Doppler feature of each target in the target environment. The millimeter-wave radar technology is combined with artificial intelligence technology, so as to enable human detection in the target environment without invading human privacy, thus providing the possibility of achieving automatic control, monitoring and other operations of the target environment.