Radar People Counting via 2-D Angular Intensity Maps
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Solution Overview
Problem
Existing people counting technologies, particularly those based on camera images, face challenges in accuracy due to varying lighting conditions, and there is a need for advanced techniques that can accurately count a large number of people using radar measurements.
Innovation Solution
The use of 2-D angular intensity maps and Doppler frequency-shift bins from radar measurement data allows for accurate people counting, enabling the separation of individuals even when close together in a scene.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If camera-based people counting is used, then implementation is simple and cost-effective, but accuracy varies with lighting conditions
Solution Approach 1:
The patent replaces camera-based optical detection with radar-based electromagnetic wave detection. The radar sensor captures reflection signals from persons in the scene, transforming the detection mechanism from optical to electromagnetic, thereby eliminating sensitivity to lighting conditions while maintaining implementation feasibility through standard radar technology
Solution Approach 2:
The patent transforms radar measurement data by changing parameters through Fourier transformation, converting time-domain reflection signals into frequency-domain Doppler spectra. This parameter transformation enables accurate people counting by extracting motion characteristics that are independent of lighting conditions
2Measurement precision
If radar-based people counting is used, then accuracy is improved and lighting independence is achieved, but device complexity increases
Solution Approach 1:
The patent segments the complex radar signal processing into distinct stages: capturing reflection signals, performing Fourier transformation to obtain Doppler spectra, identifying peaks in the spectra, and counting persons based on peak characteristics. This segmentation simplifies the overall system by breaking down complex operations into manageable, independent modules
Solution Approach 2:
The patent extracts only the essential information needed for people counting from the radar measurements. By focusing on Doppler frequency peaks and their characteristics, the system discards redundant data, thereby reducing processing complexity while maintaining counting accuracy
3Ease of operation
If traditional radar measurement is used, then implementation is straightforward, but ability to separate close persons is insufficient
Solution Approach 1:
The patent introduces the Doppler frequency dimension to the traditional radar measurement. By transforming the data into Doppler frequency bins and analyzing spectral peaks, the system creates an additional differentiation dimension that enables separation of persons who are spatially close but have different motion characteristics
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
This approach enables accurate and reliable people counting, independent of lighting conditions, and can handle a large number of individuals by increasing the degree of freedom in the counting process.
Implementation Method 1
respective data samples that are acquired by a radar sensor monitoring a scene
Implementation Method 2
Doppler frequency-shift bins can be created based on range-Doppler intensity maps
Data Source
AI summary
In an embodiment, a method includes: obtaining one or more radar measurement frames, each one of the one or more radar measurement frames including respective data samples acquired by a radar sensor monitoring a scene; for each one of the one or more radar measurement frames, determining a respective 2-D angular intensity map of the scene based on the respective radar measurement frame; and performing a people counting operation based on the one or more 2-D angular intensity maps determined for the one or more radar measurement frames to determine a people count for the scene.