Millimeter-Wave Radar Human Behavior Detection Power Control
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Solution Overview
Problem
Current millimeter-wave radar systems face challenges in efficiently processing RF signals to determine human behavior and vital signs, requiring improved methods for macro-Doppler, micro-Doppler, and vital-Doppler signal processing to accurately detect and classify targets within a field of view.
Innovation Solution
The system employs a method that identifies targets using millimeter-wave radar data, performing macro-Doppler, micro-Doppler, and vital-Doppler processing across distinct frames to determine the presence of signals, activating range bins accordingly, and adjusting power modes based on signal presence or absence, while utilizing filtering techniques to detect heart rates and breathing cycles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If macro-Doppler, micro-Doppler, and vital-Doppler processing are performed continuously at full power, then detection accuracy and classification precision are improved, but power consumption increases
Solution Approach 1:
The radar system dynamically adjusts its operating power level based on detected activity. When motion is detected at one power level, the system transitions to a different power level for continued monitoring. This dynamic adaptation allows the system to maintain detection accuracy when needed while conserving power during idle periods.
Solution Approach 2:
The system implements periodic scanning at reduced power levels between active detection periods. Instead of continuous full-power operation, the radar performs intermittent scans at lower power, only escalating to full processing capability when targets or motion are detected, thereby reducing overall power consumption while maintaining detection effectiveness.
2Measurement precision
If multiple Doppler processing frames are captured and processed, then human behavior classification accuracy is improved, but processing time and computational complexity increase
Solution Approach 1:
The Doppler processing is divided into separate functional frames: macro-Doppler frames for gross motion detection, micro-Doppler frames for fine motion analysis, and vital-Doppler frames for vital sign extraction. This segmentation allows the system to process different aspects of target behavior in parallel or in optimized sequences, reducing overall processing time while maintaining comprehensive analysis capability.
Solution Approach 2:
The system performs preliminary macro-Doppler processing to detect gross motion before committing to more computationally intensive micro-Doppler and vital-Doppler processing. This preliminary action allows the system to quickly identify targets of interest and only then allocate computational resources for detailed behavior analysis, reducing unnecessary processing time for non-targets.
3Measurement precision
If the radar sensor operates at high power mode continuously, then signal detection sensitivity is improved, but energy efficiency deteriorates
Solution Approach 1:
The radar system dynamically transitions between power modes based on detection needs. High power mode is activated only when targets are detected or during critical monitoring periods, while low power mode is used during idle periods. This dynamic power management maintains detection sensitivity when required while dramatically improving energy efficiency during normal operation.
Solution Approach 2:
The system uses feedback from detection results to control power mode selection. When motion or targets are detected, the system feedback-triggered transition to high power mode for detailed analysis. When no activity is detected for extended periods, feedback triggers a transition to low power mode, creating an adaptive energy-efficient operation cycle.
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 detection and classification of human behavior, including heart rates and breathing cycles, while optimizing power consumption by adapting power modes based on signal presence, thereby enhancing the efficiency of millimeter-wave radar systems.
Implementation Method 1
Some radar systems include a transmit antenna to transmit the RF signal, a receive antenna to receive the RF, as well as the associated RF circuitry used to generate the transmitted signal and to receive the RF signal
Implementation Method 2
capturing radar data corresponding to the set of targets across a macro-Doppler frame; performing macro-Doppler processing on the macro-Doppler frame and determining whether a macro-Doppler signal is present
Data Source
Figure 1A
Figure 1B
Figure 2A
AI summary
An embodiment method includes identifying a set of targets within a field of view of a millimeter-wave radar sensor based on radar data received by the millimeter-wave radar sensor; capturing radar data corresponding to the set of targets across a macro-Doppler frame; performing macro-Doppler processing on the macro-Doppler frame and determining whether a macro-Doppler signal is present in the macro-Doppler frame based on the macro-Doppler processing; capturing radar data corresponding to the set of targets across a micro-Doppler frame, wherein the micro-Doppler frame has a duration superior or equal to a duration of a first plurality of macro-Doppler frames; performing micro-Doppler processing on the micro-Doppler frame and determining whether a micro-Doppler signal is present in the micro-Doppler frame based on the micro-Doppler processing; and activating at least one range bin of a plurality of range bins in response to a determination that at least one of the macro-Doppler signal or the micro-Doppler signal is present.