Radar Gesture Recognition Thresholds and Diagrams
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current macro gesture recognition systems face challenges in accuracy due to sensitivity to ambient lighting, privacy concerns, and high battery consumption, especially with optic sensor-based solutions. Additionally, radar-based solutions lack robustness and have high environmental dependency, leading to sub-optimal gesture classification accuracies and high false-alarm rates.
Innovation Solution
The proposed solution involves an electronic device equipped with a transceiver that transmits and receives radar signals to obtain a range Doppler map. The processor determines detection thresholds for each range-bin value, generating a time velocity diagram (TVD) and a time angle diagram (TAD) to enhance macro gesture recognition accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If optic sensor based solutions are used for gesture recognition, then gesture recognition performance is improved, but sensitivity to ambient lighting conditions and battery consumption increase
Solution Approach 1:
The patent replaces optical sensors with radar-based sensing technology. Radar uses electromagnetic waves in the microwave frequency range to detect gestures, eliminating dependence on visible light conditions. The radar system transmits signals and processes the reflected signals to extract gesture information, providing robust performance across varying ambient lighting conditions while maintaining measurement precision.
2Object-affected harmful factors
If LIDAR based solutions are used for gesture recognition, then lighting conditions and privacy challenges are overcome, but cost increases
Solution Approach 1:
The patent employs radar technology that uses readily available microwave components and signal processing techniques, avoiding the need for expensive LIDAR hardware. The radar system leverages existing transceivers and processors, making it cost-effective for mass production while achieving comparable or superior performance in gesture recognition applications.
3Ease of manufacture
If radar based solutions are used for gesture recognition, then cost and privacy concerns are reduced, but false-alarm rates and environmental dependency increase
Solution Approach 1:
The patent segments the gesture recognition process into distinct stages: signal transmission, echo reception, range-Doppler map generation, detection threshold determination, and TVD/TAD construction. Each stage is optimized independently with specialized algorithms, allowing precise control over false-alarm rejection and improving overall system reliability while maintaining cost-effectiveness.
Solution Approach 2:
The patent implements dynamic detection thresholds that adapt to environmental conditions and signal characteristics. The system continuously adjusts thresholds based on the range-Doppler map analysis, enabling robust gesture recognition across varying environmental conditions while minimizing false alarms through real-time parameter optimization.
4Measurement precision
If detection thresholds are determined for each range-bin value in radar signals, then macro gesture recognition accuracy is improved, but processing complexity increases
Solution Approach 1:
The patent applies different detection thresholds to different range-bin values in the range-Doppler map, optimizing detection sensitivity for specific distances. This local quality approach allows the system to tailor threshold values to the characteristics of gestures at different ranges, improving macro gesture recognition accuracy while managing processing complexity through efficient algorithm design.
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 improves the accuracy of macro gesture recognition by reducing false-alarm rates and enhancing classification accuracy, making the system more robust and less environmentally dependent.
Implementation Method 1
obtain a range Doppler map associated with the plurality of radar signals
Implementation Method 2
transmitting and receiving a plurality of radar signals corresponding with a gesture
Data Source
AI summary
An electronic device includes a transceiver. The transceiver is configured to transmit and receive a plurality of radar signals corresponding with a gesture. The electronic device further includes a processor operatively coupled to the transceiver. The processor is configured to obtain a range Doppler map associated with the plurality of radar signals, and determine a plurality of detection thresholds, each detection threshold corresponding with a range-bin value of the range Doppler map. The processor is further configured to generate, based on the determined plurality of detection thresholds, a time velocity diagram (TVD) and a time angle diagram (TAD) corresponding with the gesture.