Radar Gesture Recognition Using Signal Variance Normalization
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Solution Overview
Problem
Existing gesture recognition methods using cameras face challenges in low-light environments and require complex training, while radar-based systems suffer from reliability issues due to variations in distance and orientation between the radar sensor and the user.
Innovation Solution
A gesture recognition device and method using a radar system that includes a signal receiver, clutter remover, signal intensity variance acquirer, ToA variance acquirer, frequency acquirer, and a reference database to determine gestures based on signal intensity variance, ToA variance, and frequency, ensuring robustness against changes in distance and orientation, and adaptability to lighting conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If gesture recognition uses a camera, then it can capture hand gestures, but it requires line of sight and fails in low-light environments
Solution Approach 1:
The patent replaces the optical camera system with a radar-based gesture recognition system. Radar uses electromagnetic waves to detect hand gestures through radio wave reflection, eliminating dependency on visible light and providing reliable operation in low-light or dark environments while maintaining gesture recognition capability without requiring line of sight
2Adaptability or versatility
If gesture recognition uses a wearable device, then it is not limited by lighting conditions, but it requires high cost and complicated training
Solution Approach 1:
The radar-based system performs gesture recognition autonomously by analyzing reflected radio waves from the user's hand movements. The system automatically extracts feature information including signal intensity variance, time of arrival variance, and frequency characteristics, eliminating the need for complex training procedures or wearable devices while providing reliable operation across lighting conditions
3Adaptability or versatility
If gesture recognition uses radar, then it can work in low-light environments, but recognition performance deviates with distance and orientation changes
Solution Approach 1:
The patent compensates for distance and orientation variations by extracting multiple invariant feature parameters from the radar signals: signal intensity variance, time of arrival variance, and frequency characteristics. These parameters are normalized and compared against reference database values, allowing the system to maintain consistent gesture recognition accuracy despite changes in user distance or orientation relative to the radar sensor
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
The solution provides reliable and robust gesture recognition performance, effectively applicable in driver environments with varying lighting conditions, by normalizing and comparing feature information from user gestures against a reference database, enhancing recognition accuracy and usability.
Implementation Method 1
a signal receiver unit configured to receive radar signals reflected by a gesture of a user
Implementation Method 2
receive radar signals reflected by a gesture of a user
Implementation Method 3
a clutter remover unit configured to remove clutter from the signals received at the signal receiver unit
Implementation Method 4
a signal intensity variance acquirer unit configured to acquire a variance of signal intensity values from the reflected signals from which the clutter has been removed
Implementation Method 5
a ToA variance acquirer unit configured to acquire ToA's (times of arrival) corresponding to maximum values of fast time signals forming the reflected signals from which the clutter has been removed and configured to acquire a variance of the acquired ToA's corresponding to the maximum values
Implementation Method 6
a frequency acquirer unit configured to compute a frequency of the reflected signals from which the clutter has been removed
Data Source
AI summary
A gesture recognition device and method using radar are proposed. The gesture recognition device includes: a signal receiving unit for receiving a radar signal reflected by a gesture of a user; a clutter removing unit for removing clutter from the signal received by the signal receiving unit; and a signal magnitude variance acquiring unit for acquiring the variance of a signal magnitude from a reflection signal from which the clutter has been removed. The proposed device and method have an advantage of enabling a gesture to be recognized with performance that is robust to changes in distance and direction between a user and a radar sensor.