Biometric Identification Device Using Multi-Antenna Correlation
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Solution Overview
Problem
Existing biometric identification systems using electromagnetic waves often incorrectly identify individuals when the subject's data is not included in the teacher data, leading to a high equal error rate due to false acceptance and rejection rates.
Innovation Solution
The system employs multiple transmission and reception antenna elements to capture a broader range of features from a subject's reflection signals, calculating correlation coefficients between teacher signals and reception signals to accurately identify the subject by determining if the maximum correlation value exceeds a threshold.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single transmitter and receiver are used for biometric identification, then the device complexity is low, but the measurement precision and reliability are insufficient leading to high equal error rate
Solution Approach 1:
The system segments the identification task by using multiple transmission antenna elements (M≥1) and multiple reception antenna elements (N≥3) to capture multiple reflection signals from different spatial positions. This segmentation of the measurement process across multiple antenna elements enables more comprehensive feature extraction from the subject, improving identification accuracy while distributing the complexity across modular components
Solution Approach 2:
The invention transitions from a single-transmitter-single-receiver configuration to a multi-antenna array system that captures signals from multiple spatial dimensions. By arranging N≥3 reception antenna elements in different positions and calculating correlation coefficients across M×N signal combinations, the system adds spatial dimensionality to the measurement, enabling more robust biometric identification that is less susceptible to positional variations
2Reliability
If the subject data is not included in the teacher data, then false acceptance occurs leading to high equal error rate, but adding more verification methods increases device complexity
Solution Approach 1:
The system implements feedback through correlation coefficient calculation between the measured reflection signals and pre-stored teacher data. By computing correlation coefficients for M×N signal combinations and comparing against a threshold, the system provides a quantitative feedback mechanism that reliably distinguishes between matching and non-matching subjects, reducing false acceptance rates without requiring complex additional verification hardware
Solution Approach 2:
The invention changes the parameter of signal comparison by using correlation coefficient calculation across multiple antenna signal combinations rather than simple signal matching. This parameter transformation from direct signal comparison to statistical correlation analysis enables more reliable discrimination between subjects, particularly when the subject is not in the teacher data, thereby reducing false acceptance rates
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 reduces the equal error rate by accurately distinguishing between subjects included in the teacher data and those not, thereby minimizing erroneous identifications.
Implementation Method 1
receiving a first reception signal including a reflection signal obtained as a result of the first transmission signal being reflected by the first living body
Data Source
Figure 1
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Figure 4
AI summary
An identification device includes: M transmission antenna elements each of which transmits a first transmission signal to a predetermined area including a first living body; N receivers disposed surrounding the predetermined area, and each including a reception antenna element and receiving, using the reception antenna element, a first reception signal including a reflection signal obtained as a result of the first transmission signal being reflected by the first living body, during a predetermined period; a memory (41) storing teacher signals (42) which are M × N second reception signals obtained about a second living body; and a circuit (40) which calculates a plurality of correlation coefficients from the teacher signals (42) and M × N first reception signals obtained as a result of each of the N receivers receiving the first reception signal, performs biometric authentication of the first living body according to whether or not the maximum value of the plurality of correlation coefficients calculated exceeds a threshold, and when the biometric authentication of the first living body is to be performed, identifies by a predetermined method the first living body and the second living body as identical.