Pseudoinverse Noise Equalization for Differential Measurement Systems
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Solution Overview
Problem
Differential measurement systems face challenges in noise equalization, particularly with differential-mode noise, which can disrupt signal representation and affect accuracy in mutual capacitance measurement systems due to physical asymmetries and channel effects.
Innovation Solution
The implementation of pseudoinverse-based noise equalization, where a pseudoinverse channel matrix is used to reduce channel effects and differential-mode noise by converting differential measurement signals into balanced signals, thereby improving signal accuracy and noise cancellation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If differential measurement systems are used, then signal representation is improved, but differential-mode noise disrupts accuracy
Solution Approach 1:
A pseudoinverse equalization system is introduced as an intermediary component between the differential measurement system and the output. This system processes the differential signals through pseudoinverse channel matrices to cancel differential-mode noise while preserving the measurement accuracy, effectively mediating between the conflicting requirements of signal representation and noise rejection
2Measurement precision
If noise equalization is applied, then measurement accuracy is improved, but device complexity increases
Solution Approach 1:
The patent replaces complex hardware-based noise equalization mechanisms with software-based pseudoinverse calculations. By using mathematical algorithms (pseudoinverse channel matrices) instead of complex physical equalization circuits, the system achieves noise cancellation while minimizing additional device complexity
3Ease of manufacture
If physical asymmetries are present, then manufacturing is simplified, but channel effects increase noise
Solution Approach 1:
The patent compensates for physical asymmetries by dynamically adjusting the parameters of the pseudoinverse channel matrices. These matrices are calibrated to account for specific channel characteristics and asymmetries, allowing the system to maintain measurement accuracy despite manufacturing variations and physical asymmetries in the differential signaling paths
Data Source
AI summary
A method includes obtaining a first single-ended measurement signal and a second single-ended measurement signal; and producing an equalized measurement signal at least partially based on a predetermined pseudoinverse channel matrix and one or more of: the first single-ended measurement signal and the second single-ended measurement signal.