Capacitive Imaging Noise Reduction via Self-Capacitance Segmentation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Capacitive imaging devices using arrays of row and column electrodes face challenges with noise interference from voltage sources, which affects measurement accuracy and reliability, especially in hidden object detection applications.
Innovation Solution
The method involves measuring cross-capacitance by obtaining self-capacitance values from row and column electrodes separately and combined, then using these measurements to isolate and subtract noise-related capacitances, allowing for accurate detection of dielectric features without significant noise interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If cross-capacitance measurement is performed using row and column electrodes, then the number of connections is reduced to M plus N, but noise from voltage sources couples to pickup lines affecting measurement accuracy
Solution Approach 1:
The measurement process is segmented into multiple sequential steps: first measuring self-capacitance of row electrodes, then self-capacitance of column electrodes, and finally combined self-capacitance. This segmentation allows isolation and subtraction of noise components from each measurement stage, improving overall measurement accuracy while maintaining the simplified M plus N connection structure
Solution Approach 2:
Self-capacitance measurements of row and column electrodes are performed preliminarily before the actual cross-capacitance measurement. These preliminary measurements capture the noise characteristics of individual electrode lines, which are then used to correct the final cross-capacitance measurement, thereby compensating for noise coupling in advance
2Reliability
If charge amplifier is inserted to eliminate pickup electrode capacitive loading, then measurement reliability is improved, but device complexity increases
Solution Approach 1:
The system performs self-characterization by measuring the self-capacitance of each electrode line and using this information to correct subsequent cross-capacitance measurements. This self-service approach eliminates the need for external charge amplifiers or complex calibration equipment, maintaining measurement reliability while avoiding additional circuit complexity
Solution Approach 2:
The measured self-capacitance values are fed back into the measurement process to correct the cross-capacitance readings. This feedback mechanism compensates for capacitive loading effects and noise coupling without requiring additional active components, thereby maintaining reliability while minimizing circuit complexity
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 enhances the accuracy and stability of capacitive imaging by minimizing noise effects, enabling effective detection of both near and remote dielectric features with improved resolution and reduced interference from external noise sources.
Implementation Method 1
sense the M times N row-to-column mutual or cross-capacitances concentrated near row-to-column crossovers
Implementation Method 2
cross-capacitance coupling from a drive electrode to a pickup electrode only takes place near their crossover
Data Source
AI summary
A capacitive imaging method or device using an array of row electrodes 101 and column electrodes 102 on a substrate 100, wherein cross-capacitance between row and column electrodes is obtained from row electrode 101 self-capacitance measured with the remaining electrodes grounded, column electrode 102 self-capacitance measured with the remaining electrodes grounded, and combined row and column electrode self-capacitance measured with the remaining electrodes grounded. A preferred embodiment is a hand-held wall scanner for detecting hidden features having a two-dimensional display the size of the array and located over it. Hidden features influencing row-to-column cross-capacitances are thus imaged in real size and at their real location.