Structured Noise Suppression in Touch Sensing Arrays
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Touch sensing systems face performance degradation due to structured noise from various sources, which manifests as image artifacts in touch images, affecting the accuracy of touch detection and input processing in devices like touch screens.
Innovation Solution
The method involves determining and removing noise characteristics from respective groups of touch nodes in a masked touch image, specifically by averaging background touch signals to subtract noise offsets from unmasked touch signals, and iteratively refining this process until noise criteria are met, thereby suppressing structured noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional touch sensing methods are used, then touch detection capability is maintained, but structured noise degrades measurement precision
Solution Approach 1:
The touch image is divided into multiple groups of touch nodes (e.g., rows and columns). Noise characteristics are determined separately for each group, allowing localized noise suppression that preserves touch signal integrity while reducing structured noise artifacts.
Solution Approach 2:
The patent extracts noise characteristics from background touch signals in each group of touch nodes. By separating the noise component from the total signal and subtracting it, the method removes structured noise while maintaining the original touch detection capability.
2Measurement precision
If noise suppression processing is applied, then measurement precision improves, but device complexity increases
Solution Approach 1:
The system uses its own background touch signals to determine noise characteristics without requiring external calibration or additional hardware. The noise profile is derived from the device's own operational data, making the solution self-contained and reducing overall system complexity.
Solution Approach 2:
Noise characteristics are determined in advance for each group of touch nodes and stored as noise offsets. This preliminary processing allows rapid noise suppression during actual touch detection without real-time computational overhead, reducing processing complexity during operation.
Data Source
AI summary
Structured noise from various aggressors can be suppressed to improve touch performance. A respective noise characteristic can be determined for each respective group of touch nodes (e.g., row, column) among multiple groups of touch nodes in a masked touch image. The respective noise characteristic can be removed from the corresponding respective group of touch nodes in the touch image. For example, a respective noise characteristic can be determined for each respective row and/or for each respective column in the masked touch image. The respective noise characteristic can be removed from the respective row and/or column in the unmasked touch image. In some examples, the determining and subtracting of the noise characteristic can be repeated iteratively within a window of time and/or until one or more noise criteria are met.