Capacitive Proximity Sensing With Drift-Suppressed Baseline Filtering
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Solution Overview
Problem
Existing capacitive proximity detectors in portable devices are susceptible to drift, particularly from thermal fluctuations, which can mask the signal of interest when the approach is slow, leading to reduced sensitivity and precision in detecting user proximity.
Innovation Solution
A digital drift-suppression filter that estimates and subtracts a baseline signal, using a baseline estimator to generate a drift-suppressed signal by incrementing the baseline based on the variation of the proximity signal, with symmetrical threshold checks and resets, effectively suppressing thermal and other drifts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a straightforward high-pass filter or running average is used to suppress drift, then the drift is reduced, but the desired signal is also reduced particularly when the signal varies gradually
Solution Approach 1:
The patent applies different processing treatments to different portions of the signal based on local characteristics. The signal is divided into segments where gradual variations are treated differently from abrupt changes. The filter adapts its behavior locally - using stronger suppression for drift components and preserving signal components based on their local temporal characteristics
Solution Approach 2:
The patent employs a dynamic filtering approach where the filter characteristics change over time based on signal conditions. The running average window adapts its length and the filter coefficients are adjusted dynamically to distinguish between drift and signal components, allowing the system to maintain high suppression effectiveness while preserving signal integrity under varying conditions
2Reliability
If a running average is used to represent and subtract the drift, then the drift suppression is achieved, but the sensitivity is reduced when the user approaches slowly
Solution Approach 1:
The patent implements dynamic adaptation of the filtering parameters based on the detected signal characteristics and approach speed. When slow approach is detected, the system adjusts the running average window and filter strength to maintain sensitivity while still suppressing drift, allowing the filter to respond appropriately to different temporal scales of signal variation
3Device complexity
If the background capacity and its fluctuations are not eliminated, then the drift suppression is simpler, but the proximity signal is completely masked
Solution Approach 1:
The patent employs feedback mechanisms where the detected signal characteristics are used to continuously adjust the drift suppression parameters. The system monitors the proximity signal and adapts the filter strength and characteristics in real-time, creating a closed-loop system that optimizes the balance between drift suppression and signal preservation based on actual operating conditions
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 improved immunity to drift, maintaining high sensitivity and precision in detecting proximity even with slow approaches, reducing noise and retaining the desired signal integrity.
Implementation Method 1
The detector is sensitive to the capacitance Cx of an electrode 20 that will increase slightly at the approach of a user's hand, face or body
Implementation Method 2
Capacitive proximity detection depends critically on drift suppression
Data Source
Figure 1~2
Figure 3
AI summary
A portable device including a capacitive proximity sensor can suppress a drift superimposed to the capacitive proximity signal and the corresponding method. A processor generates a baseline value by integrating a series of values that are derived from the slope of the proximity signal, when the slope is within stated limits, or a fixed value outside of the stated limits.