Touch Sensor Reference Sequence Correlation for Noise Mitigation
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Solution Overview
Problem
Touch sensors face challenges in accurately detecting touch input due to noise interference from various sources, which can degrade the signal-to-noise ratio (SNR) and lead to erroneous detection, especially when placed proximate to displays that couple noise capacitively through optically clear adhesives.
Innovation Solution
The method involves establishing a first reference sequence and reducing a set of candidate reference sequences using a rule set to derive a smaller set, calculating touch detection performance scores, and configuring receive circuits to correlate signals using selected candidate reference sequences in a combined correlation operation, effectively mitigating noise and improving SNR without increasing power consumption or complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional single reference sequence correlation is used, then the system complexity is low, but noise mitigation is insufficient leading to poor touch detection accuracy
Solution Approach 1:
The patent segments the correlation processing into multiple independent parallel operations, each using a different reference sequence. Instead of one complex correlation, the system performs multiple simpler correlations simultaneously with different reference sequences (e.g., QPSK, BPSK, MSK), then combines the results. This segmentation allows noise mitigation through diversity while keeping each individual correlation operation simple and manageable.
Solution Approach 2:
The patent merges multiple correlation results from different reference sequences into a single combined output. The receive circuit correlates the received signal with multiple reference sequences and combines the correlation outputs, thereby leveraging the strengths of different sequences to mitigate various noise types while achieving superior touch detection accuracy compared to any single reference sequence alone.
2Reliability
If multiple reference sequences are used for correlation, then noise mitigation improves, but power consumption increases
Solution Approach 1:
The patent segments the noise mitigation function across multiple parallel correlation operations rather than using one computationally intensive method. Each correlation with a different reference sequence handles specific noise characteristics, and the segmentation allows the system to achieve robust noise immunity through diversity while managing power consumption by using efficient, simple correlation algorithms in parallel.
Solution Approach 2:
The patent changes the parameter of reference sequence type to optimize performance. By selecting from different modulation schemes (QPSK, BPSK, MSK) as reference sequences, the system adapts to different noise conditions and optimizes the balance between noise immunity and power consumption. Each sequence type has different computational requirements and noise characteristics, allowing parameter-based optimization.
3Reliability
If multiple reference sequences are correlated, then touch detection reliability improves, but processing time increases
Solution Approach 1:
The patent segments the processing into parallel independent correlation operations that can be executed simultaneously. By dividing the task into multiple parallel streams (each correlating with a different reference sequence), the system achieves reliable touch detection through multiple perspectives while avoiding sequential processing delays. The parallel architecture ensures that processing time does not increase linearly with the number of reference sequences.
4Measurement precision
If a single reference sequence is used, then the system is simple to implement, but touch detection precision deteriorates due to noise
Solution Approach 1:
The patent merges multiple correlation results from different reference sequences to achieve superior touch detection precision. The receive circuit combines the outputs of parallel correlations, leveraging the complementary noise mitigation properties of different sequences. This merging approach achieves high precision without requiring any single complex processing method, instead using the collective strength of multiple simpler operations.
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 of touch input detection by effectively mitigating noise interference, improving the SNR of touch sensor output, and maintaining operational efficiency without increasing power consumption or complexity.
Implementation Method 1
Some touch sensors are configured to detect touch input by sensing changes in capacitance between rows and columns of an electrode matrix
Implementation Method 2
placed proximate to displays that couple noise capacitively through optically clear adhesives
Data Source
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AI summary
Embodiments are disclosed that relate to touch input detection in a touch sensor. One example provides a method comprising establishing a first reference sequence, starting with a first set of candidate reference sequences each differing from the first reference sequence, reducing the first set of candidate reference sequences by applying a rule set to the first set to derive a relatively smaller second set of candidate reference sequences, for each candidate reference sequence in the second set of candidate reference sequences, calculating a touch detection performance score of a combined reference sequence, and configuring at least a portion of a receive circuit to correlate signals to at least one of the touch detection conditions by using the first reference sequence in a combined correlation operation with at least a selected candidate reference sequence from the second set of candidate reference sequences.