Impulse Response Filter for CDM Signal Measurement Accuracy
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Solution Overview
Problem
Existing capacitive sensing devices face challenges in accurately filtering code division multiplexed (CDM) signals, particularly in determining user input and interface reporting, due to limitations in current filtering methods that do not effectively handle overlapping and non-overlapping code phases.
Innovation Solution
The implementation of an impulse response filter that applies different filter weights to CDM signals over multiple signal bursts, allowing for overlapping filtering and improved measurement accuracy by extending the filter length beyond the code length, thereby enhancing report rates and reducing correlation between sequential measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional boxcar filtering is used to filter CDM signals, then the filtering process is simple and computationally efficient, but the measurement accuracy is insufficient and correlation between sequential measurements increases
Solution Approach 1:
The patent changes the filtering parameters by extending the filter length beyond the code length and applying different filter weights to different signal bursts. This transforms the traditional boxcar filter into an impulse response filter with variable weights, improving measurement accuracy while managing complexity through systematic parameter selection
Solution Approach 2:
The patent introduces dynamic filtering by applying different filter weights to different signal bursts based on their temporal position and correlation characteristics. This dynamic approach allows the filter to adapt to varying signal conditions and reduce correlation between sequential measurements
2Reliability
If the filter length is extended beyond the code length to reduce correlation between measurements, then the measurement independence improves, but the computational complexity and processing time increase
Solution Approach 1:
The patent performs preliminary actions by pre-calculating and storing impulse response filter weights before actual signal processing. This preparation work is done offline, so it does not add to real-time processing time during signal bursts, while still achieving the benefit of reduced measurement correlation
Solution Approach 2:
The patent applies different filter weights to different portions of the signal bursts based on local characteristics. By tailoring the filter response to specific signal segments rather than applying a uniform filter, the system achieves better measurement independence without uniformly increasing processing complexity across all data
3Measurement precision
If different filter weights are applied to overlapping signal bursts to improve accuracy, then the user input detection accuracy improves, but the computational load and processing complexity increase
Solution Approach 1:
The patent implements periodic filtering by applying impulse response filters at regular intervals corresponding to signal burst periods. This periodic structure allows for optimized computational routines that can be efficiently repeated, maintaining processing efficiency while achieving improved detection accuracy through consistent application of the filtering method
Data Source
AI summary
An example method of capacitive sensing includes: receiving at least one code division multiplexed (CDM) signal transmitted from different transmitters using different codes over a plurality of signal bursts, wherein a length of each of the different codes is equal to or greater than a number of the different transmitters; filtering the at least one CDM signal using an impulse response filter, wherein the filtering comprises: accumulating the at least one CDM signal over the plurality of signal bursts to obtain measurements of the at least one CDM signal; and for the measurements of the at least one CDM signal, applying different filter weights to the resulting signals over a number of the plurality of signal bursts that is greater than the length of the different codes.