Integrated Capacitive Sensor Sampling for Aliasing-Resistant EMC
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Solution Overview
Problem
Integrated Capacitive Sensor systems face significant challenges in reducing spectral noise sensitivity and electromagnetic compatibility (EMC) susceptibility, particularly due to the aliasing effect caused by interference frequencies equal or multiple to the sampling frequency.
Innovation Solution
The method involves generating multiple sampling frequencies from an oscillator or frequency divider and calculating the digital representative of the input signal as a reverse weighted average of differences between subsequent measurements at these frequencies, reducing spectral noise sensitivity and improving EMC robustness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a low-pass anti-aliasing filter is used to reduce spectral noise sensitivity, then spectral noise sensitivity is reduced, but device complexity increases and high-frequency signal attenuation occurs
Solution Approach 1:
The patent replaces the traditional hardware low-pass anti-aliasing filter with a software-based digital signal processing approach. Multiple measurements are taken at different sampling frequencies and processed algorithmically through reverse weighted averaging, substituting physical filtering components with computational methods to achieve noise reduction without the associated hardware complexity and signal attenuation issues
Solution Approach 2:
The patent changes the sampling frequency parameter dynamically by performing measurements at multiple different sampling frequencies rather than a single fixed frequency. This parameter variation allows the system to avoid aliasing effects and reduce spectral noise sensitivity through algorithmic processing of the varied frequency data, eliminating the need for fixed-frequency hardware filters
2Measurement precision
If the sensitivity of the Switched Capacitor Integrator is increased to improve measurement precision, then measurement precision is improved, but susceptibility to interference frequencies (aliasing effect) increases
Solution Approach 1:
The patent implements periodic measurements at multiple different sampling frequencies rather than continuous measurement at a single frequency. By periodically switching between different sampling rates and combining the results through reverse weighted averaging, the system maintains high sensitivity while periodically avoiding aliasing interference through frequency variation
Solution Approach 2:
The patent introduces an intermediary algorithmic processing step that mediates between the high-sensitivity sensor measurements and the final output. The reverse weighted averaging algorithm acts as an intermediary that processes measurements from multiple frequencies, reducing aliasing effects while preserving the benefits of high sensor sensitivity
3Reliability
If multiple sampling frequencies are used to reduce aliasing effects, then EMC robustness is improved, but measurement time and processing complexity increase
Solution Approach 1:
The patent performs measurements at multiple sampling frequencies, which is more than the single frequency traditionally used. This excessive action of measuring at multiple frequencies provides redundant data that, when processed through reverse weighted averaging, reduces aliasing effects and improves EMC robustness while the processing algorithm efficiently combines these measurements
Data Source
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AI summary
The invention addresses to a Method for improving the EMC robustness of Integrated Capacitive Sensor systems with a sensor Signal-Conditioner (SSC), having an external capacitor (a) representing the physical quantity to be sensed, connected with a capacitive integrating converter (b) to convert this capacity into a bit stream and an oscillator (g) providing sampling frequency for the capacitive integrating converter (b) and a counter (d) connected with the capacitive integrating converter (b), whereby a controller (e) is connected with a counter (d) which collects the bit stream and calculates the digital representative of the physical input which is than stored in an output register, comprising the steps of performing some conversions with different sampling frequencies from the oscillator (g) or a frequency divider by the capacitive integrating Signal-Converter (b); storing the results of the samplings and using the results in the following cycle to calculate for each sampling frequency a difference to the prior sampling of the same frequency; and calculating the digital representative of the input signal from the external sensing capacitor (a) as the reverse weighted average of the samplings of the different frequencies.