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 due to electromagnetic compatibility (EMC) susceptibility, particularly the aliasing effect caused by interference frequencies equal or multiple to the sampling frequency.
Innovation Solution
The method involves a Sensor Signal-Conditioner with a capacitive integrating converter and an oscillator generating multiple sampling frequencies, where the results from different sampling frequencies are used to calculate a digital representative of the input signal as a reverse weighted average, reducing spectral noise sensitivity by minimizing the influence of noisy channels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a low-pass anti-aliasing filter is used to filter the input signal before digitalization, 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-based anti-aliasing filter with a software-based signal processing approach. Multiple measurements are taken at different sampling frequencies and processed algorithmically through weighted averaging, substituting the mechanical/electrical filter system with a computational system that achieves noise reduction without the associated 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 subsequent weighted averaging of the results
2Measurement precision
If multiple sampling frequencies are used to reduce aliasing effects, then measurement accuracy improves, but processing time and computational load increase
Solution Approach 1:
The patent performs preliminary measurements at multiple sampling frequencies and stores the results before final processing. By pre-acquiring all necessary measurement data and storing them for subsequent weighted averaging calculation, the system optimizes the timing of operations to reduce overall processing time while maintaining measurement accuracy
3Reliability
If a RC filter is combined with spread spectrum technology, then aliasing reduction is achieved for higher multiples of sampling frequency, but the solution is only partially effective and device complexity increases
Solution Approach 1:
The patent creates a universal solution that handles all aliasing cases (not just higher multiples) through a single multi-frequency sampling approach. The system performs measurements at multiple sampling frequencies and uses weighted averaging to universally address aliasing effects across the entire frequency spectrum, replacing the need for separate RC filters and spread spectrum modulation circuits
Solution Approach 2:
The patent replaces the combination of RC filter hardware and spread spectrum modulation with a purely computational approach. By using multiple sampling frequencies and processing the results through weighted averaging algorithms, the system achieves comprehensive aliasing reduction without the complexity of hardware filters and modulation circuits
Data Source
AI summary
A method is provided for improving the EMC robustness of Integrated Capacitive Sensor systems with a sensor Signal-Conditioner (SSC). The SSC is connected with a capacitive integrating converter to convert a received signal into a bit stream. An oscillator provides a plurality of sampling frequencies. A counter connected with the capacitive integrating converter collects the bit stream and calculates the digital representative of the physical input which is than stored in an output register. The method includes performing some conversions with different sampling frequencies from the oscillator or a frequency divider by the capacitive integrating Signal-Converter; 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 as the reverse weighted average of the samplings of the different frequencies.