ADC Polling Signal Processing for Low-Latency Noise Rejection
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Solution Overview
Problem
Existing signal processing methods for analog-to-digital converters, such as average, median, and exponential weighted moving average (EWMA), suffer from increased noise influence and lengthy latency, particularly in embedded control systems requiring instant responses.
Innovation Solution
A method using polling to determine a delegate candidate interval with the most sampling points and calculating a delegate value based on the number and values of sampling points within that interval, excluding noise-influenced points to reduce latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If average method is used to calculate output value, then noise influence increases, but calculation is simple
Solution Approach 1:
The patent segments the sampling space into multiple candidate intervals and divides sampling points into groups based on their assigned candidate intervals. This segmentation allows the system to process groups of sampling points separately, reducing the influence of noise on the overall average calculation while maintaining computational efficiency through the structured division of data.
2Measurement precision
If median method is used to output median value, then noise resistance improves, but latency increases due to sorting
Solution Approach 1:
The patent performs preliminary action by pre-assigning each sampling point to a candidate interval before the actual signal processing. This pre-grouping eliminates the need for sorting operations during real-time processing, thereby maintaining noise resistance through selective averaging while significantly reducing processing latency.
3Speed
If EWMA method is used to calculate weighted average, then responsiveness to signal changes improves, but latency increases during weighting calculation
Solution Approach 1:
The patent applies partial action by calculating averages only for sampling points within the same candidate interval rather than performing full EWMA weighting calculations across all sampling points. This selective processing maintains responsiveness to signal changes within each interval while reducing overall computational time and latency.
4Device complexity
If all sampling points are processed equally, then simplicity is maintained, but noise influence increases
Solution Approach 1:
The patent applies local quality by treating sampling points differently based on their assigned candidate intervals. Instead of uniform processing, the system calculates averages locally within each interval, allowing sampling points in the same interval to be processed together while excluding points from other intervals. This localized processing improves noise resistance by focusing on relevant data groups while maintaining relative simplicity in the overall approach.
Data Source
AI summary
A method of signal processing for handling a digital signal outputted by an analog-to-digital converter includes determining a candidate interval corresponding to each of multiple sampling points in a sampling space of the digital signal, wherein the candidate interval is one of multiple candidate intervals, calculating numbers of sampling points corresponding to each one of the multiple candidate intervals to determine a delegate candidate interval, and calculating a delegate value of the sampling space according to a number of sampling points corresponding to the delegate candidate interval and values of the sampling points corresponding to the delegate candidate interval.