ADC MSB-LSB Processing for Lower Quantization Error
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Solution Overview
Problem
Proximity sensors face significant errors due to ambient light interference and quantization errors from analog-to-digital conversion, particularly when using AC-powered fluorescent lights, leading to inaccurate distance sensing and prolonged operation times.
Innovation Solution
The method involves reducing least-significant-bit (LSB) operations by performing accumulation and merge operations on most-significant-bit (MSB) data, with LSB operations only performed in the final stage to generate the output signal, thereby minimizing quantization errors and shortening overall processing time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensing results are acquired and multiple LSB operations are performed for calibration, then the accuracy of proximity sensing is improved, but the quantization errors accumulate and the operating time is prolonged
Solution Approach 1:
The patent segments the sensing results into MSB and LSB components, processing MSB through accumulation operations and LSB through selective merge operations. This segmentation allows the system to reduce the number of LSB operations from multiple calibrations to just one or two, thereby reducing quantization errors and operating time while maintaining calibration accuracy.
Solution Approach 2:
The patent changes the processing parameter from performing LSB operations on every sensing result to performing LSB operations only on selected sensing results (one or two out of multiple). This parameter change in the operation frequency significantly reduces the accumulation of quantization errors and shortens the total operating time of the ADC.
2Measurement precision
If the sensing duration is shortened to reduce ambient light interference, then the luminance difference between measurements is reduced, but the ADC operating time becomes a larger proportion of the total sensing time
Solution Approach 1:
The patent extracts and processes only the necessary MSB components through accumulation operations, and performs LSB operations minimally (one or two times only). This extraction approach reduces the total processing time required, allowing the sensing duration to be optimized for luminance consistency without sacrificing overall sensing efficiency.
3Measurement precision
If multiple LSB operations are performed for each sensing result, then the calibration accuracy is improved, but the quantization errors from each operation accumulate in the final result
Solution Approach 1:
The patent segments the calibration process into MSB accumulation (performed multiple times) and LSB merge operations (performed only once or twice). This segmentation strategy maintains calibration accuracy through multiple MSB measurements while minimizing the accumulation of quantization errors by limiting LSB operations to a minimum necessary number.
Solution Approach 2:
The patent applies partial action by performing LSB operations only once or twice instead of multiple times for each sensing result. This partial approach is sufficient to achieve adequate calibration accuracy while avoiding the excessive accumulation of quantization errors that would result from performing LSB operations on every sensing result.
Data Source
AI summary
The present application relates to a method for operating sensing signals and the circuit thereof. An analog-to-digital converter first processes the input signal having the most significant bit (MSB DATA) data at least once. Afterwards, the analog-to-digital converter processes the input signal having the least significant bit (LSB) data and the MSB data and sums all the input signals. Thereby, the process steps of the analog-to-digital converter can be simplified and the processing time can be shortened.