Pipelined ADC Dither Reconstruction for Faster Correlation Convergence
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Solution Overview
Problem
Correlation-based algorithms for removing dither signals from pipelined analog-to-digital converters (ADCs) suffer from long convergence times, leading to prolonged start-up and production test times due to the propagation of random dither signals through stages.
Innovation Solution
Reconstructing and subtracting estimates of dither signals before applying the correlation algorithm, significantly reducing the energy of undesired sequences and improving convergence time by using a combination of dither injection, correlation, and subtraction circuits within the ADC system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If correlation-based algorithms are used to remove dither signals from pipelined ADC output, then dither signals can be removed from the output, but the convergence time becomes very long
Solution Approach 1:
The patent applies preliminary action by reconstructing and subtracting estimates of dither signals from the ADC output before the correlation algorithm processes the signal. This pre-processing step removes the majority of dither energy in advance, allowing the correlation algorithm to converge much faster while still achieving complete dither removal. The subtraction operation is performed using reconstructed dither estimates that account for gain effects propagated through subsequent stages.
2Manufacturing precision
If dither signals are injected into stages for calibration purposes, then calibration can be performed, but the dither signals propagate through subsequent stages and influence the output
Solution Approach 1:
The patent applies the extraction principle by separating the dither signal component from the useful signal at the ADC output. The system reconstructs the propagated dither signals based on known injection patterns and stage gain characteristics, then subtracts these reconstructed dither components from the output. This extraction process removes the harmful propagated dither while preserving the useful calibration and conversion signals.
Solution Approach 2:
The patent uses an intermediary approach by introducing a dither reconstruction and subtraction mechanism between the ADC output and the correlation algorithm. This intermediary process accounts for the gain effects that dither signals experience as they propagate through subsequent stages, allowing accurate reconstruction and removal of the propagated dither without affecting the useful signal path.
3Ease of operation
If simple subtraction of injected dither is used to remove dither signals, then the process is straightforward, but it does not account for gain effects that dither experiences in subsequent stages
Solution Approach 1:
The patent applies parameter changes by modifying the dither removal process to account for gain variations in subsequent stages. Instead of simple subtraction, the system reconstructs the dither signals by applying the appropriate gain factors that represent the propagation effects through each stage. This allows accurate removal of propagated dither while maintaining operational feasibility through systematic parameter adjustment based on stage characteristics.
Data Source
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AI summary
A method and a corresponding device reduce the convergence time of a correlation algorithm that uses random signals injected into an analog-to-digital converter (ADC) as input to the algorithm. The method and device involve, at a processor of a pipelined ADC, injecting a random signal into each of a plurality of stages in the pipeline and obtaining digital values generated in response to the random signals. Noise components of residue signals in the plurality of stages are calculated as a function of the digital values and values of the random signals. The noise components correspond to the random signals.