Programmable DAC Linearity Correction for Self-Heating Errors
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Solution Overview
Problem
Digital-to-analog converters (DACs) suffer from systematic non-linearity errors due to components like SiCr thin-film resistors, which introduce power and heat dissipation-related non-linearities, affecting the accuracy of the analog output.
Innovation Solution
A systematic error correction network is implemented, which samples the digital input signal, generates a correction signal based on the non-linearity characteristic, and scales it by a reference variable to merge with the analog output, effectively counteracting the non-linearity errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If SiCr thin-film resistors are used in the DAC, then better linearity is achieved compared to polysilicon or diffusion resistors, but non-linearity errors are introduced due to power and heat dissipation
Solution Approach 1:
The patent measures the non-linearity error caused by TFR self-heating and uses this measured error information to generate a correction signal. The harmful non-linearity is converted into useful correction data that compensates for the error, transforming the problem into a solution.
Solution Approach 2:
The patent implements a feedback mechanism where the non-linearity error is measured, processed through a correction network, and the correction signal is fed back to the DAC output to compensate for the error in real-time, creating a closed-loop system that continuously corrects the non-linearity.
2Power
If larger operating voltages are applied to the DAC, then greater power dissipation occurs in TFR components, but this leads to increased non-linearity errors
Solution Approach 1:
The patent measures the voltage-dependent non-linearity error and uses this measurement to generate a correction signal that compensates for the error. The harmful effect of voltage-induced self-heating is converted into useful correction information.
Solution Approach 2:
The patent changes the operating parameters of the correction network to match the DAC operating voltage. The correction network is configured with different parameters for different voltage levels, allowing it to effectively correct non-linearity errors across various operating conditions.
3Measurement precision
If an error correction network is implemented to counter non-linearity errors, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent introduces a correction network as an intermediary component between the DAC and the output. This intermediary processes the DAC output signal, extracts non-linearity error information, and generates correction signals that are added back to compensate for the errors.
Solution Approach 2:
The patent creates a model or representation of the non-linearity error through measurement and processing. This copied error information is then used to generate the correction signal, allowing the system to compensate for errors without directly modifying the original DAC structure.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach significantly improves the accuracy of digital-to-analog conversion by destructively interfering with non-linearity errors, resulting in a more precise analog output.
Implementation Method 1
TFRs, generally, dissipate power and heat over themselves. The power and heat dissipation alter the resistance of TFR when the temperature coefficient of resistance is non-zero leading to the largest source of non-linearity error in a TFR.
Data Source
AI summary
The invention provides a systematic error correction network coupled to a converter. The converter may display a systematic non-linearity error, and the systematic error correction network shapes a correction transform function that acts like counter distortion function for the non-linearity error. The systematic error correction network then scales the correction transform function according to a reference variable, where the magnitude of non-linearity error is related to the reference variable. The scaled correction transform function is then applied to the converter path in order to generate a corrected analog output signal.