Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2511.11917 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866913057010089984 |
|---|---|
| author | Schey, Thorben Karoonlatifi, Khaled Weyrich, Michael Morozov, Andrey |
| author_facet | Schey, Thorben Karoonlatifi, Khaled Weyrich, Michael Morozov, Andrey |
| contents | This paper builds on our Uncertainty-Guided Live Measurement Sequencing (UGLMS) method. UGLMS is a closed-loop test strategy that adaptively selects SAR ADC code edges based on model uncertainty and refines a behavioral mismatch model in real time via an Extended Kalman Filter (EKF), eliminating full-range sweeps and offline post-processing. We introduce an enhanced UGLMS that delivers significantly faster test runtimes while maintaining estimation accuracy. First, a rank-1 EKF update replaces costly matrix inversions with efficient vector operations, and a measurement-aligned covariance-inflation strategy accelerates convergence under unexpected innovations. Second, we extend the static mismatch model with a low-order carrier polynomial to capture systematic nonlinearities beyond pure capacitor mismatch. Third, a trace-based termination adapts test length to convergence, preventing premature stops and redundant iterations. Simulations show the enhanced UGLMS reconstructs full Integral- and Differential-Non-Linearity (INL/DNL) in just 36 ms for 16-bit and under 70 ms for 18-bit ADCs (120 ms with the polynomial extension). Combining the faster convergence from covariance inflation with reduced per-iteration runtime from the rank-1 EKF update, the method reaches equal accuracy 8x faster for 16-bit ADCs. These improvements enable real-time, production-ready SAR ADC linearity testing. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_11917 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Advanced Strategies for Uncertainty-Guided Live Measurement Sequencing in Fast, Robust SAR ADC Linearity Testing Schey, Thorben Karoonlatifi, Khaled Weyrich, Michael Morozov, Andrey Hardware Architecture This paper builds on our Uncertainty-Guided Live Measurement Sequencing (UGLMS) method. UGLMS is a closed-loop test strategy that adaptively selects SAR ADC code edges based on model uncertainty and refines a behavioral mismatch model in real time via an Extended Kalman Filter (EKF), eliminating full-range sweeps and offline post-processing. We introduce an enhanced UGLMS that delivers significantly faster test runtimes while maintaining estimation accuracy. First, a rank-1 EKF update replaces costly matrix inversions with efficient vector operations, and a measurement-aligned covariance-inflation strategy accelerates convergence under unexpected innovations. Second, we extend the static mismatch model with a low-order carrier polynomial to capture systematic nonlinearities beyond pure capacitor mismatch. Third, a trace-based termination adapts test length to convergence, preventing premature stops and redundant iterations. Simulations show the enhanced UGLMS reconstructs full Integral- and Differential-Non-Linearity (INL/DNL) in just 36 ms for 16-bit and under 70 ms for 18-bit ADCs (120 ms with the polynomial extension). Combining the faster convergence from covariance inflation with reduced per-iteration runtime from the rank-1 EKF update, the method reaches equal accuracy 8x faster for 16-bit ADCs. These improvements enable real-time, production-ready SAR ADC linearity testing. |
| title | Advanced Strategies for Uncertainty-Guided Live Measurement Sequencing in Fast, Robust SAR ADC Linearity Testing |
| topic | Hardware Architecture |
| url | https://arxiv.org/abs/2511.11917 |