A First Step for an INL Spectral-Based BIST: The Memory Optimization

Abstract

International audienceIntegral non-linearity (INL) is the main static parameter of analog-to-digital converter. This paper presents a comparison between different INL test techniques based on INL estimation from the spectrum of the converted signal. The most common technique is based on polynomial fitting of the INL curve. This technique is well suited to the estimation of a smooth INL curve without sharp transitions. The new method described in the paper is based on a Fourier series expansion of the INL curve. We demonstrate that this new technique allows a more efficient INL estimation. The comparison between the two techniques has been realized thanks to a metrics that considers the uncertainty of production test measurements. Finally, we propose a first step of the study of implementation feasibility of the INL estimation technique. This study focus only on the optimization of required memory

Adaptive LUT-based system for in situ ADC auto-correction

“…Finally, the main ADC parameters (such as INL) are extracted from the comparison between the two histograms. Other techniques have been developed [18][19][20][21][22][23] for INL estimation; they are based on an INL modeling using polynomial or Fourier series expansion. In [22][23], the authors showed that only the technique based on Fourier series expansion can give local information on the INL.…”

ADC Production Test Technique Using Low‐Resolution Arbitrary Waveform Generator

“…The critical static parameter is the integral nonlinearity (INL). The above set of parameters can be derived [11,14,15] or computed [1] from the harmonic values and/or the noise value. A very common way to evaluate these harmonic and noise values of a given converter relies on spectral analysis, that is, to apply a singletone sine wave to the converter input and compute the FFT on the output signal.…”

Simple Evaluation of the Nonlinearity Signature of an ADC Using a Spectral Approach

“…For these kinds of converters, the use of methods based on spectral processing can be satisfactory acquiring only some tens of thousands of samples independently of the ADC resolution [3][4][5][6]. Although this estimate leads to a partial description of the static behavior of the ADC and, for example, it is not a reliable method to calibrate the nonlinearity, such description may be enough to show a malfunctioning and it may be very useful to set a test protocol [7][8][9].…”