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Effect of flicker noise on SEIR for accurate ADC linearity testing

机译:闪烁噪声对SEIR的影响,可进行精确的ADC线性测试

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This paper investigates the effectiveness of the stimulus error identification and removal (SEIR) algorithm for linearity testing of high precision Analog-to-Digital Converters (ADCs) in the presence of flicker noise. The SEIR algorithm has been demonstrated to be highly effective in estimating the integral nonlinearity (INL) of high precision ADCs tested with low linearity input sources. Since flicker noise has the tendency to accumulate to large values over time, simulations reveal that this accumulation will introduce errors in linearity estimation when using SEIR. Previously, Center Symmetric Interleaving (CSI) pattern was used for generating input ramps. Both simulations and measurement results have proven its effectiveness in suppressing environmental nonstationarity which is in polynomial form. Simulations of CSI combined with SEIR show that CSI is not effective in eliminating the error in linearity estimation introduced by flicker noise with an rms value of 0.5 LSB, since flicker noise is not in polynomial form. In comparison, simulations with an interleaving pattern, which is easier to implement in practice, show that it is more effective in reducing the estimation error caused by flicker noise. By using 128 triangle waves with 0.15 LSB rms flicker noise, the estimation error can be reduced to within 0.5 LSB.
机译:本文研究了激励误差识别和消除(SEIR)算法在存在闪烁噪声的情况下对高精度模数转换器(ADC)进行线性测试的有效性。 SEIR算法已被证明在评估使用低线性输入源测试的高精度ADC的积分非线性(INL)方面非常有效。由于闪烁噪声会随着时间的流逝而累积到较大的值,因此仿真表明,使用SEIR时,这种累积会在线性估计中引入误差。以前,中心对称交织(CSI)模式用于生成输入斜坡。仿真和测量结果均证明了其在抑制多项式形式的环境非平稳性方面的有效性。 CSI与SEIR结合的仿真表明,由于闪烁噪声不是多项式形式,因此CSI不能有效消除均方根值为0.5 LSB的闪烁噪声所引起的线性估计误差。相比之下,在实际中更易于实现的具有交织模式的仿真显示,它在减少由闪烁噪声引起的估计误差方面更为有效。通过使用具有0.15 LSB rms闪烁噪声的128个三角波,可以将估计误差减小到0.5 LSB之内。

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