Oscillation-based testing (OBT) and Oscillation-based built-in self-testing (OBIST) circuits enable detection of catastrophic faults in analogue and RF circuits, but both are sensitive to process, voltage and temperature (PVT) variation. This paper investigates 15 OBT and OBIST feature extraction strategies, and four approaches to threshold selection, by calculating figure-of-merit (FOM) across PVT variation. This is done using a 2.4 GHz LNA in $0.35 \mu \mathrm{m}$ CMOS as DUT. Of the 15 feature extraction approaches, the OBT approaches are found more effective, with some benefit gained from switched-state detection. Of the four approaches to threshold selection (nominal-ranged static thresholds, extreme-range static thresholds, temperature dynamic thresholds, and simple noise-filtered tone detection), dynamic thresholds resulted in the highest average FoM of 0.919, with the best FoM of 0.952, with a corresponding probability of test escape $P\left(T_E\right)$ and yield loss $P\left(Y_L\right)$ of $5 \cdot 10^{-2}$ and $1.89 \cdot 10^{-2}$ respectively but requires accurate temperature measurement. Extreme static threshold selection resulted in a comparable average FoM of 0.912, but with less susceptibility to process variation and without the need for temperature measurement. Binary detection of a noise-filtered oscillating tone is found the least complex approach, with an average FoM of 0.891.

中文翻译：

---

PVT 变化和阈值选择对 RFCMOS 放大器中 OBT 和 OBIST 故障检测的影响

基于振荡的测试 (OBT) 和基于振荡的内置自测试 (OBIST) 电路能够检测模拟和射频电路中的灾难性故障，但两者都对工艺、电压和温度 (PVT) 变化敏感。本文通过计算 PVT 变化的品质因数 (FOM)，研究了 15 种 OBT 和 OBIST 特征提取策略，以及四种阈值选择方法。这是使用 2.4 GHz LNA 在 $0.35 \mu \mathrm{m}$CMOS 作为 DUT。在 15 种特征提取方法中，OBT 方法被发现更有效，并且从开关状态检测中获得了一些好处。在四种阈值选择方法（标称范围静态阈值、极端范围静态阈值、温度动态阈值和简单的噪声过滤音调检测）中，动态阈值导致最高平均 FoM 为 0.919，最佳 FoM 为 0.952 ，具有相应的测试逃逸概率 $P\左（T_E\右）$和产量损失 $P\左(Y_L\右)$的 $5 \cdot 10^{-2}$和 $1.89 \cdot 10^{-2}$分别但需要精确的温度测量。极端静态阈值选择导致可比较的平均 FoM 为 0.912，但对过程变化的敏感性较低并且不需要温度测量。噪声过滤振荡音的二进制检测是最简单的方法，平均 FoM 为 0.891。