Auto-detection method for random telegraph signal noise detection for CMOS active pixel sensors based on real-time thresholds

Ran ZHENG; Ruiguang ZHAO; Chao LIU; Yongcai HU

doi:10.11889/j.1000-3436.2018.rrj.36.020701

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Auto-detection method for random telegraph signal noise detection for CMOS active pixel sensors based on real-time thresholds

RADIATION INTERDISCIPLINARY RESEARCH | 更新时间：2021-12-10

- Auto-detection method for random telegraph signal noise detection for CMOS active pixel sensors based on real-time thresholds
- Journal of Radiation Research and Radiation Processing Vol. 36, Issue 2, (2018)
- 作者机构：
  
  1.西北工业大学计算机学院西安 710072
  2.斯特拉斯堡大学斯特拉斯堡 67037
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China(61306128);Natural Science Foundation of Shaanxi Province, China(2017JM6084)
- DOI：10.11889/j.1000-3436.2018.rrj.36.020701
  CLC：
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Ran ZHENG, Ruiguang ZHAO, Chao LIU, et al. Auto-detection method for random telegraph signal noise detection for CMOS active pixel sensors based on real-time thresholds. [J]. Journal of Radiation Research and Radiation Processing 36(2):020701-8(2018)
DOI：

Ran ZHENG, Ruiguang ZHAO, Chao LIU, et al. Auto-detection method for random telegraph signal noise detection for CMOS active pixel sensors based on real-time thresholds. [J]. Journal of Radiation Research and Radiation Processing 36(2):020701-8(2018) DOI： 10.11889/j.1000-3436.2018.rrj.36.020701.

摘要

研究了辐射环境下CMOS有源像素传感器产生的暗信号随机电报噪声（RTS）的特性，针对这一噪声提出一种实时自动检测算法，用以检测、重建暗信号RTS，并提取噪声关键参数。采用,60,Co γ射线进行的辐照实验测试结果表明，对于辐照后被观测像素发生的282次多级RTS转换，基于本文提出的实时阈值检测方法成功检测出了257次，检测效率达到91%，比采用暗信号幅值标准差为阈值的检测方法高出了16%。

Abstract

Based on the study of radiation-induced random telegraph signal (RTS) noise in CMOS active pixel sensors, we propose a real-time auto-detection method for RTS detection, reconstruction, and parameters extraction. ,60,Co γ-ray radiation experimental results reveal that, using the proposed method and employing the standard deviation of real-time Gaussian noise as the detection threshold, 257 out of 282 multilevel RTS transitions were successfully detected, thus, indicating a detection efficiency of 91%. This detection efficiency is 16% higher than that obtained in the detection method that uses signal standard deviation as the detection threshold.

关键词

随机电报噪声暗电流辐射粒子检测基于阈值检测

Keywords

Random telegraph signalDark signalRadiationCharged particle trackingThreshold based detection

references

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