基于实时阈值的CMOS有源像素传感器辐射致随机电报噪声自动检测

郑然; 赵瑞光; 刘超; 胡永才

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

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基于实时阈值的CMOS有源像素传感器辐射致随机电报噪声自动检测

辐射交叉学科研究 | 更新时间：2021-12-10

- 基于实时阈值的CMOS有源像素传感器辐射致随机电报噪声自动检测
- Auto-detection method for random telegraph signal noise detection for CMOS active pixel sensors based on real-time thresholds
- 辐射研究与辐射工艺学报 2018年36卷第2期
- 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：
  
  [ "郑然, 男, 1981年12月出生, 2013年于西北工业大学获得工学博士学位, 微电子与集成电路专业, 主要研究方向为集成电路设计及集成电路辐射效应研究, 副教授, E-mail:zhengran@nwpu.edu.cn", "ZHENG Ran (male) was born in December 1981, and received his doctoral degree (in integrated circuit design) from Northwestern Polytechnical University in 2013. Now he is an associate professor at Northwestern Polytechnical University, engaging in integrated circuit design and radiation effects on semiconductor devices. E-mail: zhengran@nwpu.edu.cn" ]
- 基金信息：
  
  国家自然科学基金青年基金项目(61306128);陕西省自然科学基金面上项目(2017JM6084)
- DOI：10.11889/j.1000-3436.2018.rrj.36.020701
  中图分类号：
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郑然, 赵瑞光, 刘超, 等. 基于实时阈值的CMOS有源像素传感器辐射致随机电报噪声自动检测[J]. 辐射研究与辐射工艺学报, 2018,36(2):020701-8.

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, 2018,36(2):020701-8.
郑然, 赵瑞光, 刘超, 等. 基于实时阈值的CMOS有源像素传感器辐射致随机电报噪声自动检测[J]. 辐射研究与辐射工艺学报, 2018,36(2):020701-8. DOI： 10.11889/j.1000-3436.2018.rrj.36.020701.

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, 2018,36(2):020701-8. 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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