The Characterization of Radiation Response for MAPS

Abstract

Abstract This paper studies the response of γ-ray ionizing radiation under the irradiation of single active Pixel Sensor in the irradiation chamber and the Calibration Chamber, Designs Radiation Experiments, and analyzes and discusses the characteristic values in different statistical regions of pixels in the bright and dark environment, the linear relationship and dispersion degree between the statistical eigenvalue and the dose rate under different statistical algorithms are studied. The experimental results show that in the dark environment, the background gray values of any region in the image are in the range of 10–30, and the eigenvalue have a good linear response. Under the bright environment, the global region of the image will be confused with the neighboring region because of the different background gray values of the color region in the Byer array, which will affect the characterization of the dose rate. In low dose rate, the signal of radiation response is too small, dark current and background dark noise produce interference signal, so the signal-to-noise ratio is too low, and 300 frames of image data are needed to achieve the detection accuracy. In high dose rate, the response signal is strong, and 2 consecutive frames of image data are needed to achieve the detection accuracy. The characteristic value of threshold pixel at low dose rate is good, and the characteristic value of threshold Pixel and total gray value at high dose rate are good, which meet the requirement of wide range detection. In the radiation field experiment, we can choose the corresponding algorithm to detect the dose rate according to the field environment. This study provides theoretical basis and data support for improving gamma-ray dose rate detection technology based on MAPS image and realizing radiation field dose rate characterization. In order to use the static environment to do the radiation experiment, we can design an algorithm to cut the edge of the frame image, and use the computer image processing technology to choose the area which is advantageous to the dose rate Characterization, To realize radiation Detection in dynamic environment.