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A Comprehensive Model for Bolometer Element and Uncooled Array Design and Imaging Sensor Performance Prediction

机译:富豪计元素元素元素和阵列设计和成像传感器性能预测的综合模型

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This paper reports on a model developed to predict bolometer performance in its environment, where the environment consists of thermal, optical and electrical components. Two complementary methods were employed to predict performance. The first solves the heat balance equation for the bolometer in its circuit and its thermal environment with known values of heat capacitance, thermal conductance, absorptance, temperature coefficient of resistance and the user-defined bias current (either constant or pulsed). This iteration yields a bolometer temperature rise, and a corresponding change in resistance and voltage. This is the signal part of the equation. The second method is required to calculate the total bolometer noise. It uses equations derived from the literature to predict bolometer noise, response, NEP and NETD from first principles for the four types of noise generated in thermal detectors (thermal fluctuation noise, background fluctuation noise, johnson noise and 1/f noise). Thermal conductance and heat capacities are calculated using all the elements of the bolometer structure such as the silicon nitride structure, the VOx coating, and the nichrome electrical leads. Using a calculation of the full spectral irradiance on the bolometer from the scene and the dewar and a user-defined bolometer element spectral absorption, the model will accurately assess performance in any environment. The model also employs a 3-D noise model and provides synthetic images of PSF-blurred bar targets for NETD and MRTD predictions.
机译:本文报告了一种开发的模型,以预测其环境中的提高计性能,环境包括热,光学和电气部件。使用两种互补方法来预测性能。首先解决其电路中的辐射仪的热平衡方程及其热环境,具有已知的热电容值,导热,吸收率,电阻温度系数和用户定义的偏置电流(常数或脉冲)。这种迭代产生较高计的温度计,并且电阻和电压的相应变化。这是方程的信号部分。第二种方法是计算总鼓声器噪声的。它使用从文献中衍生的方程来预测热量检测器中产生的四种噪声的第一个原理(热波动噪声,背景波动噪声,Johnson噪声和1 / F噪声)的第一个原理来预测大计噪声,响应,NEP和NetD。使用诸如氮化硅结构,VOX涂层和镍铬物电引线的辐射计结构的所有元件计算热敏电导和热容。使用从场景和露天度计上的辐射计的全谱辐照度和用户定义的辐射计元素谱吸收,模型将准确地评估任何环境中的性能。该模型还采用了3-D噪声模型,并为NetD和MRTD预测提供了PSF模糊的律靶的合成图像。

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