In this paper, the key technology of interferometric microwave thermometer is studied, the research can be applied to the temperature measurement of human body and subcutaneous tissue. This paper proposes a hardware architecture of interferometric microwave thermometer with 2 GHz bandwidth, in which the phase shifter is used to correct phase error and the quadrature demodulator is used to realize autocorrelation detection function. The results show that when input power is 7 dBm, the detection sensitivity can reach 176.54 mV/dBm and the temperature resolution of the microwave radiometer can reach 0.4 K. Correction algorithm is designed to improve the accuracy of temperature measurement. After correction, the phase error is reduced from 40° to 1.4° and when temperature changes 0.1 °C, the voltage value changes obviously. Step-by-step calibration and overall calibration are used to calibrate the device. Inversion algorithm can determine the relationship between physical temperature and output voltage. The mean square error of water temperature inversion by multiple linear regression algorithm is 0.607 and that of BP neural network algorithm is 0.334. The inversion accuracy can be improved by reducing the temperature range. Our work provides a promising realization of accurate, rapid and non-contact detection device of human body temperature.

中文翻译：

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新型用于人体温度测量的干涉式微波辐射计的设计与实现

本文研究了干涉式微波温度计的关键技术，该研究可应用于人体和皮下组织的温度测量。提出了一种带宽为2 GHz的干涉式微波温度计的硬件架构，其中使用移相器校正相位误差，使用正交解调器实现自相关检测功能。结果表明，在输入功率为7 dBm时，检测灵敏度可达176.54 mV / dBm，微波辐射计的温度分辨率可达0.4K。设计了校正算法，提高了温度测量的准确性。校正后，相位误差从40°减小到1.4°，并且当温度变化0.1°C时，电压值会明显变化。使用逐步校准和整体校准来校准设备。反演算法可以确定物理温度与输出电压之间的关系。多元线性回归算法的水温反演均方误差为0.607，BP神经网络算法的均方误差为0.334。通过减小温度范围可以提高反演精度。我们的工作为准确，快速和非接触式的人体温度检测设备提供了一个有希望的实现。通过减小温度范围可以提高反演精度。我们的工作为准确，快速和非接触式的人体温度检测设备提供了一个有希望的实现。通过减小温度范围可以提高反演精度。我们的工作为准确，快速和非接触式的人体温度检测设备提供了一个有希望的实现。