High-Precision Temperature Inversion Algorithm for Correlative Microwave Radiometer

In order to achieve high precision from non-contact temperature measurement, the hardware structure of a broadband correlative microwave radiometer, calibration algorithm, and temperature inversion algorithm are innovatively designed in this paper. The correlative radiometer is much more sensitive t...

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Published in:	Sensors (Basel, Switzerland) Vol. 21; no. 16; p. 5336
Main Authors:	Liu, Jie, Zhang, Kai, Ma, Jingyan, Wu, Qiang, Sun, Zhenlin, Wang, Hao, Zhang, Youquan
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 07.08.2021 MDPI
Subjects:	Accuracy Algorithms Aluminum Antennas Bandwidths Calibration Circuits Coronaviruses correction algorithm correlative radiometer COVID-19 Design integral calibration Neural networks Noise PSO-LM-BP inversion algorithm R&D Radiation Radiometers Receivers & amplifiers Research & development
ISSN:	1424-8220, 1424-8220
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Abstract	In order to achieve high precision from non-contact temperature measurement, the hardware structure of a broadband correlative microwave radiometer, calibration algorithm, and temperature inversion algorithm are innovatively designed in this paper. The correlative radiometer is much more sensitive than a full power radiometer, but its accuracy is challenging to improve due to relatively large phase error. In this study, an error correction algorithm is designed, which reduces the phase error from 69.08° to 4.02°. Based on integral calibration on the microwave temperature measuring system with a known radiation source, the linear relationship between the output voltage and the brightness temperature of the object is obtained. Since the metal aluminum plate, antenna, and transmission line will have a non-linear influence on the receiver system, their temperature characteristics and the brightness temperature of the object are used as the inputs of the neural network to obtain a higher accuracy of inversion temperature. The temperature prediction mean square error of a back propagation (BP) neural network is 0.629 °C, and its maximum error is 3.351 °C. This paper innovatively proposed the high-precision PSO-LM-BP temperature inversion algorithm. According to the global search ability of the particle swarm optimization (PSO) algorithm, the initial weight of the network can be determined effectively, and the Levenberg–Marquardt (LM) algorithm makes use of the second derivative information, which has higher convergence accuracy and iteration efficiency. The mean square error of the PSO-LM-BP temperature inversion algorithm is 0.002 °C, and its maximum error is 0.209 °C.
AbstractList	In order to achieve high precision from non-contact temperature measurement, the hardware structure of a broadband correlative microwave radiometer, calibration algorithm, and temperature inversion algorithm are innovatively designed in this paper. The correlative radiometer is much more sensitive than a full power radiometer, but its accuracy is challenging to improve due to relatively large phase error. In this study, an error correction algorithm is designed, which reduces the phase error from 69.08° to 4.02°. Based on integral calibration on the microwave temperature measuring system with a known radiation source, the linear relationship between the output voltage and the brightness temperature of the object is obtained. Since the metal aluminum plate, antenna, and transmission line will have a non-linear influence on the receiver system, their temperature characteristics and the brightness temperature of the object are used as the inputs of the neural network to obtain a higher accuracy of inversion temperature. The temperature prediction mean square error of a back propagation (BP) neural network is 0.629 °C, and its maximum error is 3.351 °C. This paper innovatively proposed the high-precision PSO-LM-BP temperature inversion algorithm. According to the global search ability of the particle swarm optimization (PSO) algorithm, the initial weight of the network can be determined effectively, and the Levenberg–Marquardt (LM) algorithm makes use of the second derivative information, which has higher convergence accuracy and iteration efficiency. The mean square error of the PSO-LM-BP temperature inversion algorithm is 0.002 °C, and its maximum error is 0.209 °C. In order to achieve high precision from non-contact temperature measurement, the hardware structure of a broadband correlative microwave radiometer, calibration algorithm, and temperature inversion algorithm are innovatively designed in this paper. The correlative radiometer is much more sensitive than a full power radiometer, but its accuracy is challenging to improve due to relatively large phase error. In this study, an error correction algorithm is designed, which reduces the phase error from 69.08° to 4.02°. Based on integral calibration on the microwave temperature measuring system with a known radiation source, the linear relationship between the output voltage and the brightness temperature of the object is obtained. Since the metal aluminum plate, antenna, and transmission line will have a non-linear influence on the receiver system, their temperature characteristics and the brightness temperature of the object are used as the inputs of the neural network to obtain a higher accuracy of inversion temperature. The temperature prediction mean square error of a back propagation (BP) neural network is 0.629 °C, and its maximum error is 3.351 °C. This paper innovatively proposed the high-precision PSO-LM-BP temperature inversion algorithm. According to the global search ability of the particle swarm optimization (PSO) algorithm, the initial weight of the network can be determined effectively, and the Levenberg-Marquardt (LM) algorithm makes use of the second derivative information, which has higher convergence accuracy and iteration efficiency. The mean square error of the PSO-LM-BP temperature inversion algorithm is 0.002 °C, and its maximum error is 0.209 °C.In order to achieve high precision from non-contact temperature measurement, the hardware structure of a broadband correlative microwave radiometer, calibration algorithm, and temperature inversion algorithm are innovatively designed in this paper. The correlative radiometer is much more sensitive than a full power radiometer, but its accuracy is challenging to improve due to relatively large phase error. In this study, an error correction algorithm is designed, which reduces the phase error from 69.08° to 4.02°. Based on integral calibration on the microwave temperature measuring system with a known radiation source, the linear relationship between the output voltage and the brightness temperature of the object is obtained. Since the metal aluminum plate, antenna, and transmission line will have a non-linear influence on the receiver system, their temperature characteristics and the brightness temperature of the object are used as the inputs of the neural network to obtain a higher accuracy of inversion temperature. The temperature prediction mean square error of a back propagation (BP) neural network is 0.629 °C, and its maximum error is 3.351 °C. This paper innovatively proposed the high-precision PSO-LM-BP temperature inversion algorithm. According to the global search ability of the particle swarm optimization (PSO) algorithm, the initial weight of the network can be determined effectively, and the Levenberg-Marquardt (LM) algorithm makes use of the second derivative information, which has higher convergence accuracy and iteration efficiency. The mean square error of the PSO-LM-BP temperature inversion algorithm is 0.002 °C, and its maximum error is 0.209 °C.
Author	Liu, Jie Zhang, Youquan Ma, Jingyan Sun, Zhenlin Zhang, Kai Wu, Qiang Wang, Hao
AuthorAffiliation	Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China; KaiZhang@emails.bjut.edu.cn (K.Z.); majy0405@emails.bjut.edu.cn (J.M.); qiangwu@bjut.edu.cn (Q.W.); dmahz13@163.com (Z.S.); haowang@bjut.edu.cn (H.W.); S201961721@emails.bjut.edu.cn (Y.Z.)
AuthorAffiliation_xml	– name: Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China; KaiZhang@emails.bjut.edu.cn (K.Z.); majy0405@emails.bjut.edu.cn (J.M.); qiangwu@bjut.edu.cn (Q.W.); dmahz13@163.com (Z.S.); haowang@bjut.edu.cn (H.W.); S201961721@emails.bjut.edu.cn (Y.Z.)
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Copyright	2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2021 by the authors. 2021
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References	Zhu (ref_32) 2018; 29 Wu (ref_29) 2018; 7 Li (ref_33) 2018; 46 Ling (ref_11) 2019; 569 Zhang (ref_5) 2013; 11 Zhou (ref_20) 2013; 15 ref_13 ref_35 ref_12 ref_34 ref_10 ref_30 Wang (ref_8) 2017; 66 ref_18 Popovic (ref_17) 2014; 52 ref_15 He (ref_28) 2018; 24 Su (ref_1) 2016; 37 ref_25 ref_24 Ouyang (ref_31) 2020; 72 ref_23 ref_22 Lin (ref_37) 2008; 2 Dong (ref_21) 2018; 46 Momenroodaki (ref_14) 2018; 66 Gong (ref_36) 2012; 33 ref_3 ref_2 Yang (ref_19) 2001; 03 ref_27 ref_26 ref_9 Gilreath (ref_4) 2011; 46 Vaks (ref_16) 2002; 45 Gu (ref_38) 2020; 47 ref_7 ref_6
References_xml	– ident: ref_7 – volume: 29 start-page: 115602 year: 2018 ident: ref_32 article-title: Prediction of the tensile force applied on surface-hardened steel rods based on a CDIF and PSO-optimized neural network publication-title: Meas. Sci. Technol. doi: 10.1088/1361-6501/aadebf – ident: ref_9 doi: 10.3390/s18020677 – ident: ref_34 doi: 10.1109/GCAT47503.2019.8978348 – ident: ref_3 – volume: 52 start-page: 118 year: 2014 ident: ref_17 article-title: Toward wearable wireless thermometers for internal body temperature measurements publication-title: IEEE Commun. Mag. doi: 10.1109/MCOM.2014.6917412 – volume: 46 start-page: 185 year: 2018 ident: ref_21 article-title: A Variable Temperature Calibration Source for Microwave Radiometer Based on Polarized Line Gate publication-title: Acta Electron. Sin. – ident: ref_26 – ident: ref_24 doi: 10.3390/s21051619 – volume: 2 start-page: 68 year: 2008 ident: ref_37 article-title: Application of Infrared Thermometer to Observation of Blood Circulation of Head and Neck Tumor Postoperative Flap publication-title: Mod. Med. Instrum. Appl. – ident: ref_13 doi: 10.3390/s17092105 – volume: 45 start-page: 7 year: 2002 ident: ref_16 article-title: Thermal Near Field and the Possibilities of Its Use for In-Depth Temperature Diagnostics of Media publication-title: Radiophys. Quantum Electron. doi: 10.1023/A:1015284304784 – volume: 66 start-page: 2997 year: 2017 ident: ref_8 article-title: A Compact Analog Complex Cross-Correlator for Passive Millimeter-Wave Imager publication-title: IEEE Trans. Instrum. Meas. doi: 10.1109/TIM.2017.2714501 – ident: ref_18 – ident: ref_23 – volume: 7 start-page: 69 year: 2018 ident: ref_29 article-title: Nonlinear Function Fitting Based on BP Neural Network publication-title: Electron. World – ident: ref_30 doi: 10.3390/rs11232864 – volume: 66 start-page: 2535 year: 2018 ident: ref_14 article-title: Noninvasive Internal Body Temperature Tracking with Near-Field Microwave Radiometry publication-title: IEEE Trans. Microw. Theory Tech. doi: 10.1109/TMTT.2017.2776952 – volume: 33 start-page: 1469 year: 2012 ident: ref_36 article-title: Application and research of infrared body temperature monitoring in psychiatric inpatients publication-title: J. Jilin Med. Sci. – volume: 46 start-page: 105 year: 2018 ident: ref_33 article-title: Fast inversion algorithm of magnetic nanometer temperature based on Gaussian Newton method publication-title: J. Huazhong Univ. Sci. Technol. Nat. Sci. Ed. – ident: ref_15 doi: 10.1109/EuMC.2015.7345858 – ident: ref_6 – volume: 569 start-page: 7 year: 2019 ident: ref_11 article-title: Magnetic Nanometer Temperature Retrieval Algorithm Based on PSO publication-title: Electron. World – volume: 15 start-page: 75 year: 2013 ident: ref_20 article-title: Research on Cold Space Calibration and Geophysical Parameters Inversion of Haiyang-2 Scanning Microwave Radiometer publication-title: Eng. Sci. – ident: ref_25 – ident: ref_27 – ident: ref_2 – ident: ref_12 – volume: 72 start-page: 37 year: 2020 ident: ref_31 article-title: Prediction model of slope displacement of open-pit mine based on PSO optimized BP neural network publication-title: Nonferrous Met. – ident: ref_10 – ident: ref_35 doi: 10.1109/CAC.2017.8244159 – volume: 46 start-page: 2240 year: 2011 ident: ref_4 article-title: Design and Analysis of a W-Band SiGe Direct-Detection-Based Passive Imaging Receiver publication-title: IEEE J. Solid State Circ. doi: 10.1109/JSSC.2011.2162792 – ident: ref_22 – volume: 37 start-page: 110 year: 2016 ident: ref_1 article-title: Current situation and development of medical infrared body temperature measuring instrument publication-title: Med. Health Equip. – volume: 11 start-page: 747 year: 2013 ident: ref_5 article-title: Design of Microwave Radiometer with K-band Spectrum Analysis Technology publication-title: J. Terahertz Sci. Electron. Inf. – volume: 24 start-page: 151 year: 2018 ident: ref_28 article-title: A Comparison of the Retrieval of Atmospheric Temperature Profiles Using Observations of the 60 Ghz and 118.75 Ghz Absorption Lines publication-title: J. Trop. Meteorol. – volume: 03 start-page: 21 year: 2001 ident: ref_19 article-title: Study on the calibration equation of microwave radiometer publication-title: J. Chang. Inst. Opt. Fine Mech. – volume: 47 start-page: 10 year: 2020 ident: ref_38 article-title: Application and measurement points of infrared thermometer for human body temperature screening publication-title: Shanghai Metrol. Test.
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SubjectTerms	Accuracy Algorithms Aluminum Antennas Bandwidths Calibration Circuits Coronaviruses correction algorithm correlative radiometer COVID-19 Design integral calibration Neural networks Noise PSO-LM-BP inversion algorithm R&D Radiation Radiometers Receivers & amplifiers Research & development
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Title	High-Precision Temperature Inversion Algorithm for Correlative Microwave Radiometer
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