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A compensation model of aeromagnetic gradient tensor data based on low-temperature superconducting |
HOU Rui-Dong1,2,3( ), GUO Zi-Qi2,3( ), QIAO Yan-Chao2,3, LIU Jian-Ying2,3 |
1. College of Resources and Environment University of Chinese Academy of Sciences, Beijing 100049, China 2. Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China 3. State Key Laboratory of Remote Sensing Science, Beijing 100101, China |
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Abstract In the compensation of the aeromagnetic gradient tensor data based on superconducting, the simulation results of the compensation model often differ from the compensation results of the survey data. To establish a model that is valid for measured data, this study analyzed the sources of errors, proposed a comprehensive compensation model by combining magnetic interference, installation errors, and the degree of unbalance, and determined the method to solve the model. Moreover, this study compensated the measured data using the comprehensive compensation model proposed and verified the compensation effects. The experimental results show that the comprehensive compensation model is applicable to the compensation of measured data since it can not only effectively reduce the influence of external interference but also can improve the quality of magnetic gradient tensor data and achieve significant compensation effects.
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Received: 14 October 2021
Published: 24 February 2023
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Corresponding Authors:
GUO Zi-Qi
E-mail: houruidong19@mails.ucas.ac.cn;guozq@radi.ac.cn
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Installation structure(a) and coordinate system of hexagonal prism(b) (perpendicular to y axis)
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Effective part of closed line
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Comparison of compensation results of closed line
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| G1 | G2 | G3 | G4 | G5 | G6 | mean | 补偿前σ | Line1 | 0.5761 | 0.8201 | 1.1711 | 0.7814 | 0.9162 | 0.7253 | 0.8317 | Line2 | 0.7229 | 0.4262 | 0.6916 | 0.8545 | 0.6699 | 0.8314 | 0.6994 | Line3 | 0.7033 | 0.5446 | 0.6784 | 0.7712 | 1.3354 | 0.7168 | 0.7916 | Line4 | 0.4413 | 0.7411 | 0.8144 | 0.7838 | 0.6123 | 0.7393 | 0.6887 | 补偿后σ | Line1 | 0.0031 | 0.0029 | 0.005 | 0.0034 | 0.0115 | 0.0043 | 0.0050 | Line2 | 0.0013 | 0.0005 | 0.0015 | 0.002 | 0.0022 | 0.002 | 0.0016 | Line3 | 0.0014 | 0.0015 | 0.0021 | 0.002 | 0.0026 | 0.0026 | 0.0020 | Line4 | 0.0014 | 0.001 | 0.0015 | 0.0026 | 0.0036 | 0.0023 | 0.0021 | 改善比IR | Line1 | 185.84 | 282.79 | 234.22 | 229.82 | 79.67 | 168.67 | 373.0675 | Line2 | 556.08 | 852.40 | 461.07 | 427.25 | 304.50 | 415.70 | Line3 | 502.36 | 363.07 | 323.05 | 385.60 | 513.62 | 275.69 | Line4 | 315.21 | 741.10 | 542.93 | 301.46 | 170.08 | 321.43 |
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