Volume 43 Issue 1
Jan.  2023
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ZHANG Haicheng, QUAN Ronghui, ZHANG Chengyue. Inversion Analysis of GEO Plasma Environmental Parameters Based on BP Neural Network (in Chinese). Chinese Journal of Space Science, 2023, 43(1): 78-86 doi: 10.11728/cjss2023.01.220311028
Citation: ZHANG Haicheng, QUAN Ronghui, ZHANG Chengyue. Inversion Analysis of GEO Plasma Environmental Parameters Based on BP Neural Network (in Chinese). Chinese Journal of Space Science, 2023, 43(1): 78-86 doi: 10.11728/cjss2023.01.220311028
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Inversion Analysis of GEO Plasma Environmental Parameters Based on BP Neural Network

doi: 10.11728/cjss2023.01.220311028 cstr: 32142.14.cjss2023.01.220311028

  • School of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 211106

  • Received Date: 2022-03-11
  • Rev Recd Date: 2022-10-11
    • Available Online: 2023-02-09
    Abstract
  • The surface charging effect induced by the space plasma environment may interfere with the operation of spacecraft, which can lead to the failure of solar cells and other components. It is shown that the high-energy plasma environmental parameters can also be obtained by taking the electrical potential curve of the dielectric surface in the GEO environment as input under the assumption of double Maxwell distribution. Firstly, the influence of GEO plasma environment parameters on the surface charging potential curve is analyzed, indicating that the high energy peak plays a decisive role in the charging process. Then, BP neural network is established by MATLAB, and the network training data is obtained according to multiple groups of charging curves calculated by COMSOL. Finally, the average relative error of plasma density and temperature inversion is 0.42% and 0.03%, and respectively, and the overall relative error is within 0.1%~5.6%. Results showed that it was feasible to use a neural network to invert the plasma environment, and the method can be used as a reference for comparison of the detection results of the space plasma environment. The inversion results can be used as the input conditions for surface potential calculation of non-detection points of spacecraft.

     

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