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Volume 42 Issue 5
May  2016
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Journal of Beijing University of Aeronautics and Astronautics  > 2016  >  42(5): 920-926.
ZHANG Yiteng, LI Lei, ZHOU Bin, et al. Eliminating magnetic disturbance of satellites by method of magnetic field gradient tensor measurement[J]. Journal of Beijing University of Aeronautics and Astronautics, 2016, 42(5): 920-926. doi: 10.13700/j.bh.1001-5965.2015.0356(in Chinese)
Citation: ZHANG Yiteng, LI Lei, ZHOU Bin, et al. Eliminating magnetic disturbance of satellites by method of magnetic field gradient tensor measurement[J]. Journal of Beijing University of Aeronautics and Astronautics, 2016, 42(5): 920-926. doi: 10.13700/j.bh.1001-5965.2015.0356(in Chinese)
shu

Eliminating magnetic disturbance of satellites by method of magnetic field gradient tensor measurement

doi: 10.13700/j.bh.1001-5965.2015.0356
  • 1.

    State Key Laboratory of Space Weather, National Space Science Center, Chinese Academy of Sciences, Beijing 100190, China

  • 2. University of Chinese Academy of Sciences, Beijing 100094, China

  • Received Date: 01 Jun 2015
  • Publish Date: 20 May 2016
    Abstract
  • Based on the investigation of eliminating magnetic disturbance of satellites, in the way of magnetic field gradient tensor measurement method instead of traditional bi-sensor gradient method, simulation and physical test were carried out to eliminate the satellite magnetic disturbance due to its main body, and the relationship among the structural index of Euler deconvolution algorithm, the boom length and the background magnetic field inversion error was investigated. Simulation results show that according to 1m side length and 1 A·m2 remnant magnetism of cube satellite, magnetic field gradient tensor method has lower inversion accuracy of the background magnetic field under the short boom condition of 1-2 m, and higher inversion accuracy under the long boom condition of more than 3 m, which is about 0.5 nT under the condition of 4 m length boom. Under the long boom condition, the accuracy is approximately 3 times higher than that of the bi-sensor gradient method.

     

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