Geomagnetic field modeling from on-board LEO attitude-control magnetometer

拟议的研究旨在将地磁场中的核心分量从用于卫星姿态控制的磁强计测量中分离出来并建立模型，以填补传统卫星磁力飞行任务之间存在的时间覆盖空白，并增进我们对地球磁特性及其起源的理解。卫星磁场数据将提供有关地磁场模型(GFM)的关键见解，该模型主要基于地面观测站数据，覆盖范围较差且有偏差。GFM也依赖于传统的卫星磁数据，但各次飞行任务之间存在显著的时间差距。幸运的是，近地轨道卫星携带有星载姿态控制磁强计(TAMS)。最近确定，KOMPSAT-1卫星仅对进行了3天的测量，提供了自1958年以来约30年间磁场行为的重要知识，当时无法进行常规的磁力飞行任务。因此，建议研究利用KOMPSAT-1和KOMPSAT-2卫星全部测量数据的综合数据和其他磁测卫星的常规磁力数据。程序和最先进的数据处理技术将包括坐标变换、谱相关滤波、象限交换、球谐系数计算和地下建模。作为研究成果，总场图和球谐核心场模型可用于更新全球模型。地下模拟的结果还将提高我们对地壳碳氢化合物和矿产资源分布以及地质灾害的了解。

The proposed research aims to separate and model the core components in the geomagnetic field from the magnetometer measurements that have been used in attitude control of satellites, in order to fill temporal coverage gaps that exist between conventional satellite magnetic missions and to improve our understanding of the Earth's magnetic properties and its origin. The satellite magnetic data will provide key insights on the geomagnetic field model (GFM), which is based largely on ground observatory data that has poor and biased coverage. The GFM also relies on the conventional satellite magnetic data, but significant temporal gaps exist between missions. Fortunately, low-Earth orbit satellites carry on-board attitude control magnetometers (TAMs). It was recently determined that only 3 days of TAM measurements from the KOMPSAT-1 satellite were found to provide important knowledge on the behaviour of the magnetic field for the roughly 30 years since 1958, when conventional magnetic missions were unavailable. Accordingly, a study is proposed to investigate the use of comprehensive TAM data from the entire measurement data of KOMPSAT-1 and -2 satellites and conventional magnetic data from other magnetic survey satellites. Procedures and state-of-the-art data processing techniques will include coordinate transformation, spectral correlation filtering, quadrant-swapping, spherical harmonic coefficient calculation, and subsurface modeling. As research outcomes, the total field map and the spherical harmonic core field model can be used to update global models. The results of the subsurface modeling will also improve our understanding of crustal distribution of hydrocarbons and mineral resources, as well as geological hazards.