欧明, 甄卫民, 张时生, 赵庶凡, 於晓, 徐继生. 一种融合天地基多源数据的电离层反演方法[J]. 电波科学学报, 2016, 31(4): 713-719. doi: 10.13443/j.cjors.2015123001
      引用本文: 欧明, 甄卫民, 张时生, 赵庶凡, 於晓, 徐继生. 一种融合天地基多源数据的电离层反演方法[J]. 电波科学学报, 2016, 31(4): 713-719. doi: 10.13443/j.cjors.2015123001
      OU Ming, ZHEN Weimin, ZHANG Shisheng, ZHAO Shufan, YU Xiao, XU Jisheng. A combined ionosphere inversion method by data fusion of space and observations[J]. CHINESE JOURNAL OF RADIO SCIENCE, 2016, 31(4): 713-719. doi: 10.13443/j.cjors.2015123001
      Citation: OU Ming, ZHEN Weimin, ZHANG Shisheng, ZHAO Shufan, YU Xiao, XU Jisheng. A combined ionosphere inversion method by data fusion of space and observations[J]. CHINESE JOURNAL OF RADIO SCIENCE, 2016, 31(4): 713-719. doi: 10.13443/j.cjors.2015123001

      一种融合天地基多源数据的电离层反演方法

      A combined ionosphere inversion method by data fusion of space and observations

      • 摘要: 数据融合是观测数据稀疏条件下电离层精确反演的重要技术途径.文中提出了一种融合天地基多源数据的电离层反演方法.选择地基GNSS、低轨卫星(Low Earth Orbiting, LEO)掩星、卫星信标及垂测仪等手段为观测系统, 国际参考电离层(International Reference Ionosphere, IRI)为背景模型, 利用改进的克里格插值及乘法代数重构方法实现多源数据的有效融合.以中国区域为例, 观测系统模拟试验的结果表明:文中提出的方法能将各类观测资料有效地融合到背景模式中, 反演得到的总电子含量及电子密度误差相比经验模型均有显著降低; 在地基GNSS观测的基础上, 融入地基垂测与天基掩星可有效提升电子密度的反演精度.相关研究结果可为中国现有电离层观测系统的优化提供科学依据.

         

        Abstract: Data fusion is an important way which can be used for accurate inversion of ionosphere. In this paper, a combined ionosphere inversion method by multisource data fusion of space and ground-based observations is proposed. Measurements obtained by ground-based GNSS, low earth orbit(LEO) occultation, beacon and ionosonde are chosen as observation system to do simulation experiment. International Reference Ionosphere (IRI) is chosen to be the background model, while an improved Kriging interpolation method and multiplicative algebraic reconstruction technique (MART) are utilized for effective multisource data assimilation. Inversion results by observation system simulation experiment (OSSE) taking China for example show that it can obtain a good estimation of total electron content (TEC) and ionospheric electron density (IED) by ingesting the multisource data into the IRI model. Errors of the TEC and electron density are significantly reduced after data fusion. Ingestion of ground-based ionosonde and space-based occultation can greatly improves the accuracy of retrieved electron density of the observation system which only relies on the ground-based GNSS. This work will benefit the optimization of the ionospheric observation system in China.

         

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