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利用二维核回归估计的大气密度模式修正

程国胜 李星祥 来鹏 周率

程国胜, 李星祥, 来鹏, 周率. 利用二维核回归估计的大气密度模式修正[J]. 空间科学学报, 2016, 36(3): 323-330. doi: 10.11728/cjss2016.03.323
引用本文: 程国胜, 李星祥, 来鹏, 周率. 利用二维核回归估计的大气密度模式修正[J]. 空间科学学报, 2016, 36(3): 323-330. doi: 10.11728/cjss2016.03.323
CHENG Guosheng, LI Xingxiang, LAI Peng, ZHOU Lü. Atmospheric Density Model Calibration Using 2-dimension Kernel Regression Method[J]. Journal of Space Science, 2016, 36(3): 323-330. doi: 10.11728/cjss2016.03.323
Citation: CHENG Guosheng, LI Xingxiang, LAI Peng, ZHOU Lü. Atmospheric Density Model Calibration Using 2-dimension Kernel Regression Method[J]. Journal of Space Science, 2016, 36(3): 323-330. doi: 10.11728/cjss2016.03.323

利用二维核回归估计的大气密度模式修正

doi: 10.11728/cjss2016.03.323
基金项目: 国家自然科学基金项目(11301279),国家公益性行业专项(气象)(GYHY201306063),江苏省高校自然科学基金(12KJB110016)和航天飞行动力学技术重点实验室开放基金(2012afdl029)共同资助
详细信息
    作者简介:

    程国胜,E-mail:chenggs@nuist.edu.cn

  • 中图分类号: P351

Atmospheric Density Model Calibration Using 2-dimension Kernel Regression Method

  • 摘要: 传统经验大气密度模式预测大气密度存在的较大误差会引起低轨卫星轨道预报误差,对卫星的再入轨、控制计划、碰撞规避及精密定轨造成不利影响.利用天宫一号卫星探测数据,针对大气NRLMSISE-00模式计算的误差特点,在地磁相对平静(Ap ≤ 30)的时间段内,对相近地方时和纬度的模式误差分布进行分析发现,相近地方时和纬度的模式误差分布基本相同.利用二维核回归估计方法,对与预测点相近地方时和纬度的样本误差进行加权,估计预测点处的模式误差,进而按距离预测日期天数的长短,采用加权修正法对模式预测结果进行修正,修正后大气模式误差的均方差(RMS)由14.09%降至4.05%.研究结果表明,该修正方法可以显著提高大气密度预报精度.

     

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出版历程
  • 收稿日期:  2015-05-07
  • 修回日期:  2015-12-02
  • 刊出日期:  2016-05-15

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