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基于最大似然估计的远紫外遥感反演电离层电子密度算法

冯桃君 于钱 张凯

冯桃君, 于钱, 张凯. 基于最大似然估计的远紫外遥感反演电离层电子密度算法[J]. 空间科学学报. doi: 10.11728/cjss2022.06.211115118
引用本文: 冯桃君, 于钱, 张凯. 基于最大似然估计的远紫外遥感反演电离层电子密度算法[J]. 空间科学学报. doi: 10.11728/cjss2022.06.211115118
FENG Taojun, YU Qian, ZHANG Kai. An Algorithm for Retrieving Ionospheric Electron Density from Far Ultraviolet Remote Sensing Based on Maximum Likelihood Estimation (in Chinese). Chinese Journal of Space Science, xxxx, x(x): x-xx doi: 10.11728/cjss2022.06.211115118
Citation: FENG Taojun, YU Qian, ZHANG Kai. An Algorithm for Retrieving Ionospheric Electron Density from Far Ultraviolet Remote Sensing Based on Maximum Likelihood Estimation (in Chinese). Chinese Journal of Space Science, xxxx, x(x): x-xx doi: 10.11728/cjss2022.06.211115118

基于最大似然估计的远紫外遥感反演电离层电子密度算法

doi: 10.11728/cjss2022.06.211115118
基金项目: 国家重点研发计划项目资助(2016 YFB0501300,2016 YFB0501304)
详细信息
    作者简介:

    冯桃君:E-mail:taozi_1227@126.com

  • 中图分类号: P356

An Algorithm for Retrieving Ionospheric Electron Density from Far Ultraviolet Remote Sensing Based on Maximum Likelihood Estimation

  • 摘要: 原子氧135.6 nm夜气辉主要由氧离子O+与电子的辐射复合反应生成,一些星载远紫外遥感观测任务证实135.6 nm夜气辉可用于反演电离层电子密度。针对远紫外临边遥感观测反演电离层电子密度,分析了135.6 nm夜气辉辐射强度与电子密度之间的非线型前向模型,基于离散反演理论设计了从夜间135.6 nm临边观测数据反演电子密度高度分布的反演算法,算法应用最大似然估计通过迭代求解电离层参数的最佳拟合值。通过仿真计算了TIMED卫星上全球紫外成像仪GUVI观测的反演结果,验证了本反演算法的可行性。对GUVI的实际观测数据进行反演,获得了电子密度高度分布。通过与GUVI数据的电离层参数对比分析得出,本文建立的反演模型使NmF2被高估,同时使hmF2被低估。对于不同的太阳活动强度,NmF2hmF2的系统误差分别在10%和5%以内,能较精确地获得电离层参数。精确获得电离层电子密度信息对于提高空间天气预报及电离层模型的修正具有重要意义。

     

  • 图  1  GUVI的扫描示意

    Figure  1.  Schematic of GUVI’s scan imaging

    图  2  10次反演结果及反演结果均值与电离层参数真值对应的电子密度高度分布(a)和辐射强度随视线切点高度的分布(b),10次反演叠加的噪声相同但迭代初值不同

    Figure  2.  (a) Electron density altitude profiles and (b) 135.6 nm radiances against tangent height of line of sight corresponding to the ten retrieved solutions, mean of solutions, true values of ionospheric parameters. Ten inversion runs have identical noise but differ in initial guess

    图  3  $ {\chi }^{2} $随迭代步数的变化(不同的曲线代表不同的反演,每次反演的迭代初值和噪声不同)

    Figure  3.  Variation of $ {\chi }^{2} $ with number of iterations (Different curve represents different inversion run. Each inversion run is different in both errors added and initial guess)

    图  4  100次反演的结果分布及百分比误差的概率密度函数 (PDF)统计直方图(每次反演的迭代初值和噪声不同)Probability Density Function

    Figure  4.  Distributions of three ionospheric parameters with respect to true values and the probability density Function (PDF) histograms of percentage differences for 100 inversion runs (Each inversion run is different in both errors added and initial guess)

    图  5  100次反演结果及反演结果均值与电离层参数真值对应的电子密度高度分布(a)和辐射强度随视线切点高度分布(b)(每次反演的迭代初值与噪声不同)

    Figure  5.  (a) Electron density altitude profiles and (b) 135.6 nm radiances against tangent height of line of sight corresponding to the one hundred retrieved solutions, mean of solutions, true values of ionospheric parameters (Each inversion run is different in both errors added and initial guess)

    图  6  三种仪器响应度情况下的NmF2 hmF2反演百分比误差对比

    Figure  6.  Percentage difference of NmF2 and hmF2 between their retrieved values and true values for three responsivity levels

    图  7  2002年7月20日(a)和2007年10月4日(b)GUVI 135.6 nm临边观测反演结果典型示例及与相同条件下的IRI2016模型的EDP、GUVI数据的EDP、基于IRI2016模型的仿真反演结果的对比

    Figure  7.  Comparison among the typical inversion results from GUVI 135.6 nm observations, IRI2016 EDP, GUVI EDP product and the inversion results from simulated data based on IRI2016 model on 20 July 2002 (a) and 4 October 2007 (b) under the same condition

    图  8  2002年7月20日的观测数据反演获得的电离层参数与GUVI数据电离层参数的比较

    Figure  8.  Comparison between retrieved ionospheric parameters from observations and GUVI data on 20 July 2002

    图  9  2007年10月4日的观测数据反演获得的电离层参数与GUVI数据电离层参数的比较

    Figure  9.  The comparison between retrieved ionospheric parameters from observations and GUVI data on 4 October 2007

    表  1  3种响应度情况的反演误差(%)数据对比

    Table  1.   Comparison of the retrieved errors (%) of three responsivity cases

    Ionospheric Parameter0.1 count·R–11 count·R–110 count·R–1
    maxminRMSmaxminRMSmaxminRMS
    NmF239.980.4812.0423.280.046.335.190.051.85
    hmF232.940.017.899.460.032.482.900.010.85
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出版历程
  • 收稿日期:  2021-11-15
  • 录用日期:  2021-04-15
  • 修回日期:  2022-05-05
  • 网络出版日期:  2022-11-09

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