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GRACE时变信号恢复方法对比分析
引用本文:刘冰石,邹贤才.GRACE时变信号恢复方法对比分析[J].大地测量与地球动力学,2019,39(2):204-209.
作者姓名:刘冰石  邹贤才
作者单位:武汉大学测绘学院,武汉市珞喻路129号,430079;武汉大学测绘学院,武汉市珞喻路129号,430079;武汉大学地球空间环境与大地测量教育部重点实验室,武汉市珞喻路129号,430079
基金项目:国家自然科学基金;国家自然科学基金;国家重点基础研究发展计划(973计划);民用航天十三五技术预先研究项目
摘    要:针对利用GRACE重力数据反演地表质量变化过程中产生的时变信号削弱和泄露现象,分别采用尺度因子法和迭代恢复法对信号进行恢复,并选用CSR Mascon产品从时间序列变化和空间分布两个角度对两种恢复方法的效果进行对比分析。结果表明:1)尺度因子法虽实现上较为简单,但其计算结果完全依赖于所选的先验模型,当所选模型的可靠性较差时,会影响到GRACE反演结果的可靠性。2)迭代恢复法的恢复过程仅受GRACE原始观测值的约束,能较好地恢复研究区域的长期趋势信号和周期信号,但在部分区域可能存在信号过量恢复的现象。建议采用迭代恢复法进行GRACE时变信号恢复。

关 键 词:GRACE  信号泄露  信号恢复  尺度因子法  迭代恢复法

Comparison and Analysis of GRACE Time-Varying Signal Recovery Methods
LIU Bingshi,ZOU Xiancai.Comparison and Analysis of GRACE Time-Varying Signal Recovery Methods[J].Journal of Geodesy and Geodynamics,2019,39(2):204-209.
Authors:LIU Bingshi  ZOU Xiancai
Institution:(School of Geodesy and Geomatics,Wuhan University,129 Luoyu Road,Wuhan 430079,China;Key Laboratory of Geospace Environment and Geodesy,Ministry of Education,Wuhan University,129 Luoyu Road,Wuhan 430079,China)
Abstract:In view of the phenomenon of time-varying signal weakening and leakage in the process of GRACE data preprocessing, the scaling factors method and the forward modeling method are used to recover the lost signals. CSR Mascon products are adopted to compare the effects of the two recovery methods from the perspective of time series and spatial distribution. Results show: 1) The scaling factors method is relatively simple to implement, but the result of the scaling factors is completely dependent on the prior model, and when the reliability of the selected model is poor, the reliability of the GRACE inversion results are affected. 2) The restoration process of the forward modeling method is constrained by the original GRACE observations, and can restore the long-term trend and periodic signals, but there may be signal over-recovery in some areas. In restoring GRACE time-varying signals, we suggest using the forward modeling method.
Keywords:GRACE  signal leakage  signal recovery  scaling factors method  forward modeling method  
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