CMG--Particle Filtering for Time-Dependent Tomographic Analysis of the Solar Atmosphere

CMG--用于太阳大气瞬态层析成像分析的粒子过滤

• 批准号: 0620550
• 负责人: Yuguo Chen
• 金额: $ 76.04万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-09-01 至 2012-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0620550&HistoricalAwards=false
• 关键词: CMG; Particle; Filtering; Time; Dependent

Knowledge of the solar corona's 3D distribution of density and temperature is needed to model the propagation of solar disturbances from the Sun's surface out to the near-Earth environment, where effects on space-weather may be observed, experienced and, ultimately, mitigated. Current and next generation Sun observing spacecraft are providing us with unprecedented access to, and challenging amounts of, data regarding the three dimensional and time varying structure of the corona. Dynamic solar rotational tomography (SRT) is the approach that this collaboration of geoscientists and statisticians from the University of Illinois (Urbana-Champaign) will develop under a NSF interdisciplinary program, Collaborations in Mathematical Geosciences. Their approach seeks the development of Monte Carlo filtering algorithms optimized for non-linear and non-Gaussian probability distribution functions. To be capable of handling the large data sets associated with these tomographic problems requires progress in statistical estimation theory as well as the design of efficient computational algorithms. As well as benefiting the broader geophysical and statistical communities, graduate and undergraduate research and training to take between the two disciplinary areas provides an important educational incentive for the work. Tomographic particle filtering techniques, such as those proposed here, may have additional applications of interest to other fields in the geosciences, as well as in engineering and biomedical imaging.

需要了解日冕的三维密度和温度分布，以模拟太阳扰动从太阳表面向近地环境的传播，在近地环境中可以观察、体验并最终减轻对空间天气的影响。 当前和下一代太阳观测航天器为我们提供了前所未有的访问，并具有挑战性的数量，数据有关的三维和随时间变化的结构的日冕。动态太阳旋转层析成像（SRT）是伊利诺伊大学（厄巴纳-香槟）地球科学家和统计学家合作的方法，将在NSF跨学科计划数学地球科学合作下开发。 他们的方法寻求开发针对非线性和非高斯概率分布函数优化的蒙特卡罗滤波算法。 为了能够处理与这些断层问题相关的大数据集，需要在统计估计理论以及设计有效的计算算法的进展。除了使更广泛的地球物理和统计界受益外，研究生和本科生在这两个学科领域之间进行的研究和培训为这项工作提供了重要的教育激励。 层析粒子滤波技术，如这里提出的，可能有其他感兴趣的应用领域在地球科学，以及在工程和生物医学成像。