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Ionospheric data assimilation methods for geodetic applications

机译:大地测量应用中的电离层数据同化方法

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One of the major limiting factors in geodetic applications of the Global Positioning System (GPS) is lack of knowledge of the propagation delays imposed by the ionosphere. Single frequency, differential carrier phase measurements are limited to baselines with lengths less than the correlation size of the ionosphere (typically 10-20 km). Extending these measurements to longer distances requires accurate estimates of the slant total electron content (TEC) from a receiver to all observable GPS satellites. While dual frequency carrier phase measurements permit an ionosphere-free linear combination, accurate estimates of the double difference in integrated TEC between pairs of satellites and receivers provide an important constraint for accurate and rapid carrier phase ambiguity resolution. To achieve these accuracy requirements various approaches to the assimilation of groundbased GPS data from the CORS network and the mathematical representation of the ionospheric electron density field have been studied. The model presented uses a Kalman filter algorithm to assimilate data in various forms and an optional mapping function to alter the representation of the state vector in terms of a set of discrete radial empirical orthonormal functions (EOF's). Initial results from local networks show agreement with ambiguity-fixed double-differenced ionosphere delays of a few tenths of a TEC. The advantages of the various approaches and additional results will be discussed.
机译:全球定位系统(GPS)在大地测量应用中的主要限制因素之一是缺乏对电离层施加的传播延迟的了解。单频,差分载波相位测量仅限于基线,其长度小于电离层的相关大小(通常为10-20 km)。将这些测量扩展到更长的距离需要准确估计从接收器到所有可观测GPS卫星的倾斜总电子含量(TEC)。尽管双频载波相位测量允许无电离层线性组合,但对卫星和接收机对之间的集成TEC双重差的准确估计为准确,快速的载波相位模糊度解决提供了重要的限制。为了达到这些精度要求,研究了各种方法来同化来自CORS网络的地面GPS数据以及电离层电子密度场的数学表示。提出的模型使用卡尔曼滤波算法来吸收各种形式的数据,并使用可选的映射函数来根据一组离散的径向经验正交函数(EOF)来更改状态向量的表示。本地网络的初步结果表明,歧义固定的双差电离层延迟仅为TEC的十分之一。将讨论各种方法的优点和其他结果。

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