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arXiv physics/9807026physics.geo-phphysics.ao-ph
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电离层电子含量GPS层析成像的PIM辅助卡尔曼滤波

A PIM-aided Kalman Filter for GPS Tomography of the Ionospheric Electron Content

Giulio Ruffini, Lidia Cucurull, Alex Flores, Antonio Rius

摘要:

我们开发了一个基于PIM的功能与卡尔曼滤波器的随机层析成像的形式主义,其中与四维电离层随机层析成像的反演问题进行了正则化。为了保持一致性,GPS数据用于以3DVAR方式动态地选择最佳PIM参数。我们演示了摄取GPS(IGS和GPS/MET)数据到一个参数化的电离层模型,用于选择一组参数,最大限度地减少了合适的成本功能。将得到的PIM拟合模型与直接3D体素断层扫描进行比较。我们证明了这种方法分析IGS和GPS/MET GPS数据的价值,并提出我们的结果在电离层电子密度的4D模型。

英文摘要:

We develop the formalism for a PIM-based functional for stochastic tomography with a Kalman filter, in which the inversion problem associated with four-dimensional ionospheric stochastic tomography is regularized. For consistency, GPS data is used to select dynamically the best PIM parameters, in a 3DVAR fashion. We demonstrate the ingestion of GPS (IGS and GPS/MET) data into a parameterized ionospheric model, used to select the set of parameters that minimize a suitable cost functional. The resulting PIM-fitted model is compared to direct 3D voxel tomography. We demonstrate the value of this method analyzing IGS and GPS/MET GPS data, and present our results in terms of a 4D model of the ionospheric electronic density.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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