Abstract Ionospheric disturbance (ID) detected using GPS based Total Electron Content (TEC) measurements are widely used to study the morphology and dynamics of the ionosphere, and its impact on radio communication and satellite based navigation. The IDs normally derived as rate of change of TEC (ROT) between consecutive ionospheric pierce points at uniform time interval implicitly results in non-uniform spatial sampling along the GPS satellite tracks. The non-uniform spatial sampling introduces aliasing in ROT. These aliasing corrupt amplitude and Signal-to-Noise Ratio (SNR) of the detected IDs. In this study, we propose a Spatio-Periodic Leveling Algorithm (SPLA) to remove such aliasing. Efficiency of the proposed algorithm was tested by simulating the IDs along a satellite track and validated with GPS observations carried out during 2015 St. Patrick's day geomagnetic storm. Spatiotemporal, and SNR analyses of simulated and observed IDs reveal that the SPLA is (i) efficient in removing the aliases, (ii) increases the SNR on an average of 99.5% compared to ROT, (iii) removes the need of applying elevation cut-off, and (iv) expands the area of coverage up to 65%.

中文翻译：

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使用 GPS 检测电离层扰动而不会出现由非均匀空间采样引起的混叠：算法、验证和说明

摘要 使用基于 GPS 的总电子含量 (TEC) 测量检测到的电离层扰动 (ID) 被广泛用于研究电离层的形态和动力学，及其对无线电通信和卫星导航的影响。ID 通常作为在均匀时间间隔内连续电离层穿透点之间的 TEC (ROT) 变化率得出的结果隐含地导致沿 GPS 卫星轨迹的非均匀空间采样。非均匀空间采样在 ROT 中引入了混叠。这些混叠破坏了检测到的 ID 的幅度和信噪比 (SNR)。在这项研究中，我们提出了一种空间周期调平算法 (SPLA) 来消除这种混叠。通过模拟沿卫星轨道的 ID 来测试所提出算法的效率，并通过 2015 年圣彼得堡期间进行的 GPS 观测进行验证。帕特里克节地磁风暴。模拟和观察到的 ID 的时空和 SNR 分析表明，SPLA (i) 有效去除别名，(ii) 与 ROT 相比，SNR 平均提高 99.5%，(iii) 消除了应用高程切割的需要-off，以及 (iv) 将覆盖范围扩大到 65%。