精密單點定位(Precise Point Positioning, PPP)結合了單點定位以及相對定位的優勢，能使用單一接收機得到高精度的定位成果，然而其需要花上許多時間收斂定位誤差，導致在即時定位及導航等方面的應用受限。定位誤差的主因之一為電離層的電漿擾動，若是能準確地預測電離層的狀態以及影響量預期能加速PPP的誤差收斂，對導航以及通訊等民生系統的運作有很大的幫助。目前多採用以電離層模式預估電離層誤差量予以扣除的形式，然而電離層模式會受到邊界條件以及設定參數的影響，預估的精確度有限，因此本研究嘗試導入台灣上空人造衛星觀測的電離層資料(Global Navigation Satellite System Total Electron Content, GNSSTEC)，並透過資料同化技術中的系集卡爾曼濾波法(Ensemble Kalman Filter, EnKF)和局地系集變換卡爾曼濾波法(Local Ensemble Transform Kalman Filter, LETKF)進行電離層模式—國際參考電離層(International Reference Ionosphere, IRI)的同化修正，建構台灣上空區域性高解析度二維電離層狀態EnKF/IRI以及LETKF/IRI同化模式，並討論有無同化電離層之模式、不同尺度電離層模式、不同時刻、季節與太陽活動性等條件下PPP水平定位誤差與收斂速度之影響與可能原因。
結果發現，EnKF/IRI和LETKF/IRI同化模式能在台灣上空及其周圍建構出完整且近似於觀測資料分布之電離層結構，但受制於GNSSTEC觀測資料在空間分布上不均勻，於資料涵蓋量較少的區域同化後結構不完整。而由於IRI模式不具備預報能力，長期同化會導致電離層結構不連續等結構不完整狀況，因此並不適合做為資料同化模式背景。透過使用中央氣象局地球物理資料系統提供的中央氣象局站以及歸仁之GNSS測站進行動態GPS PPP定位測試後，使用EnKF/IRI與LETKF/IRI模式比起未經同化的IRI模式來說皆能縮短40%以上的收斂時間。於背景電離層濃度較高的平靜日，區域性EnKF/IRI與LETKF/IRI模式在PPP定位誤差的表現比全球尺度資料同化模式表現更好，代表區域性電離層結構能在導航定位有更好的成效。

The precise point positioning (PPP) can get the highly precise position by one GNSS receiver. However, it takes lots of time for PPP to converge the positioning error. One of the main reasons is the ionosphere delay. At present, the ionosphere delay is usually estimated by ionospheric models. However, the accuracy of these ionospheric models is affected by boundary conditions and the input parameters. In this study, we constructed the regional high-resolution ionosphere around Taiwan area by use the Ensemble Kalman Filter (EnKF) and Local Ensemble Transfer Kalman Filter (LETKF) to assimilate the ionospheric data from satellite observations into the international reference ionosphere (IRI) model. We then further evaluate the effect of regional assimilation ionosphere models in PPP by comparing the horizontal positioning error and the converge time of PPP with other physics-based and observation-based ionospheric models and the global-scale data assimilation ionospheric model in different times, seasons, and the solar activities.
Results found that EnKF/IRI and LETKF/IRI models can reconstruct a complete ionospheric structure over Taiwan. After the dynamic GPS PPP positioning test at two stations provided by Central Weather Bureau Geophysical Data System, the error convergence time can be shorted by more than 40% by using both EnKF/IRI and LETKF/IRI assimilation models compared with using IRI model. On days with high ionospheric electron density, the performance of regional EnKF/IRI and LETKF/IRI models is better than the global-scale data assimilation model, indicating that regional ionospheric structures can be more effective in navigation and positioning.

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李皇緣，使用全球電離層模型提升 GPS 精密單點定位成果，成功大學測量及空
間資訊學系研究所碩士論文，共 78頁，2021。