在不久的將來，可以用來導航的衛星將超過150顆，假如能成功的整合這多星系全球導航衛星系統之衛星資訊，即可解決目前許多都市區域中因可視衛星不足而造成無法定位的情形，使用者的定位效能將大大的提升。美中不足的是，當使用者處於無遮蔽物之空曠環境時，可視衛星也將達到接近50顆的數量。同時要接收這麼多的衛星觀測量，也會對接收機造成巨大的演算負擔。為了保有多星系全球導航衛星系統的優勢，並同時減輕接收機演算負擔，本研究提出了一套新的演算法：優化之三角形(Tri-Angle Optimization ,TAO)衛星選擇法，此演算法能夠在現有之可視衛星終選擇較少的衛星，並在選擇的同時考慮各衛星之觀測量，以便能在使用較少的衛星狀態下，還能提供相同品質之定位精確度。

本研究針對四種導航衛星系統利用實收之衛星訊號去分析以及驗證其效能(四套系統包含：全球定位系统、格洛納斯系統、北斗衛星導航系統以及準天頂衛星系統)。本論文之首要目標為建立各衛星導航系統誤差之間的檢查機制，並藉由分析實收的衛星訊號提供建議以及注意事項給想要整合多星系系統來定位的使用者。在這之後，本研究之第二目標為提供一個新的衛星選擇機制去降低接收多星系衛星時造成的演算負擔。本研究所使用的接收機為NovAtel FlexPak 6，所搭配的天線盤為NovAtel 703 GGG。為了完成此兩項重要的目標，本研究提出了三種品質分析方式，分別是：一、衛星資料品質分析；二、衛星訊號品質分析；三、衛星觀測量品質分析。利用此三大類分析方式去偵測導致異常結果發生的原因。本論文也呈現成功整合各系統後，單一星系和多星系之效能差異。分析項目有：一、可視衛星數量；二、衛星仰角分布；三、衛星幾合分布；四、衛星定位精確度；五、在不同環境之可用性分析。在此之後，本研究針對在選擇衛星上應該要注意的三個議題提出討論，此三個議題分別為：一、衛星幾合配置之影響；二、衛星觀測量誤差之影響；三、衛星選擇數量之影響。在分析完所有議題並做出結論後，本研究提出一套可以同時考慮所有議題之結論的TAO衛星選擇方式。本研究利用八天的資料，將所有可能出現的全球導航衛星組合加入驗證，以便分析TAO衛星選擇法的效能。使用衛星選擇法之效能分析項目包含：選衛星後幾合分布情形、選衛星後定位精確度、整體演算時間分析。最終，本研究所提出之TAO衛星選擇法能夠在維持相通精確度的前提下，節省了高於50%的接收機運算量。此研究結果將有助於讓多星系全球導航衛星系統更普遍的存在於一般大眾可使用之接收機中。

The final objective of this research is to integrate multi-constellation Global Navigation Satellite System (GNSS) and reducing the computation load at the same time. This research utilizes actual satellite signal in space (SIS) data to evaluate four satellite navigation systems (GPS, QZSS, GLONASS, and BDS). The first objective of this dissertation is to establish an inspection method and provide suggestions to users who want to combine different satellite navigation systems for positioning. The second objective is to propose a satellite selection method to reduce the computation load due to the high number of satellites in multi-GNSS. The receiver used in this research is NovAtel FlexPak 6, and the antenna is NovAtel 703 GGG. With these objectives, this research starting from presents the integration results of multi-constellation GNSS, and compares the performance of stand-alone GNSS and various GNSS combinations. The analysis performance indicators are number of satellites in view, satellite elevation angle, satellite geometry distribution, positioning accuracy, and positioning availability under various mask angles. After that, this research provides three quality analysis methods, namely data quality analysis (DQA), signal quality analysis (SQA), and measurement quality analysis (MQA), for finding issues that cause anomalous results. After summarizing the results from these three methods, three important issues relate to satellite selection are then discussed. Namely the influences of satellite geometry, measurement error, and selected satellite number. Considering these issues, the TAO satellite selection algorithm is presented. This algorithm is verified for various satellite combinations using 8 days of SIS information to show overall performance. The analysis is divided into determining the constellation geometry distribution after satellite selection, determining positioning accuracy after satellite selection, and overall calculation time analysis. Compared to use all satellite to positioning, TAO is shown to maintain high positioning accuracy while reducing computation time of multi-GNSS positioning. The results of this research will help multi-constellation GNSS implementation in a commercial receiver and give general users the benefits of modern GNSS technology.

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