整合多星系全球導航衛星系統為優化定位結果的趨勢，然而由於一般商用接收機受限於運算能力，急遽增加的衛星數量將造成其使用上的負擔及困難。此外，位於市區的使用者經常接收到反射訊號，並造成非直視性(Non-line-of-sight, NLOS)和多路徑(multipath)效應訊號的接收。為解決上述問題，本研究提出之演算法包含基於衛星幾何分佈和基於觀測量品質的衛星選擇方法，於不同定位環境中以合理之演算時間提供良好定位結果。

本研究使用兩種基於衛星幾何分佈之選擇方式以減少最後計算定位解之衛星數量：半優化衛星選擇(Quasi-Optimal Satellite Selection, QOSS)及三角形優化(Tri-Angle Optimal)衛星選擇方法。為檢查觀測量品質，本研究使用多重錯誤假設下的接收機自主完整性監測(Receiver Autonomous Integrity Monitoring, RAIM)錯誤偵測與排除(Fault Detection and Exclusion, FDE)，並利用貪婪式演算法(greedy search)運算。所使用之衛星選擇方法將與其他選擇方法在衛星幾合分佈及定位誤差上做比較。若使用者處於空曠環境中，兩種衛星幾何選擇方法加上觀測量監測將皆被使用，使計算定位解的衛星數量降低至六顆。由於本研究使用三組星系GNSS，須計算使用者三維位置解和三個使用者時鐘誤差項，因此至少需要接收六顆衛星用以解算三星系GNSS。在限制環境中，僅使用一次衛星分佈選擇加上RAIM FDE。另外本研究使用道路模擬限制之擴展示卡曼濾波器(Extended Kalman Filter, EKF)以解決在極端艱困環境下的定位困難。

所提出之演算法以商用接收機實收資料，在不外加感測器的情況下進行測試並分析。實驗結果顯示本研究之演算法能在不同環境中，以最少的衛星數量提供良好之定位解。所提出之演算法最多以10顆衛星做最後使用者位置解算，而在開闊的環境中，最少能以6顆衛星進行定位解運算。在一般都市環境下，相較於最小平方法之結果，此研究能在平均水平定位誤差達成6公尺、平均垂直定位誤差達成56公尺的優化。在密集都市環境下，最小平方法無法解算出水平誤差小於3.25公尺之定位解，而此研究提出之方法能夠提供百分之11.429小於3.25公尺水平誤差的定位解，相較於最小平方法的結果，亦在平均水平定位誤差提供11公尺、平均垂直定位誤差提供58公尺的優化。

Integrating multi-constellation global navigation satellite systems (GNSSs) is a beneficial method to improve the positioning performance. However, the dramatic increases in the number of satellites is causing an issue to commercial receivers due to the limited availability of computational resources. Moreover, users in urban areas often suffer from signal blockage and reflections, resulting in non-line-of-sight (NLOS) and multipath reception. To address these issues, the objective of this research is to develop an algorithm for satellite selection that considers both satellite geometry and measurement quality under various positioning environments within a desired computational time and with good positioning performance.

Two satellite selection algorithms that consider satellite geometry are used to reduce the number of satellites, namely quasi-optimal satellite selection (QOSS) and tri-angle optimal (TAO) satellite selection algorithms. Receiver autonomous integrity monitoring (RAIM) fault detection and exclusion (FDE), with a multiple-fault assumption based on greedy search is used to check measurement quality. The applied satellite selection algorithms are compared with other selection methods in terms of satellite geometry and positioning error. For users in open-sky areas, two rounds of the geometry-based satellite selection and the measurement quality check are conducted, and only six satellites are needed to calculate the position solution. Since three constellations of a GNSS are utilized in this study, the user position in three dimensions and three user clock biases should be calculated, where a minimum of six satellites are required for integrated positioning of a three multi-constellation GNSS. For users in constrained environments, one geometry selection is performed followed by RAIM FDE. Furthermore, an extended Kalman filter with a road-model-constrained solution is adopted to overcome the positioning difficulties in extreme positioning scenarios. The method effectively generates accurate positioning results for users.

The proposed algorithm is evaluated using a real dataset collected with a commercial receiver without additional sensors to test its applicability. The results show the algorithm provides good positioning performance using the minimum number of tracking channels under various environments. A maximum of 10 satellites are used for the final positioning algorithm in the proposed method, while a minimum of 6 satellites can be reached in open sky areas. In middle urban areas, improvements of 6 meters in the horizontal positioning difference mean and 56 meters in the vertical positioning difference mean are achieved, respectively, compared to the least squares results. In urban canyons, where the least squares generates a 0 percent horizontal difference within 3.25 meters, the proposed algorithm provides a 11.429 percent horizontal difference under the same conditions, with a horizontal difference mean that is 11 meters lower and a vertical difference mean that is 58 meters lower compared to the least squares results.

[1] GPS-ICD, Global Positioning System Directorate Systems Engineering & Integration Interface Specification IS-GPS-200H, 2013.
[2] GLONASS-ICD, Global Navigation Satellite System GLONASS, Interface Control Document, Navigational radio signal in bands L1, L2, Edition 5.1 Russian Institute of Space Device Engineering, 2008.
[3] BDS-ICD, BeiDou Navigation Satellite System Signal In Space Interface Control Document. Open Service Signal (Version 2.0). China Satellite Navigation Office, 2013.
[4] IS-QZSS, Interface Specification for QZSS, Quasi-Zenith Satellite System Navigation Service, version 1.6, Japan Aerospace Exploration Agency, 2014.
[5] G. Artaud, A. De Latour, J. Dantepal, L. Ries, E. Senant, N. Maury, J.-C. Denis and T. Bany, “A new GNSS multi constellation simulator: NAVYS,” in Satellite Navigation Technologies and European Workshop on GNSS Signals and Signal Processing (NAVITEC), 5th ESA Workshop, 2010.
[6] M. Bahrami and M. Ziebart, “GNSS Geodetic Reference Frames: Consistency, Stability and the Related Transformation Parameters,” Proceedings of the 24th International Technical Meeting of the Satellite Division of the Institute of Navigation, 2001.
[7] K. Huber, F. Heuberger, C. Abart, A. Karabatic, R. Weber and P. Berglez, “PPP: Precise Point Positioning – Constraints and Opportunities,” FIG Congress 2010, Sydney, Australia, 11-16 April 2010.
[8] S. Kogure, “Asia Oceania is the 'Showcase of the New GNSS Era',” 5th QZSS user meeting, 10th March 2010.
[9] Y. Yang, Ronald R. Hatch and Richard T. Sharpe, “GPS Multipath Mitigation in Measurement Domain and Its Applications for High Accuracy Navigation,” Proceedings of the 17th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2004), Long Beach, CA, September 2004.
[10] J. Soubielle, I. Fijalkow, P. Duvaut, and A. Bibaut, “GPS Positioning in a Multipath Environment,” IEEE Transactions on Signal Processing, vol. 50, no. 1, January 2002.
[11] D. Roongpiboonsopit and H. A Karimi, “A multi-constellations satellite selection algorithm for integrated global navigation satellite systems,” Journal of Intelligent Transportation Systems, vol.13, no. 3, pp. 127-141, 2009.
[12] C.-W. Park, Precise relative navigation using augmented CDGPS, Thesis, Citeseer, 2001.
[13] A.-L. Tao and S.-S. Jan, “Optimal Navigation with Multi-constellation GNSS: A Satellite Selection Algorithm,” ION GNSS+ 2016, Portland, Oregon, September 12-16, 2016.
[14] M. Kihara and T. Okada, “A satellite selection method and accuracy for the global positioning system,” Navigation, vol. 31, no. 1, pp. 8-20, 1984.
[15] J. Li, A. Ndil, L. Ward, S. Buchman, “GPS receiver satellite/antenna selection algorithm for the Stanford gravity probe B relativity mission,” National Technical Meeting’Vision 2010: Present and Future, 1999.
[16] J. Blanch, T. Walter, and P, Enge, “Efficient Multiple Fault Exclusion with a Large Number of Pseudorange Measurements,” ION ITM 2015, Dana Point, California, January 26-28, 2015.
[17] L.-T. Hsu, H. Tokura, N. Kubo and S. Kamijo, “Evaluation of Multiple Fault Exclusion Based on L1 Norm Minimization with multi-GNSS measurements in Urban Environments,” ION GNSS+ 2015, Tampa, Florida, September 14-18, 2015.
[18] Y. Cui and S. S. Ge, “Autonomous Vehicle Positioning With GPS in Urban Canyon Environments,” IEEE Transactions on Robotics and Automation, vol. 19, no. 1, February 2003.
[19] P. Misra and P. Enge, Global Positioning System: Signals, Measurements and Performance Second Edition, Lincoln, MA: Ganga-Jamuna Press, 2006.
[20] GPSoftNav, “SatNav ToolBox for MATLAB”.
[21] S. Bhattacharyya and D. Gebre-Egziabher, “Kalman Filter-Based RAIM for GNSS Receivers,” IEEE Transactions on Aerospace and Electronic Systems, vol. 51, no. 3, July 2015.
[22] Y. C. Lee, “New Advanced RAIM with Improved Availability for Detecting Constellation-wide Faults, Using Two Independent Constellations,” NAVIGATION, Journal of The Institute of Navigation, vol. 60, no. 1, Spring 2013.
[23] A. Rakipi, B. Kamo, S. Cakaj, V. Kolici, A. Lala, I. Shinko, “Integrity Monitoring in Navigation Systems: Fault Detection and Exclusion RAIM Algorithm Implementation,” Journal of Computer and Communications, 3, pp. 25-33.
[24] Q.-D. Xiao, “A Study of RAIM Algorithm of the Multi-constellation Navigation System,” SOFTWARE, vol. 36, no. 4, 2015.
[25] L.-T. Hsu, Y. Gu, S. Kamijo , “NLOS Correction/Exclusion for GNSS Measurement Using RAIM and City Building Models,” Sensors, 2015.
[26] L.-T. Hsu, Y. Gu, S. Kamijo, “3D building model-based pedestrian positioning method using GPS/glonass/qzss and its reliability calculation,” GPS Solutions, Volume 20, pp. 413-428, July 2016.
[27] J.-H. Song and G.-I. Jee, “Performance Enhancement of Land Vehicle Positioning Using Multiple GPS Receivers in an Urban Area,” Sensors, October 2016.
[28] S. Gleason and D. Gebre-Egziabher, GNSS Applications and Methods.
[29] P. Zarchan and H. Musoff, Fundamentals of Kalman Filtering: A Practical Approach.
[30] T.Takasu, RTKLIB: Open Source Program Package for RTK-GPS, FOSS4G 2009, Tokyo, Japan, November 2, 2009.
[31] L.-T. Hsu, “Implementation of Vector Tracking Loop in GPS Software Receiver and Its Evaluation in Multi-path Environments,” PhD Thesis, National Cheng Kung University, 2013.