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Land vehicle navigation using low-cost integrated smartphone gnss mems and map matching technique

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The demand for smartphone positioning has grown rapidly due to increased positioning accuracy applications, such as land vehicle navigation systems used for vehicle tracking, emergency assistance, and intelligent transportation systems. The integration between navigation systems is necessary to maintain a reliable solution. High-end inertial sensors are not preferred due to their high cost. Smartphone microelectromechanical systems (MEMS) are attractive due to their small size and low cost; however, they suffer from long-term drift, which highlights the need for additional aiding solutions using road network that can perform efficiently for longer periods. In this research, the performance of the Xiaomi MI 8 smartphone's single-frequency precise point positioning was tested in kinematic mode using the between-satellite single-difference (BSSD) technique. A Kalman filter algorithm was used to integrate BSSD and inertial navigation system (INS)-based smartphone MEMS. Map matching technique was proposed to assist navigation systems in global navigation satellite system (GNSS)-denied environments, based on the integration of BSSD-INS and road network models applying hidden Marcov model and Viterbi algorithm. The results showed that BSSD-INS- map performed consistently better than BSSD solution and BSSD–INS integration, irrespective of whether simulated outages were added or not. The root mean square error (RMSE) values for 2D horizontal position accuracy when applying BSSD-INS-map integration improved by 29% and 22%, compared to BSSD and BSSD-INS navigation solutions, respectively, with no simulated outages added. The overall average improvement of proposed BSSD-INS-map integration was 91%, 96%, and 98% in 2D horizontal positioning accuracy, compared to BSSD-INS algorithm for six GNSS simulated signal outages with duration of 10, 20, and 30 s, respectively.
Słowa kluczowe
Rocznik
Strony
138--157
Opis fizyczny
Bibliogr. 21 poz., rys., tab.
Twórcy
  • Faculty of Engineering, Cairo University, Cairo, Egypt
  • Faculty of Engineering, Cairo University, Cairo, Egypt
  • Faculty of Engineering, Cairo University, Cairo, Egypt
Bibliografia
  • Abd Rabbou, M., & El-Rabbany, A. (2015a). Integration of GPS precise point positioning and MEMS-based INS using unscented particle filter. Sensors (Switzerland), 15(4), 7228-7245. https://doi.org/10.3390/s150407228.
  • Abd Rabbou, M., & El-Rabbany, A. (2015b). An Improved GPS/GLONASS PPP Model for Kinematic Applications. Arab Institution of Navigation Journal, 16, 37-42.
  • Angrisano, A. (2010) “GNSS/INS Integration Methods”.
  • Attia, M. (2013). Map Aided Indoor and Outdoor Navigation Applications. University of Calgary, 2(SGEM2016 Conference Proceedings, ISBN 978-619-7105-16-2 / ISSN 1314-2704), 1-39.
  • Dabove, P., & Di Pietra, V. (2019). Towards high accuracy GNSS real-time positioning with smartphones. Advances in Space Research, 63(1), 94-102. https: z//doi.org/10.1016/j.asr. 2018.08.025.
  • Elmezayen, A., & El-Rabbany, A. (2019). Precise point positioning using world’s first dualfrequency GPS/galileo smartphone. Sensors (Switzerland), 19(11). https://doi.org/10.3390/s19112593.
  • European GNSS Agency. (2017) White Paper on “Using GNSS Raw Measurements on Android devices”; Luxembourg: Publications Office of the European Union, 2017.
  • Export | Open Street Map.(2020). Retrieved December 12, 2020, from https://www.openstreetmap.org/export#map=4/65.68/-93.60.
  • Goh, C. Y., Dauwels, J., Mitrovic, N., Asif, M. T., Oran, A., & Jaillet, P. (2012). Online mapmatching based on hidden Markov model for real-time traffic sensing applications. IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC, 117543, 776-781. https://doi.org/10.1109/ITSC.2012.6338627.
  • GSA Raw measurements task force. (2017). USING GNSS RAW MEASUREMENTS ON ANDROID DEVICES - Towards better location performance in mass market applications. Publications Office of the European Union, 48. https://doi.org/10.2878/449581.
  • Hamed, M., Abdallah, A., & Farah, A. (2019). Kinematic PPP using mixed GPS/Glonass single-frequency observations. Artificial Satellites, 54(3), 97-112. https://doi.org/10.2478/arsa2019-0008.
  • Jung, C. (2019). “Offline Map-Matching for matching a trajectory with a network”. AGITJournal for applied geoinformatics,5, 156-163.
  • Karamat, T. Bin. (2014). Improved Land Vehicle Navigation and GPS Integer Ambiguity Resolution using Enhanced Reduced-IMU/GPS Integration. (June), 264. http://www.pqdtcn.com/thesisDetails/A17DBDE946CD40F2F57C8380AFB10168.
  • Luo, A., Chen, S., & Xv, B. (2017). Enhanced map-matching algorithm with a hidden markov model for mobile phone positioning. ISPRS International Journal of Geo-Information, 6(11), 1-17. https://doi.org/10.3390/ijgi6110327.
  • Moussa, M, Moussa, A., El-sheimy, N., 2019. “Ultrasonic Wheel Based Aiding for Land Vehicle Navigation in GNSS denied environment”, in: Proceedings of the 2019 International Technical Meeting, ION ITM 2019, Reston, Virginia, pp. 319-333.
  • Niu, X., Zhang, H., Chiang, K.-W., & El-Sheimy, N. (2010). Using Land-Vehicle Steering Constraint To Improve the Heading Estimation of Mems Gps/Ins Georeferencing Systems. 2010 Canadian Geomatics Conference and Symposium of Commission I, Isprs Convergence in Geomatics - Shaping Canada’S Competitive Landscape, 38(1).
  • Noureldin, A., Karamat, T. B., & Georgy, J. (2013). Fundamentals of inertial navigation, satellite-based positioning and their integration. In Fundamentals of Inertial Navigation, Satellite-Based Positioning and their Integration. https://doi.org/10.1007/978-3-642-30466-8.
  • Raw GNSS Measurements | Android Developers. (n.d.). Retrieved December 20, 2020, from https://developer.android.com/guide/topics/sensors/gnss.
  • Trogh, J., Botteldooren, D., De Coensel, B., Martens, L., Joseph, W., & Plets, D. (2020). Map Matching and Lane Detection Based on Markovian Behavior, GIS, and IMU Data. IEEE Transactions on Intelligent Transportation Systems, 1-15. https://doi.org/10.1109/tits. 2020.3031080.
  • Wu, Q., Sun, M., Zhou, C., & Zhang, P. (2019). Precise point positioning using dual-frequency GNSS observations on smartphone. Sensors (Switzerland), 19(9). https://doi.org/10.3390 /s19092189.
  • Zhang, Q., Hu, Y., Li, S., Zhang, T., & Niu, X. (2021). Mounting Parameter Estimation from Velocity Vector Observations for Land Vehicle Navigation. IEEE Transactions on Industrial Electronics, 0046(c). https://doi.org/10.1109/TIE.2021.3075883.
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-36334372-c416-44a5-86f6-93a2bf172b0f
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