Abstract
Global Navigation Satellite Systems (GNSS) is often integrated with Inertial Measurement Unit (IMU) in order to improve the overall accuracy and reliability of the navigation system. The performance of the integrated system relies greatly on the quality of the GNSS measurement, however. In particular, contamination of GNSS measurements due to multipath interference and non-line-of-sight reception in urban environments affects the final performance of such integrated navigation. This paper therefore proposes two W-test aided quality control algorithms to achieve effective quality control for integrated GNSS/IMU navigation systems in urban areas. Each algorithm applies a different class of approach: i.e. the scoring strategy and the minimum error strategy. Experimental results showed that the solution with our proposed algorithms achieves the improvements of average 84% in horizontal positioning accuracy and 88% in vertical positioning accuracy compared with the pure IMU/GNSS solutions.
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References
Groves, P.D.: Principles of GNSS, Inertial, and Multi-Sensor Integrated Navigation Systems, 2nd edn. National Defense Industry Press (2013)
Liu, H., Nassar, S., El-Sheimy, N.: Two-filter smoothing for accurate INS/GPS land-vehicle navigation in urban centers. IEEE Trans. Veh. Technol. 59(9), 4256–4267 (2010)
Qiu, L., Yao, Y., Zhu, C.: Comparison of GPS/INS loose combination and compact combination implementation and positioning accuracy. Geogr. Surv. Mapp. 38(03), 17–19 (2013)
Xu, H., Angrisano, A., Gaglione, S., et al.: Machine Learning based LOS/NLOS Classifier and Robust Estimator for GNSS Shadow Matching. Satellite Navigation (2020)
Wang, J., Sun, R, Cheng, Q.: Comparison of direct and indirect filtering modes in the GPS/INS integration for UAV navigation. J. Beijing Univ. Aeronaut. Astronaut. (2020)
Zhang, Y., Li, D.: Multi-star failure monitoring algorithm based on RAIM. Command Control Simul. (2020)
Liu, C., Li, F.: Comparison and analysis of different GNSS weighting methods. Sci. Surv. Mapp. 43(242(08)), 39–44 (2018)
Brunner, F.K., Hartinger, H., Troyer, L.: GPS signal diffraction modelling: the stochastic SIGMA model. J. Geodesy 73(5), 259–267 (1999)
Gao, C., Wu, F., Chen, W.: An improved weight stochastic model in GPS precise point positioning. In: International Conference on Transportation. IEEE (2012)
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Qiu, M., Sun, R. (2021). W-Test Aided Quality Control Algorithm for GNSS/IMU Integrated Navigation in Urban Environments. In: Yang, C., Xie, J. (eds) China Satellite Navigation Conference (CSNC 2021) Proceedings. Lecture Notes in Electrical Engineering, vol 774. Springer, Singapore. https://doi.org/10.1007/978-981-16-3146-7_50
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DOI: https://doi.org/10.1007/978-981-16-3146-7_50
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