|Abstract:||With the popularity of researches in self-driving and advanced control systems, high-precision positioning techniques in urban environments have attracted more and more attention. The buildings and trees always cause signal reflections and blockages, which lead to multipath phenomenon in GNSS receptions and a reduction in the number of available satellites. In such a challenging environment, the conventional Real-time kinematic (RTK) techniques cannot provide precise positioning results independently, since the integer ambiguity resolution as its critical step is relevant to the observation quality of satellite signals. Thus, in this paper we propose an improved ambiguity resolution algorithm for INS/RTK integration, which search integer solution in the position domain using particle filter. Our integrated INS/RTK algorithm aims at enhancing the availability of integrated navigation systems and maintaining accuracy in harsh environments. Here the INS is integrated to predict motion between adjacent epochs and to generate a set of particles as searching region. In this case, inertial aiding can help reduce search space volume by providing a more accurate position and error covariance matrix. Moreover, double-differenced GPS and BDS measurements are used to update the posterior probability to determine the final integer solution. By constructing an appropriate observation model, the calculation of the posterior probability only involves the fractional part of current carrier-phase observations, so the new algorithm is insensitive to the quality of pseudorange and cycle slips. The improved ambiguity resolution algorithm is demonstrated on both simulated and real-world datasets. Compared with other RTK algorithms which search integer solutions in the ambiguity domain, our improved algorithm shows better accuracy and stability, especially when the satellite visibility changes frequently or the pseudorange noise is large.|
Proceedings of the 31st International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2018)
September 24 - 28, 2018
Hyatt Regency Miami
|Pages:||3122 - 3135|
|Cite this article:||
Li, Wei, Cui, Xiaowei, Xu, Xueyong, Lu, Mingquan, "An Improved Ambiguity Resolution Algorithm Based on Particle Filter for INS/RTK Integration in Urban Environments," Proceedings of the 31st International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2018), Miami, Florida, September 2018, pp. 3122-3135.
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