Research On GPS/SM Integrated Positioning Technology In Urban Environment

With the rapid development of geographic information, electronic communications and mobile Internet technology, the location-based service(LBS) has increasingly been widespread concern in the industry for all people, and continuous and accurate position is the basis of satellite navigation systems and location-based services. However, Satellite navigation system in dense high-rise and short spacing buildings, called urban canyon environments, buildings block, reflection, diffraction and visible satellite strip distribution have an influence on the signal received by the receiver, resulting in signal attenuation,multipath interference, non-line of signal(NLOS) and large Geometric Dilution of Precision(GDOP), so that the traditional GPS system has greater positioning errors and even can not position solution available at all. Both of accuracy and availability positioning in urban canyon environments has been a hot topic in domestic and foreign. The research work is mainly as follows:Firstly, this paper mainly introduces three-dimensional(3D) building model acquisition method in experimental scene based on the overview of RTK and total station measurement principle.Secondly, the traditional GPS positioning accuracy is poor and even can not pisition solution. For solving this issue, Shadow Matching(SM) positioning algorithm is implemented based on analysis of GPS satellites visibility used 3D building model in urban canyon environments. Tested by simulation and measured data, experimental results show that: SM positioning algorithm can achieve high-precision positioning in the across-street direction, but lack of precision in the along-street direction, and the location is not continuous.Then, shadow matching positioning algorithm is difficult to ensure positioning accuracy in the along-street direction. To solve this problem, a novel GPS/SM integrated positioning algorithm based on EKF is presented. The work establishes state and observation equation of system by extended kalman filtering(EKF) based on the introduction of GPS speed information and the SM positioning algorithm. In the experimental verification, the proposed algorithm improves the along-street accuracy with a mean absolute deviation of 1.18 m, with a 67.0% and 72.8% reduction compared to the traditional GPS with 3.58 m and the SM with4.34 m, and also ensures high-precision in the across-street direction at the same time, the positioning result is continuous and reliable.Finally, the GPS system was interfered easily by the surrounding environment in urban area, and the carrier mobility changes frequently, which leads to poor accuracy of GPS dynamic filtering. To solve this problem, a new improved strong tracking Extended Kalmanfilter(STEKF) based on fuzzy logic adaptive controller(FLAC) is presented, called fuzzy logic adaptive strong tracking Extended Kalman filter(FASTEKF). By monitoring the residual mean, the FLAC of this method dynamically adjusts the softening factor according to fuzzy rules. For this reason, this method modifies the fading adaptively and achieve the inhibition of carrier mutation. The results of simulation indicate that this new approach has a better accuracy than the EKF and STEKF in the field of maneuvering target tracking in carrier mutation, its convergence speed and stability are also improved.