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The reliability and robustness of positioning systems in urban and suburban environments are intrinsic. This is obvious following the continuous increase of Intelligent Transportation Systems (ITS) applications in such challenging environments. Global Navigation Satellite Systems (GNSS) represent the primary positioning technique used for navigation purposes in these applications, which can be satisfying in open-sky areas. However, GNSS cannot provide the same level of navigation performance in urban environments. One of the main reasons for this is the No-Line of Sight (NLOS) signals. In this study, the integration of GNSS and Light Detection and Ranging (LiDAR) sensors is exploited, and a new algorithm is proposed for the detection of NLOS signals. Real field data are used to test and validate the proposed strategy and algorithm. Phase-smoothed code observations are employed to evaluate the accuracy improvement after excluding the NLOS observations. The results show that the horizontal direction's positional accuracy can be improved significantly after applying the proposed algorithm. This improvement reaches 10.403 m with a mean value of 2.162 m (62.2% improvement) over all epochs with detected NLOS signals. After analysing this improvement in the Cross-Track (CT) and Along-Track (AT) directions, it is found that the accuracy improvement reaches 8.641 m with a mean value of 1.699 m in the CT direction and 6.879 m with a mean value of 1.303 m in the AT direction.

Detection of GNSS no-line of sight signals using LiDAR sensors for intelligent transportation systems