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.

城市和郊区环境中定位系统的可靠性和鲁棒性是固有的。随着智能交通系统 (ITS) 应用在这种充满挑战的环境中不断增加，这一点显而易见。全球导航卫星系统 (GNSS) 代表了在这些应用中用于导航目的的主要定位技术，在开阔的天空区域可以令人满意。然而，GNSS 无法在城市环境中提供相同水平的导航性能。造成这种情况的主要原因之一是无视距 (NLOS) 信号。在这项研究中，利用 GNSS 和光探测和测距 (LiDAR) 传感器的集成，提出了一种用于检测 NLOS 信号的新算法。实际现场数据用于测试和验证所提出的策略和算法。相位平滑代码观察用于评估排除 NLOS 观察后的精度改进。结果表明，应用所提算法后，水平方向的定位精度有显着提高。在检测到 NLOS 信号的所有时期，这种改进达到 10.403 m，平均值为 2.162 m（改进 62.2%）。在分析了Cross-Track（CT）和Along-Track（AT）方向的这种改进后，发现精度提高达到8.641 m，CT方向平均值为1.699 m，精度提高6.879 m，平均值为AT方向1.303 m。应用所提出的算法后，可以显着提高定位精度。在检测到 NLOS 信号的所有时期，这种改进达到 10.403 m，平均值为 2.162 m（改进 62.2%）。在分析了Cross-Track（CT）和Along-Track（AT）方向的这种改进后，发现精度提高达到8.641 m，CT方向平均值为1.699 m，精度提高6.879 m，平均值为AT方向1.303 m。应用所提出的算法后，可以显着提高定位精度。在检测到 NLOS 信号的所有时期，这种改进达到 10.403 m，平均值为 2.162 m（改进 62.2%）。在分析了Cross-Track（CT）和Along-Track（AT）方向的这种改进后，发现精度提高达到8.641 m，CT方向平均值为1.699 m，精度提高6.879 m，平均值为AT方向1.303 m。