## 1 Introduction  
Global Navigation Satellite System (GNSS) can provide all-day and all-weather global Positioning, Navigation, and Timing (PNT) services for global users, and its positioning errors will not accumulate over time [1, 2]. However, satellite signals are frequently blocked or even lose lock in complex urban scenarios, which cannot guarantee the effectiveness of positioning [3]. Inertial Navigation System (INS) has the advantages of strong autonomy and strong anti-interference and can obtain short-term, high-precision navigation and positioning results [4]. However, INS errors accumulate over time, and long-term independent solution can result in reduced accuracy or even divergence [5]. GNSS and INS possess highly complementary characteristics, which can effectively overcome the adverse effects of the harsh environment with the two systems integrated [6]. Therefore, GNSS/INS integrated navigation is widely utilized in naturalistic driving, high-precision vehicle navigation, Intelligent Transportation system (ITS), and autonomous driving [7, 8, 9, 10]. Based on the integrated method, GNSS/INS integrated navigation can be divided into loosely coupled, tightly coupled, and deeply coupled. Among them, the GNSS/INS tightly coupled system can maintain continuous positioning despite the insufficiently visible satellites and has the advantage of simple integrated structure and easier implementation, which has been extensively recognized by many scholars [11; 12; 13]. In the application of vehicle dynamic positioning, a continuous, reliable, and high-precision positioning method is urgently required. [PERSON] (2013) implemented an innovative methodology based on vehicle speed for the geo-referencing naturalistic driving method, which can overcome the problems related to the lack of positioning data [14]. However, this method requires extra geographic information. In addition, some scholars use GNSS and multiple sensors for positioning, which can integrate the advantages of each sensor, and obtain continuous and reliable positioning information in urban scenes [15; 16; 17]. But, the cost of multi-sensor is high, the weight is difficult to determine, and the amount of calculation is large. Therefore, based on the above discussion, this paper chooses GNSS/INS tightly coupled system positioning as the method to obtain the vehicle position in urban scenarios. However, the performance of GNSS/INS tightly coupled positioning is inevitably plagued by various outliers in the complex urban scenario [18]. For the GNSS receiver, the multipath effect and NLOS signal are the commonly adverse factors to restrict the positioning performance of GNSS, which further subsides the GNSS/INS integration system positioning capability [19; 20]. Multipath effect occurs when a signal is received through multiple paths between the satellite and the receiver antenna. Additionally, multipath interference can affect the phase detection characteristics of the receiver tracking loop, resulting in tracking and measurement errors [21]. Multipath includes both direct and reflected signals, and the reflected signals can be multiple. NLOS signal reception occurs when the direct path from the satellite to the receiver is blocked and the signal can only be received through the reflected path [22]. Due to the relatively low cost and the ability to provide accurate time reference and absolute coordinate information, GNSS solution is still an important and preferred technical method in the field of high-precision navigation and location services. Unfortunately, the degradation of GNSS positioning accuracy may negatively affect the performance of the entire system [23]. We need to mitigate the error of the standalone GNSS positioning with innovative signal-processing methods to promote the performance of GNSS/INS integration. Accurate multipath/NLOS detection and subsequent processing are the basis for the signal quality control and positioning strategy optimization of the GNSS/INS integration Navigation system [24].