## 1 Introduction  
For nearly a decade, as a convenient mobile terminal integrating various services such as mobile communication and location-based, smartphones have rapidly spread among the masses [1, 2]. According to the GNSS market report, smartphones are now the dominant installation base for GNSS devices [3]. Based on the precise location information of users from smartphones, the mobile applications (APPs) can provide a variety of urban transportation services including vehicle navigation and travel trajectory. In September 2017, with the emergence of the world's first dual-frequency GNSS chip GCM47755 [3] from Broadcom corporation, the progress of precise point positioning technology in smartphones was actively promoted. However, its stability and reliability are still restricted by the poor multipath suppression capability of the passive linearly polarized embedded GNSS antenna of smartphones in urban environments which are highly dynamic and complex [4]. Nevertheless, with the improved performance and decreased cost of micro-electro-mechanical systems (MEMSs), it is feasible to use the measurement data from IMUs of smartphones to aid the precise positioning under GNSS-degraded environments. As early as 2012, [PERSON] et al. [5] used the inertial sensors in the iPhone 4 from Apple Inc. to make Global Positioning System (GPS)/INS loosely-coupled integration with 15-statesKalman filter for car navigation, and verified that the MEMS sensors in smartphones can enhance the GPS positioning effectively. In 2015, [PERSON] et al. [6] also studied the conjunction between GPS data and collected IMU data from smartphones such as iPhones to estimate the missing GPS route even in the case of signal failures. Prior to Android release N (\"Nougat\" = version 7) provided by Google Inc. in May 2016, the GNSS chipset of Android smartphones could only output the position-velocity-time (PVT) and limited satellites' elevation and azimuth information [7]. Since then, the raw GNSS observations of smartphones can be outputted in receiver-independent exchange (RENIX) format directly from mobile APPs, which is convenient to analyze the characteristics of GNSS pseudorange, carrier phase, doppler, and signal strength observations from smartphones [8]. In recent years, more modern smartphones are equipped with the dual-frequency GNSS chip, and the precise point positioning technology is also widely used for smartphones' precise positioning [9; 10; 11]. The PPP is a precision absolute point positioning technology based on state space domain correction information by using GNSS pseudorange and carrier phase observations along with international GNSS service (IGS) precise orbit products [12; 13]. In May 2018, Xiaomi corporation released Mi 8, the world's first dual-frequency GNSS smartphone. Subsequently, many researchers analyzed the characteristics of dual-frequency GNSS signal observed by smartphones, and the adverse factors, such as duty cycle [4; 10; 14], carrier-to-noise ratio [7; 15], poor multipath suppression capability [16; 17], and gradual accumulation of phase error [11; 17; 18], which affect the positioning performance of smartphones were found and improved. The results of correlation studies on multi-GNSS PPP of smartphones indicated that the static horizontal positioning accuracy attained dm level in the open area without significant signal obstructions and strong multipath reflectors, and even can reach cm level after a long time to convergence [8; 10]. However, the kinematic positioning error of smartphone PPP will increase to several meters in realistic urban environments, and even to tens of meters under GNSS-degraded environments. [PERSON] et al. [10] used the ionosphere-free combined PPP mathematical model with GPS/Galileo pseudorange and carrier phase observations L1/L5 and E1/E5 of Mi 8, and the kinematic positioning trajectory had severe fluctuations within 4-5 m of the reference trajectory with extreme offsets over 20 m on the playground. [PERSON] et al.