Abstract: Objectives: Recognizing the fact that the unknown inertial measurement unit (IMU) mounting angles, i.e., the misalignment angles between the smartphone's IMU and the vehicle body frame, can seriously affect the smartphone-based Global Navigation Satellite System (GNSS)/inertial navigation system (INS) integrated system for vehicular navigation. Methods: In this contribution, a real-time estimation of the IMU mounting angles is addressed through a Kalman Filter (KF) whose measurement updates are realized by position variation between epochs derived by time-differenced carrier phase (TDCP) besides the smartphone GNSS/MEMS IMU tightly-coupled integration algorithm. Results: Two vehicular navigation experiments were carried out in urban challenging environments to evaluate the performance of the proposed algorithm. The results show that a large mounting angle can be initialized within 80 seconds under moderate occlusion conditions, then convergence of the estimated mounting angle is shown to occur within minutes, and the accuracy is in the order of 2°. When the mounting angle is estimated successfully, the positioning performance of smartphone vehicular positioning will be improved significantly, both horizontal and vertical accuracy can be maintained at about 5m in terms of root-mean-square by applying non-holonomic constraint (NHC) under severe occlusion conditions. Conclusions: The algorithm proposed can estimate large mounting angles accurately and rapidly without any auxiliary equipment such as an odometer.