###### Abstract  
New smartphones provide real-time access to GNSS pseudorange, Doppler, or carrier-phase measurement data at 1 Hz. Simultaneously, they can receive corrections broadcast by GNSS reference stations to perform real-time kinematic (RTK) positioning. This study aims at the real-time positioning capabilities of smartphones using raw GNSS measurements as a conventional method and proposes an improvement to the positioning through the integration of Inertial Navigation System (INS) measurements. A U-Blox GNSS receiver, model ZED-F9R, was used as a benchmark for comparison. We propose an enhanced ambiguity resolution algorithm that integrates the traditional LAMBDA method with an adaptive thresholding mechanism based on real-time quality metrics. The RTK/INS fusion method integrates RTK and INS measurements using an extended Kalman filter (EKF), where the state vector x includes the position, velocity, orientation, and their respective biases. The innovation here is the inclusion of a real-time weighting scheme that adjusts the contribution of the RTK and INS measurements based on their current estimated accuracy. Also, we use the tightly coupled (TC) RTK/INS fusion framework. By leveraging INS data, the system can maintain accurate positioning even when the GNSS data are unreliable, allowing for the detection and exclusion of abnormal GNSS measurements. However, in complex urban areas such as Qazvin City in Iran, the fusion method achieved positioning accuracies of approximately 0.380 m and 0.415 m for the Xiaomi Mi 8 and Samsung Galaxy S21 Ultra smartphones, respectively. The subsequent detailed analysis across different urban streets emphasized the significance of choosing the right positioning method based on the environmental conditions. In most cases, RTK positioning outperformed Single-Point Positioning (SPP), offering decimeter-level precision, while the fusion method bridged the gap between the two, showcasing improved stability accuracy. The comparative performance between the Samsung Galaxy S21 Ultra and Xiaomi Mi 8 revealed minor differences, likely attributed to variations in the hardware design and software algorithms. The fusion method emerged as a valuable alternative when the RTK signals were unavailable or impractical. This demonstrates the potential of integrating RTK and INS measurements for enhanced real-time smartphone positioning, particularly in challenging urban environments. s 2024245907 10.3390/s24185907 10. Systems (GNSSs) have prominently emerged as the favored choice for ensuring accuracy within LBSs due to their remarkable capacity to function seamlessly across diverse weather conditions. Furthermore, GNSSs can seamlessly scale on a massive level while maintaining precision [1; 2]. As reported within the 2022 GNSS market report by the European Union Agency for the Space Programme (EUSPA), most--over 92%--of the low-cost GNSS chips are used in smartphones. This prevalence is attributed to the widespread integration and use of smartphones, owing to their portability, affordability, and ease of access. This establishes them as the most prevalent LBS services [3]. A significant advancement in this realm was materialized by the introduction the GNSS raw observation API in 2016, aligning with the need for smartphone positioning. This innovation satisfied enhanced performance demands by providing essential metrics such as the pseudorange, carrier phases, Doppler effects, and signal-to-noise ratios (SNRs). As a result, numerous smartphone users have expressed keen interest in adopting more precise positioning techniques [4]. During the initial stages of GNSS development, a limited number of smartphones and tablets could conduct measurements, typically utilizing only a single frequency and one GNSS constellation. Notable among these devices were the Google Nexus 9, Samsung S8, and Huawei P9. However, a crucial moment arrived in 2018, when the Xiaomi Mi8 introduced a dual-frequency GNSS smartphone, catalyzing a transformative shift within the market landscape.