# Assessment of Affordable Real-Time PPP Solutions for Transportation Applications
## 1 Introduction
[26] introduced a low-cost Internet of Things (IoT) GNSS device that delivered commercial PPP-RTK corrections; their configuration was explored in the moving vehicular domain. Their device obtained horizontal and vertical positioning accuracy at the decimeter level. Additionally, [PERSON] and [PERSON] [31] presented a low-cost triple-constellation GNSS/INS system using a tightly coupled scheme for precise land vehicular applications. Their system was examined through three integration systems, and an adaptive Kalman filter was applied to remove the measurement outliers. Thereafter, the system was examined in three kinematic trials, showing that sub-meter- to meter-level positioning accuracy was achieved in the three components. Furthermore, [PERSON] et al. [33] developed a new multiple-constraint-fused Kalman-based navigation (MCKN) method for low-cost GNSS/INS integration in urban areas to overcome accumulated errors due to GNSS outages. Their method showed high-level performance in denied areas. [PERSON] et al. [37] proposed an affordable GNSS solution for tracking vehicles and identifying areas of the road where speed limits are exceeded. For this purpose, a system was developed using two low-cost GNSS modules to determine GNSS speed; furthermore, a smartphone was utilized to record the speedometer on video. Their proposed system showed great potential in automatic speed control and monitoring applications. These studies demonstrate that both RTK and PPP-RTK GNSS techniques have been used widely; nevertheless, these solutions are costly because they require two-receiver configurations or commercial corrections from a GNSS reference station network. As a result, the key innovation of our study is the proposal of a cost-effective real-time precise point positioning (RT-PPP) solution for transportation applications involving an affordable GNSS module and instantaneous satellite orbit and clock correction products. The main reason for choosing the RT-PPP scenario in our study is the fact that it employs only a one-receiver configuration; in addition, real-time satellite orbit and clock products are freely available from different international GNSS service (IGS) analysis centers, such as the Bundesamt fur Kartographie und Geodasie (BKG), Centre National d'Etudes Spatiales (CNES), and the GNSS research center of Wuhan University (WHU). Furthermore, these products are available in the instantaneous SSR correction format. At present, instantaneous clock and orbit products are widely utilized in various applications, including positioning, maritime, surveying, tropospheric, and ionospheric modeling applications. Recently, several studies have examined the accuracy of these products in different scenarios [38; 39; 40; 41; 42; 43; 44; 45]. For example, [PERSON] et al. [45] explored the accuracy of estimated real-time zenith tropospheric delay using GPS, Galileo, and BeiDou RT-PPP solutions based on SSR products from various centers. They revealed that the derived zenith tropospheric delay values using WHU satellite orbit and clock products had the highest accuracy. [PERSON] et al. [46] utilized a cost-effective real-time GNSS system for geodynamic applications, demonstrating its efficiency in improving positioning accuracy. To achieve the objective of our study, we acquired multi-constellation GNSS observations utilizing an affordable ZED-F9P GNSS device within a moving car in a suburban environment; then, the datasets were processed using the RT-PPP processing model under various scenarios: GPS, GPS/GLONASS, GPS/Galileo, and GPS/GLONASS/Galileo RT-PPP. Instantaneous SSR corrections from BKG, CNES, and WHU ACs were used to adapt the real-time mode. Additionally, a conventional RTK solution was applied with the aforementioned GNSS satellite system combination. To explore the accuracy of our proposed solutions, position estimates obtained using both the RT-PPP and RTK techniques were validated against those obtained with the differential GNSS kinematic method.