## 1 Introduction  
Unmanned aerial vehicles (UAVs) are widely used in various applications due to their capability to provide rapid and accurate mapping and generate three-dimensional spatial data. Especially, UAVs have become increasingly valuable in the domains of photogrammetry and remote sensing [1, 2, 3, 4]. The quality of products such as orthophotos and digital elevation model (DEM) generated by UAVs is significantly enhanced with the integration of additional sensors, coupled with advancements in hardware and software technologies. Positioning is a fundamental component of spatial information in UAV photogrammetry, making the integration of Global Navigation Satellite System (GNSS)receivers essential for maximizing operational effectiveness. In aerial photogrammetry, there are two approaches to georeferencing: direct and indirect [5; 6; 7]. Direct georeferencing determines the camera's position and orientation using onboard GNSS and IMU systems, removing the dependency on ground control points (GCPs). The indirect approach relies on GCPs, whose positions are known. It requires direct interaction with the surveyed area, careful GCP placement, precise image matching, and thorough calibration to ensure exact results. In the absence of GCPs, the quality of GPS-based camera positions significantly affects the accuracy of UAV point clouds generated by direct georeferencing [8]. RTK necessitates the utilization of specific hardware and software components to attain high-precision positioning capabilities. The hardware includes a GNSS receiver that supports RTK functionality (compatible with GPS, GLONASS, Galileo, and BeiDou), an antenna (a high-quality unit designed to capture satellite signals with minimal interference and multipath errors), and a base station (a fixed reference point, or access to a network of reference stations with a known position, which requires an antenna and receiver that can transmit real-time correction data via RTK.). Data communication (transmitting real-time correction data from the base station to the rover receiver) is also essential. Software: includes components such as RTK processing, data recording, and analysis. In RTK mode, measurements are taken in real time, whereas in PPK mode, computations occur after the data are recorded [9]. The PPK method is applicable when there is a potential interruption with the base station during RTK measurement or when operating outside the coverage area, meaning no real-time corrections are available. PPK is regarded as a reliable and robust alternative to RTK. PPK is more flexible than RTK, allowing multiple types of data processing to minimize errors [10]. Furthermore, more accurate products (precise orbits, clock products, etc.) may enhance the processing methods. Relative positioning techniques require infrastructure, additional hardware (e.g., base GNSS station, RTK receiver), and more labor. These are aspects that restrict the study of UAV photogrammetry in some cases. Another alternative positioning technique to RTK and PPK is PPP. PPP technique based on absolute positioning is an alternative for UAV photogrammetry. The technique is straightforward and significantly reduces survey costs since users can collect data using a single GNSS receiver to determine their position. The PPP technique is an available solution in hard-to-reach areas where GCPs cannot be installed and require a GNSS infrastructure such as RTK/PPK. A dependable communications infrastructure is necessary for transmitting data to the rover's receiver; therefore, it makes the RTK approach challenging to utilize in places with insufficient communication, such as the polar areas [11]. The long convergence time has restricted the worldwide application of traditional PPP based on an ionosphere-free combination of dual-frequency observations [12]. The further shortcoming is that the large noise in the east component is probably a result of integer phase uncertainties that cannot be resolved for the PPP technique [13].