# Cloud-Based Single-Frequency Snapshot RTK Positioning
## 1 Introduction
It also evaluates the performance of SRTK in terms of Integer Ambiguity Resolution (IAR) and final positioning accuracy. Particularly, the experiments described in this paper consider different baseline distances of up to 50 km instead of the zero-baseline case considered before in [12]. In addition, since collecting snapshot data from multiple frequency bands will increase the total snapshot size, only single frequency data are used in the present research, confirming that single frequency processing is sufficient to obtain a high fix rate for most of the scenarios discussed in Section 3. With SRTK, applications requiring high-precision, such as Connected and Automated Vehicles (CAV) [13], geodetic measuring, or deformation monitoring of critical infrastructures, can benefit from snapshot-based positioning as well. From a commercial point of view, one of the major costs of adopting the SRTK service comes from the transmission of raw GNSS data from the user end to the remote cloud platform. The mobile network data plan chosen for this service will depend on the minimum size of the data packet needed for each snapshot. The smaller the snapshot, the cheaper this service can be. This work mainly aims to explore the minimum data size of a snapshot required for obtaining a given IAR fix rate. The snapshot size depends on the data quantization, the sampling rate, and duration of the data collection configured in the GNSS front-end. The sampling rate directly influences the maximum bandwidth of the signal, and the duration of the data limits the total integration time available for satellite acquisition. Those constraints further influence the noise level of generated GNSS observables, which in the end determines the IAR fix rates. Furthermore, the baseline distance between the user end and the GNSS reference station also largely impacts the feasibility of achieving IAR. Different experiments are organized in this paper to explore the performance differences brought by these factors. From a technical perspective, this work mainly addresses innovations and improvements in the following three aspects:* The first contribution of this work is the development of a novel algorithm that ensures a nanosecond level absolute timing accuracy so that satellite positions can be computed with a much higher accuracy as well. * The present research also addresses the problems brought by the lack of knowledge of the encoded navigation data bits, noted as the data bit ambiguity issue in this manuscript. This issue impacts the fractional carrier phase measurements and determines the possibility of obtaining an SRTK fixed solution, a method is proposed in this work to tackle this issue. * The two previous innovations, as well as an improved data processing workflow of the novel SRTK algorithm, builds on top of our previous work [12]. To the best of our knowledge, this is the first time that snapshot signals have been used to generate RTK fixed solutions under a non-zero baseline configuration. The present research highlights the following two benefits for the GNSS industry. On the one hand, it provides a clear view of the relationships between the snapshot receiver settings and the expected positioning performance, which could be critical when deciding which parameters to use in order to reduce size of snapshot data and its transmission cost. On the other hand, the baseline distance analysis also brings useful insights for service providers, especially about the GNSS base station network density before the deployment.