# Performance Evaluation of GPS Auto-Surveying Techniques
## 4 Discussion  
To characterize the performance of several methods for the auto-survey procedure of a GNSS base station, the LS, WLS, EKF, and UKF methods were tested using data from a 24 h survey. To enhance the results of these methods, both a carrier-smoothed code method, the Hatch Filter, and a threshold filter were also analyzed. The analysis of these results shows a very clear benefit of the EKF and UKF compared to the LS and WLS, with the UKF showing slightly better results than the EKF. From these results, the LS and WLS do not appear to be viable auto-survey methods; hence, the EKF and UKF should be used for this purpose. In addition, while the UKF shows a slightly better result than the EKF, it also has higher computational complexity due to the sampling of the sigma points and their propagation through the non-linear function. Comparisons with existing auto-survey methods show that the EKF and UKF provide significantly better results when compared to the survey-in algorithm of the u-blox 6T receiver but show a worse estimate than that of the ProFlex 500 receiver; this is to be expected, since the u-blox 6T receiver used is an low-cost, single-frequency receiver when compared to the geodetic grade, dual-frequency ProFlex 500. It should be noted, however. that the EKF and UKF mean position estimate is still very close to that of the much more expensive ProFlex 500 receiver, with both having decimeter-level accuracy. When applied to a DGPS setup, the good performance of the EKF and UKF methods for auto-survey can be seen, with the test showing estimates with error of about 1 m or less for the rover position for all auto-surveys using the UKF and slightly worse results for the EKF. These results are promising, and further research could improve them, allowing for even greater precision. Another important conclusion is that there is a precision threshold at roughly the 4 h mark, with only marginal improvements for longer surveys. This result is important for the stated applications of the presented methods, as it can be used, together with the estimate precision data, to help the intended audience of this paper guide planning and logistics for said activities to better account for the auto-survey procedure without requiring an arbitrarily long survey time. These results show that low-cost GPS base stations are achievable with inexpensive receivers and small survey windows, without requiring extensive surveys, high-end survey equipment, or other external inputs and still provide meter-level or below accuracy for rovers. This opens the possibility of creating very low-cost GPS base stations for differential positioning methods without requiring external augmentations, paving the way for the use of precise GPS position estimation in activities that cannot justify the added cost of high-precision receivers and in remote and GNSS-underserved areas at a fraction of the cost of a commercial high-end receiver. Conceptualization, J.M. and J.S. ; methodology, J.M. and J.S. ; software, J.M. ; validation, J.M. and J.S. ; formal analysis, J.M. ; investigation, J.M. ; resources, [PERSON]; data curation, [PERSON]; writing--original draft preparation, [PERSON]; writing--review and editing, [PERSON] and [PERSON]; visualization, [PERSON]; supervision, [PERSON]; project administration, [PERSON] and [PERSON]; funding acquisition, [PERSON] All authors have read and agreed to the published version of the manuscript. This research has been made possible with funding from project UIDB/50008/2020 of the Instituto de Telecomunicacoes. \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline  & \multicolumn{4}{c}{**Extended Kalman Filter**} & \multicolumn{4}{c}{**Unscented Kalman Filter**} \\ \hline
**Hours** & **4** & **8** & **12** & **16** & **20** & **24** & **4** & **8** & **12** & **16** & **20** & **24** \\ \hline Mean error (m) & 0.732 & 0.794 & 0.661 & 0.787 & 0.903 & 0.932 & 0.767 & 0.677 & 0.506 & 0.584 & 0.686 & 0.719 \\ \hline \hline \end{tabular}
\end{table}