# Surface Correlation-Based Fingerprinting Method Using LTE Signal for Localization in Urban Canyon
## 5 Conclusions  
Accurate localization in urban areas still is a challenging task even with GNSS. In this paper, we proposed a surface correlation based fingerprinting method using LTE signals in urban areas. The surface correlation method compares the spatial RSS pattern of the pedestrian movement with a fingerprinting database. For this comparison of patterns, it generates a reference trajectory from the fingerprinting database that matches the walking path of a pedestrian. Accuracy and stability of the localization performance can be improved through the comparison between the RSS patterns. Moreover, the proposed method provides spatial discrimination for a signal of very low strength, so the scope of applying localization is very wide. The test results show that the performance, measured in terms of accuracy, stability, and robustness, of the proposed method is similar or better than that of  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Scenario** & **GPS** & **kNN** & **PF** & **SC** \\ \hline \multirow{2}{*}{1} & 10.15 m (50\%) & 15.47 m (50\%) & 11.93 m (50\%) & 3.42 m (50\%) \\  & 13.99 m (80\%) & 46.53 m (80\%) & 30.7 m (80\%) & 7.19 m (80\%) \\ \hline \multirow{2}{*}{2} & 11.69 m (50\%) & 44.99 m (50\%) & 25.98 m (50\%) & 8.59 m (50\%) \\  & 15.73 m (80\%) & 62.63 m (80\%) & 38.26 m (80\%) & 13.28 m (80\%) \\ \hline \hline \end{tabular}
\end{table}
Table 1: Comparison of the performance.  
Figure 19: Scenario 2 test results: (**a**) GPS; (**b**) Conventional fingerprinting (kNN); (**c**) Particle Filter with PDR; (**d**) SC.  
Figure 20: Localization error on test scenario 2: (**a**) Localization error according to the walking distance; (**b**) CDF of the localization error.  
GPS even in the narrow alleys of an urban area. Additionally, it is expected that its combination with GNSS will make it more seamless and make accurate localization possible in urban areas. The surface correlation method is applicable not only to LTE, but also to most RF signals that can be measured in signal strength such as Wi-Fi, Bluetooth, and 5G; hence, it can be applied not only to urban areas but also to various environments, such as underground or indoors.  
This work was undertaken with collaboration among all authors. [PERSON], [PERSON], [PERSON], and [PERSON] designed the proposed method. [PERSON] and [PERSON] performed the tests and analyzed the test results. [PERSON] and [PERSON] drafted the manuscript. [PERSON], and [PERSON] corrected the whole manuscript. All authors contributed and improved the manuscript. This research was supported by the KIST Institutional Program (Project No. 2E29490). This work was partly supported by Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIT) (No. 2019-0-01401, Multi-source-based 3D Emergency LOCalization using machine learning techniques (ME LOC)). This work was partially supported by the KIST Institutional Program (No. 2V06880) and also supported by the KIST Institutional Program (No. 2E29490). The authors declare no conflict of interest.