## 4 Advanced Positioning Methodologies Using UWB and Wi-Fi RTT Signals
### Integrated Positioning of Data Fusion
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Year** & **Sensors** & **Fusion Category** & **Algorithm** & **Platform** & **Experiment** & **Accuracy (m)** & **Limitations** \\ \hline
2019 & IMU, Wi-Fi & Loose coupling & Enhanced particle filter & Smartphone & An office room of 11 m \(\times\) (12.4 m/ 10 m) \(\times\) 3 m & \
\begin{tabular}{c} \(<\)1 m in 86.7\% \\ of the cases \\ \end{tabular} &
\begin{tabular}{c} Large amount of \\ calculation and \\ poor stability \\ \end{tabular} \\ \hline
2019 & IMU, Wi-Fi & Loose coupling & \begin{tabular}{c} PDR and Wi-Fi \\ RTT are \\ integrated by \\ UKF \\ \end{tabular} & Smartphone & \
\begin{tabular}{c} An office room of \\ 12 m \(\times\) 12 m; A \\ shopping mall \\ \end{tabular} & \(<\)2 m &
\begin{tabular}{c} Long-term \\ localization \\ performance needs \\ to be improved \\ \end{tabular} \\ \hline
2020 & IMU, Wi-Fi & Tight coupling & Weighted least & Smartphone & An office room of 20 m \(\times\) 6 m in 80\% of the cases &
\begin{tabular}{c} The method is \\ unstable when the \\ Wi-Fi RTT \\ measurements \\ change drastically \\ caused by \\ multipath \\ \end{tabular} \\ \hline
2021 & IMU, Wi-Fi & Loose coupling & \begin{tabular}{c} A \\ fusion-tracking \\ federated filter \\ \end{tabular} & Smartphone & \begin{tabular}{c} The two areas of \\ 10 m \(\times\) 10 m and \\ 6 m \(\times\) 4 m; An \\ office room of \\ 32 m \(\times\) 21 m \\ \end{tabular} & \
\begin{tabular}{c} The two areas of \\ \(<\)1 m in about \\ 80\% of the \\ cases \\ \end{tabular} &
\begin{tabular}{c} The method is \\ unstable when the \\ Wi-Fi RTT \\ measurements \\ change drastically \\ caused by \\ multipath \\ \end{tabular} \\ \hline
2022 & IMU, Wi-Fi & Tight coupling & \begin{tabular}{c} Error-state \\ Kalman filter; \\ Rauch–Tung– \\ Striebel \\ smoothing for \\ localization \\ optimization \\ \end{tabular} & \begin{tabular}{c} An office room of \\ 5 m \(\times\) 4 m; A \\ of the \\ smartphone \\ of 13 m \\ \end{tabular} & \
\begin{tabular}{c} 1.36 m in office \\ room; 0.92 m \\ in public area \\ \end{tabular} &
\begin{tabular}{c} Unknown \\ performance in \\ large scenes \\ \end{tabular} \\ \hline
2023 & IMU, Wi-Fi & Tight coupling & \begin{tabular}{c} Adaptive \\ extended \\ Kalman filter \\ \end{tabular} & \begin{tabular}{c} Robot with \\ IMU of the \\ smartphone \\ \end{tabular} & \begin{tabular}{c} An office \\ building with \\ LOS and NLOS \\ experiments \\ \end{tabular} & \
\begin{tabular}{c} 0.8 m in 80\% of \\ LOS cases; \\ 1.04 m in 80\% \\ of NLOS cases \\ \end{tabular} &
\begin{tabular}{c} The robot speed is \\ unknown \\ unknown \\ \end{tabular} \\ \hline
2023 & IMU, Wi-Fi & Tight coupling & \begin{tabular}{c} Factor graph \\ optimization \\ \end{tabular} & Smartphone & \begin{tabular}{c} Two real areas of \\ 126 m\({}^{2}\) \\ \end{tabular} & \
\begin{tabular}{c} 0.39 m \\ 0.39 m \\ \end{tabular} &
\begin{tabular}{c} Three pre-set \\ phone modes \\ \end{tabular} \\ \hline
2024 & Wi-Fi RTT, & Loose coupling & \begin{tabular}{c} A nonparametric \\ regression \\ \end{tabular} & Smartphone & \
\begin{tabular}{c} A passage and a \\ classroom \\ environment of 112.5 m\({}^{2}\) \\ \end{tabular} &
\begin{tabular}{c} Further validation \\ of the cases \\ settings is needed \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Summary of Wi-Fi RTT-based integrated positioning studies.