# Fast Deployment of a UWB-Based IPS for Emergency Response Operations
## 5 Performance Evaluation
### Static Tag Localization
\begin{table}
\begin{tabular}{c c} \hline \hline
**UWB–PHY Parameters** & **Value** \\ \hline Channel number & 3 \\ Center frequency (\(f_{c}\)) & 4492.8 MHz \\ Bandwidth (\(BW\)) & 499.2 MHz \\ Pulse repetition frequency (PRF) & 64 MHz \\ Preamble length & 128 symbols \\ Data rate (\(r\)) & 850 kbps \\ Preamble code (\(c_{pr}\)) & 9 \\ PAC size & 8 symbols \\ Frame delimiter & Non-standard \\ PHR mode & Extended \\ CRC filter & Off \\ Transmission power & \(<\)\(-\)41.3 dBm/MHz \\ \hline
**UWB–MAC parameters** & **Value** \\ \hline Synchronization period (\(T_{s}\)) & 1.04 s \\ Number of TDMA slots (\(n_{\text{TDMA}}\)) & 10 \\ Number of node slots (\(k\)) & 6 (= number of anchors) \\ \hline
**Gauss–Newton algorithm parameters** & **Value** \\ \hline Maximum number of expected iterations (\(i_{\text{max}}\)) & 1000 \\ Targeted precision (\(\hat{p}\)) & 0.001 m \\ \hline
**Application parameters** & **Value** \\ \hline Position update period (\(T\)) & \(\sim\)2 s \\ \hline \hline \end{tabular}
\end{table} 
Table 4: UWB-based IPS parameters. A quantitative analysis of the accuracy and precision of these estimations is provided in Figure 12. The first metric of interest corresponds to the average 2D distance error in localization, which is always below 1 m, but shows a variable behavior depending on the tag's position. Apart from the aforementioned strict NLOS conditions between the tag and the available anchors, there are two other factors that explain this performance variability:  
1. **Number of detected anchors:** Similarly to satellite positioning, dilution of precision (DOP) describes the relationship between the measurement error and position determination [62]. Therefore, the more observations used (in our case, the more detected anchors), the smaller the DOP values and, hence, the smaller the solution error. 2. **Geometry delimited by detected anchors:** Another parameter, called the geometric dilution of precision (GDOP), is a dimensionless value that measures the effect of the network geometry on the positioning solution [78]. In short, if a square pyramid is formed by lines joining the anchors with the tag at the tip of the pyramid, the larger the total volume, the better the value of GDOP [79]. Consequently, a high share of aligned anchors could penalize the positioning performance. Figure 11: Statistics of computed rangings. (**a**) Received rangings. (**b**) Ranging error. (**c**) Ranging deviation. The better behavior of the IPS in some positions is likely to be caused by (1) the avoidance of the effect of the ground-floor ceiling and other structural elements such as the stairs, which hinder the UWB signal propagation, (2) the reduced number of obstacles across the UWB signal path to the anchors, and (3) the greater number of nearby available anchors, which tend to provide more accurate rangings. As for the standard deviation of the computed data, it can be observed that the localization precision is, in general, lower in positions of the first floor (with the exception of \(puntG\)). Again, the signal propagation variability introduced by the higher number of obstacles leads to a certain dispersion in the position estimation. Still, there are some exceptions, such as \(puntN\), where the localization estimations are highly precise but not that accurate (see also Figure 10b), because the average error corresponds to 0.53 m.  
In general, the obtained 2D accuracy values are not lower bounds; in fact, this metric can be improved by selecting a subset of anchors involved in the multilateration algorithm. Indeed, it is well-known that the selection of certain anchors from a whole set can affect the localization accuracy significantly [80]. While it is true that this topic falls outside of the scope of the present work, it has been largely discussed in the existing UWB literature [81; 82; 83; 84; 85] and will be the subject of most of our next research efforts.