## 4 Photogrammetric Reconstruction with the UWB Positioning System  
This section considers an alternative 3D model of the bastion relying on the use of a very low-cost system with respect to those of Sections 2 and 3. The proposed system is based on photogrammetric reconstruction, obtained with a standard consumer camera and Agisoft PhotoScan [30]. Then, metric reconstruction is achieved by integrating the photo-based 3D reconstruction with measurements of the Pozyx UWB positioning system [24]. Finally, a Topcon HiPer V GNSS receiver is used for georeferencing the 3D model. The rationale of this system is to produce a georeferenced 3D model \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Average Error (cm)** & **RMS (cm)** & **Maximum Error (cm)** \\ \hline relative error & 4.3 & 8.2 & 193.4 \\ relative error (without left wing) & 3.6 & 4.6 & 79.3 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Leica Pegasus 3D model accuracy assessment: relative error with respect to the TLS 3D model. Figure 5: Leica Pegasus 3D model accuracy assessment: comparison with the TLS 3D model. Comparison of georeferenced point clouds (WGS84 UTM32). (**a**) Map of point-to-point distances. (**b**) Histogram of distances shown in (**a**). \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Average Error (cm)** & **RMS (cm)** & **Maximum Error (cm)** \\ \hline absolute error & 12.8 & 16.1 & 139.3 \\ absolute error (without left wing) & 11.7 & 14.4 & 67.8 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Leica Pegasus 3D model accuracy assessment: absolute error with respect to TLS 3D model. avoiding the need for CPs inside of the bastion, where GNSS positioning is not reliable, and using low-cost and easily portable instruments. Data acquisition in the bastion was carried out on 25 July 2017. Images have been taken by using a Canon G7X camera (20.2 MPix), with settings fixed at constant values (1/60-s shutter speed, f/1.8 aperture, 8.8-mm focal length, i.e., 35 mm equivalent: 24 mm). Five hundred and seven images have been collected in approximately one hour varying camera position and orientation. Portable spotlights were used in order to properly illuminate the bastion during image acquisitions. Agisoft PhotoScan performed reconstruction with camera self-calibration: images were aligned with the highest accuracy setting, leading to an RMS reprojection error of 1.24 pixel, whereas high quality and mild depth filtering were set in the dense point cloud generation, resulting in a model with 190 million points. The average number of images used to reconstruct a single point was 5.3. Clear outliers have been manually deleted from the generated point cloud by means of CloudCompare, and the point cloud has been downsampled to a resolution similar to Pegasus point cloud, i.e., 27 millions of points. Let \(\Sigma_{photo}\) be the coordinate system associated with the 3D model provided by PhotoScan. A proper transformation (i.e., scaling factor, translation and rotation) was estimated as described in the following in order to map \(\Sigma_{photo}\) into the global reference system \(\Sigma_{geo}\) (i.e., WGS84 UTM32). Since the GNSS signal was not available/reliable inside of the bastion, local positioning was obtained by using an UWB positioning system. In such a system, each device is a radio transmitter and receiver that provides ranging measurements once connected to another UWB device. Ranging is usually obtained by the time of flight of the radio signal, even if this clearly causes a decrease of ranging accuracy when devices are not in a clear line of sight (i.e., when obstacles are along the line connecting the two devices). A set of UWB devices, named anchors, are fixed to constant positions. Then, the UWB rover position is obtained by trilateration of range measurements provided by UWB anchors. A more detailed description of the Pozyx system used can be found in [8; 24].