## 5 Discussion
Differently from the Pegasus, which maintains good performance in both relative and absolute error cases, performance degradation of the low-cost system of Section 4 is significant when going from local to map coordinates (e.g., from relative (RMS = 6.1 cm) to absolute errors (RMS = 50.3 cm)). Two main factors cause such significant performance degradation: estimation error of GNSS point in \(\Sigma_{uwb}\) coordinates and the assessment of \(\Sigma_{uwb}\) orientation with respect to the georeferenced coordinate system. The first error is actually caused by the positioning estimation error of the UWB system, whereas the second is mostly due to IMU measurement errors and to calibration errors of the camera-UWB prover system. The following observations are now in order:  
* The obtained results show that both the mobile mapping systems (Leica Pegasus and UWB-based photogrammetry) allowed producing accurate 3D models in the relative error case, with quite comparable accuracy. * Absolute accuracy (map coordinates) showed an apparent difference between the two portable systems (partially motivated by the use of a better IMU in the Leica Pegasus backpack with respect to the photogrammetric system proposed in this paper). * Results shown in this paper confirm the nominal characteristics of the Leica Pegasus backpack, as listed in its specifications [15]. * Given its acceptable weight and quite good portability, the Leica Pegasus backpack is a very good candidate to produce accurate 3D models in areas where the GNSS signal is not available or hard to reach with other instruments (the weight of Leica ScanStation C10 is similar to the Pegasus one; however, the Pegasus backpack is easier to carry by a human operator in certain difficult environments). * Given the great portability of a standard camera and of Pozyx devices, which are small (the maximum side size is 6 cm) and lightweight (12 g, approximately), the proposed system is particularly well suited for mobile mapping applications where instruments have to be carried for long periods by human operators. * In this paper, UWB self-positioning was performed assuming that anchors were distributed on a 2D planar surface. Future investigation will extend UWB self-positioning to more general cases. * Comparison of Figure 6a,b shows that the proposed UWB self-positioning procedure led to quite significant errors on certain estimated anchor positions. This had a relatively small effect on the scale estimation error; however, it negatively influenced the north-vertical direction estimation used for georeferencing (comparison between Case (E) and (G) in Table 4). * Calibration errors of the camera-UWB rover system affect the performance of the photogrammetric system in the georeferenced case. Improvements shall be investigated, in particular to improve the relative orientation estimation. * The synchronization procedure between camera and UWB acquisitions, presented in Section 4, is clearly subject to estimation errors. A more robust synchronization shall be considered to improve the results. * Further future investigations will be dedicated to the reduction of photogrammetric error in the georeferenced case. Possible viable solutions that will be investigated are: including outdoor area in the photogrammetric reconstruction in order to make estimates of GNSS positions in the reconstruction more reliable, increasing the number of outdoor UWB anchors and/or GNSS points used for georeferencing the 3D model. * Both Leica Pegasus backpack and the photogrammetric system presented in Section 4 allowed for significantly reducing the survey duration with respect to TLS. Most of the time of the backpack survey was spent on calibrating the backpack's sensors, whereas data acquisition was very fast (a few minutes). The time to set up the UWB system was relatively fast (a few minutes), but image acquisition for photogrammetric reconstruction was longer than the backpack's data acquisition.