# UAV-Borne Profiling Radar for Forest Research
## 3 Field Test
### Comparison of Tomoradar Results with ALS Data  
Since Tomoradar has no scanning mechanics, its FOV of 6 degrees is determined by the 3 dB beamwidth of the antenna. The ALS scanning angle is substantially wider. To compare the Tomoradar measurement with the ALS data, the tree canopy detected by Tomoradar should be compared with its counterpart in the ALS data. This type of registration problem can be resolved using the global coordinate measurements of the georeferencing system. Figure 11 illustrates and explains how to resolve the problem. In the figure, the helicopter's trajectory during the test is presented as red solid line, which was measured using the georeferencing system with an accuracy better than 3 cm. The position of the tree was determined using a ground survey by total stations, whereby the position accuracy was better than 10 cm. The trees within the 6 degrees of the Tomoradar beamwidth footprint are represented as green asterisk marks in the picture, which of course can also be probed using the ALS system. The blue asterisk marks represent the trees that are only visible in ALS. Since the instant FOV of the ALS is 0.3 mRad, the ALS footprint is substantially smaller than that of Tomoradar (0.03 m for ALS vs. 10.5 m for Tomoradar at 100 m altitude). The point cloud collected by ALS cannot be directly compared with the Tomoradar results. Thus, we propose an indirect method by generating a similar \"IF spectrum\" using the ALS point cloud. If the flight altitude and DEM of the survey plot are known, the Tomoradar footprint can be calculated, the coordinates of the footprint cone can be determined, the ALS point cloud within the footprint cone can be selected and the height histogram of the ALS point cloud from the same observed area can be generated as radar data. In certain cases, normalization is required. Figure 12 compares the radar-like results from Tomoradar and ALS. Since ALS and Tomoradar operate on different bands (i.e., ALS on near infrared) and Tomoradar on the Ku-band (14 GHz)), the results should not be identical but comparable because of the different physical nature of the sensing technologies. Because the incidence angle is 0 degrees, we only selected one cross-polarization and one co-polarization channel for the analysis. In Figure 12, we can observe a clear, dense canopy in the upper-right section of the tree canopy in three outputs, and the topography of the tree canopy in the upper layer is similar in the three outputs. The intensity of the cross-polarization results is lower than that of the co-polarization results for same target. After range calibration, the canopy height extracted from the Tomoradar results is comparable with that of ALS. However, in the Tomoradar data, more detailed structures under the canopy are disclosed than in the ALS data due to Tomoradar's penetration capability. After geocoding the Tomoradar and ALS measurements in Evo test field, some qualitative results could be observed (and example plot in visualized in Figure 13):  
Figure 11: Tree positions at the Evo site observed by Tomoradar and ALS. 1. The tree top of Tomoradar data (light blue on the top) is lower than the tree top of ALS measurement. The major reason is the better penetration of Ku-band signal into forests. The larger FOV of Tomoradar also affects the analysis. The numerical values are analysed in more details in future studies. 2. The profile depth (colourful profile data within the green point cloud generated by ALS) of Tomoradar on canopy part is proportional to the canopy depth of the ALS measurement. 3. Combining topography information collected by laser scanner and density information unveiled by profile information archived by Tomoradar, a more composite forest model can be generated than any single sensor can output, such complex model suggests better understanding of how RF signal propagates in boreal forest, which assists the post processing research of SAR signal.