The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part Bl. Beijing 2008 
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Figure 9 shows the discrepancies between the true bore-sighting parameters recovered using different three approaches are very 
parameters and recovered ones. As it can be seen in these two small, and it can be ignored. The simulation data is relatively 
figures, if the slope of the planes is very small (e.g., less than 10 ideal compared to the real data. Anyway, the ultimate goal of 
degree), the planar patches are almost parallel, and the RMSE the calibration test using simulation data is to confirm the 
of the reconstructed coordinates of LiDAR points are very high. feasibility of the methods and detect any possible drawbacks. 
It is also seen that for such a case, the derived bore-sighting The next, the author introduces the experiment results from real 
parameters are not close to the true parameters. Therefore, it is airborne and terrestrial LiDAR data. The results are relatively 
recommended that some of the control patches should have worse than the simulation test, because the quality of this real 
slopes that exceed 10 degrees. Moreover, the patches should data is not guaranteed. Especially, the terrestrial data has some 
have different orientation in space (i.e., different aspect angles). drift errors in INS navigation data; there was, however, no 
available other terrestrial LiDAR data. 
Figure 8. Slope of planar patches and accuracies of 
reconstructed surface 
_ [meter] 
parameters [bore-sight spatial offsets] 
GiZ 
J j J ■ J 
(a) 
n 
2D 
SD 
10 D ZJD 300 <00 SOD 
Sto pe[ degl 
90D 
— 
0 
1 
I 
1 
i 
I 
3 
! 
1 
1 
parameters [bore-sight rotational offsets] 
mar 
nl 
n_- n m mi n_B [La 
n_@ 
ID 
5D 
10D 23 D 330 <0D 90.0 
Slooefdeql 
Figure 9. Differences between the true and estimated bore 
sighting parameters 
3. EXPERIMENTS 
In the first test, virtual LiDAR data was simulated and used to 
confirm the feasibility of the proposed methods. For the test 
data, airborne and terrestrial LiDAR systems are considered in 
an urban area. The airborne system flew over the area at around 
90m flying height, and the terrestrial system mainly scanned 
building walls along the road. As shown in 
Figure 10, the terrestrial data consists of two strips, which are 
left and right sides of the road. 
The results from the simulation data are shown in Table 1. As a 
result, the re-covered calibration parameters are very close to 
the expected values in all of methods, and these results are good 
enough to confirm the feasibility of the proposed calibration 
methodologies in this paper. The differences between 
Figure 10. Simulated LiDAR data: (a) is airborne LiDAR data, 
and (b)&(c) are terrestrial LiDAR data. 
A X 
A Y 
A Z 
A co 
A $ 
A K 
(m) 
(m) 
(m) 
(deg) 
(deg) 
(deg) 
True 
Parameters 
0.1 
0.1 
0.1 
1.0 
1.0 
1.0 
ICP 
0.11 
0.98 
0.10 
1.00 
1.00 
1.00 
Norm[m] : 
0.050 
0 : 0.063 
ICPatch 
0.09 
0.10 
0.09 
1.01 
1.02 
0.98 
Norm[m] : 
0.054 
0 : 0.071 
Planar 
0.11 0.10 
0.10 
1.00 
1.00 
1.00 
Patches 
Norm[m] : 
0.035 
0 : 0.051 
Table 1. The LiDAR system calibration test using simulation 
data (6 bore-sighting parameters) 
Table 2 shows the description of used data; the point density of 
the terrestrial LiDAR data is about 2.7 times that of the airborne 
LiDAR data. The airborne data was captured at a 150m flying 
height from the ground-level, while the average range of the 
terrestrial data is less than 20m. 
Reference Data 
Target Data 
System Def-ID 
Titan Laser 1 
Plate# 3 
Point density 
13.5 points/m 2 
5 points/ m 2 
System Def-Time 
1-Mar, 2007 
11-Nov, 2006 
Flying height 
N/A 
150m 
Table 2. Description about test LiDAR data 
Figure 11 shows the used real data figures; (a) represents the 
terrestrial LiDAR data used as the reference surface, and (b)