The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part Bl. Beijing 2008 
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158 157 156 155 154 62 61 60 59 58 
—♦—Original data from IMU 
in Terrestrial 
Photogrammetry 
Coordinate System - 
The results calculated 
through resection 
—•—Corrected results 
computed through 
deviation angle error 
- The results 
calculated through 
resection 
Figure 4. The comparative results of Omega between the 
original attitude data and the corrected attitude data 
Original data fr»» IMU 
in T«r*stri*l 
ftiotograsatetry 
Coordinate Sfst<* " 
Ibe results calculated 
through resection 
Corrected results 
oompttted through 
deviation angle error 
~ The results 
calculated through 
resect ion 
188 1ST 18$ 188 184 $2 61 60 SS 88 
Skaloud, J., 2006. Rigorous approach to bore-sight self 
calibration in airborne laser scanning. ISPRS Journal of 
Photogrammetry & Remote Sensing, 61, pp. 47-59. 
Naci Yastikli, 2005. Direct sensor orientation for large scale 
mapping-potential problems solutions. Photogrammetric Record, 
20(111), pp. 274-284. 
Mostafa, M, 2002. Camera/IMU boresight calibration: new 
advances and performance analysis. ASPRS Meeting, 
Washington, DC. 
Pinto, L., 2002. Integrated INS/DGPS Systems: Calibration and 
combined block adjustment. OEEPE Official Publications, 43, 
pp. 85-96. 
Mohamed, M., 2001. Calibration in multi-Sensor environment. 
ION GPS, 11-14, PP. 2693-2699. 
OTTO HOFMANN, 2005. Calibration and georeference of 
aerial digital cameras. Photogrammetric Week 05’, pp. 105-109 
Pinto, L., 2005. Experimental tests on the benefits of a more 
rigorous model in IMU/GPS system calibration. ISPRS 
Commission III, WG III/1. 
Figure 5. The comparative results of Kappa between the 
original attitude data and the corrected attitude data 
Through analyzing Figure 3, Figure 4 and Figure5, we can find 
the UAV remote sensing images attitude data correction model 
proposed in this paper improves the precision of images’ 
attitude data. But the accuracy of the deviation angle error is 
affected by systematic error of GPS / IMU, such as the error of 
gyro random drift. So the systematic error correction model for 
gyro random drift will be established to obtain higher precision 
deviation angle error in the future studies. 
Skaloud, J., 2003. Towards a more rigorous boresight 
calibration. ISPRS International Workshop on Theory, 
Technical and Realities of Inertial/GPS Sensor Orientation, 
Commission 1, WGI/5, Castelldefels, Spain, 22-23. 
ACKNOWLEDGEMENTS 
This paper is sponsored by Nature Science Fund (NSF) of 
China .No. 60602042. We would like to express our gratitude to 
all the people who have participated in the UAV experiments. 
4. CONCLUSIONS 
In this paper, the error calibration model of the UAV airborne 
attitude data is established, then the model is tested through a 
set of UAV aerial remote sensing images. Experimental results 
show that the model can effectively correct the original attitude 
data acquired from the GPS/INS. Meanwhile, from the data 
analysis we can see that the accuracy of deviation angle error is 
affected by other systematic errors of the GPS / IMU, such as 
the error of gyro random drift etc. So the systematic error 
correction model for gyro random drift will be established to 
obtain higher precision deviation angle error in the future 
studies. 
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