283 
5. CONCLUSIONS 
The paper takes the Beijing-1 small satellite image of Taian, 
Shandong as an example, performs the orthorectification 
experiment with traditional first-order RFM and fined RFM, 
and verifies the positioning accuracy of the orthographic image 
by independent CKPs. 
Building RFM through RPC can achieve relatively ideal 
positioning accuracy compared to linear equation and 
polynomial transform. Especially, the refined second-order 
RFM is more accurate with nearly a sub-pixel positioning 
accuracy that is close to the accuracy of the rigorous sensor 
model based on the collinearity equation. When there is serious 
shortage of control points and small terrain undulation, it can be 
considered using first-order RFM to rectify and achieve 
relatively ideal accuracy with a few control points. However, 
when the number of CKPs is not enough and the height change 
is large, the refined RFM should be proposed, for adding a 
small amount of GCPs can obviously improve the positioning 
accuracy. The experiment proved the residual errors sharply 
reduced in the size and distributed still more evenly in direction. 
The refined RPM thus may be suitable for Beijing-1 small 
satellite orthorectification 
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ACKNOWLEDGMENTS 
Special thanks Beijing Landview Mapping Information 
Technology Co.Ltd. for sponsoring Beijing-1 image.