RFM is suitable for geometric positioning with multi-source images because of the independence of sensors. However, without GCPs the geometric advantages from the geometrically prevailing images cannot be enforced in the traditional RFM-based orientation. It also leads to the apparent flaw of divergence of solving. By translating the priori information of autonomous positioning accuracy and imaging drift errors to bias compensation parameters in image space, it is rebuild a new RFM-based adjustment model which considers the accuracy and weight of the orientational parameters. A test study of positioning without GCPs which includes 12 scenes of TerraSAR-X images and 6 pairs of long-strip stereo SPOT-5 HRS images covering area of 186 000 km2 is conducted. Furthermore, the different impact factors on positioning accuracy, i.e., the accuracy of orientation parameters, the number of SAR image, orbit direction of SAR satellite and distribution of SAR images, are investigated. The results show that it can achieve positioning accuracy of 6.0 m in plan and 4.2 m in height for the case of geometrical combination of TerraSAR-X and HRS images. The proposed model is superior to the traditional RFM-based positioning with respect to accuracy and resolving stability. It is a potential approach for worldwide mapping at scale of 1:100 000 and 1:50 000 without GCPs by combination of different satellite images.
CHENG Chunquan
,
ZHANG Jixian
,
HUANG Guoman
,
ZHANG Li
,
YANG Jinghui
. Combined Positioning of TerraSAR-X and SPOT-5 HRS Images with RFM Considering Accuracy Information of Orientation Parameters[J]. Acta Geodaetica et Cartographica Sinica, 2017
, 46(2)
: 179
-187
.
DOI: 10.11947/j.AGCS.2017.20160138
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