| Summary: | 碩士 === 國立中央大學 === 土木工程研究所 === 100 === Synthetic Aperture Radar (SAR) and optical images are two major data sources in environment remote sensing. The integration of these two datasets can help us to obtain more object information. From geometric point of view, these two types of data may be combined for 3D positioning. Orientation modeling for satellite images is an important task for 3D positioning. To link an image point with its counterpart on the ground, Rational Function Model (RFM) has advantages of standardization for satellite image processing and is easy to implement. Thus, we use RFM to integrate SAR and optical sensor orientation data for 3D positioning.
There are four steps in this study: (1) establishment of geometric model, (2) generation of Rational Polynomial Coefficients (RPCs), (3) RFM refinement, and (4) 3D object positioning. A part of high-resolution optical satellite companies and most SAR satellite image providers only distribute the imagery with ephemeris data. Thus the establishment of geometric model for optical and SAR sensors is the first step. Then, the generation of RPCs for RFM starts from geometric model. Then we employ the ground control points to adjust the RFM for two sensor images. For a pair of conjugate points in SAR and optical images, we have four equations to determine the 3D object coordinates. The experiments include three parts: (1) model error analysis for SAR satellite images, (2) validation for 3D positioning, and (3) geometric simulation. Experimental results showed that the integration of SAR and optical images can achieve 3D object positioning.
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