COMBINED ADJUSTMENT OFALOS SARAND OPTICAL IMAGES FOR 3D OBJECT POSITIONING

摘要

Orientation modeling for satellite images is an important task for 3D positioning. Synthetic Aperture Radar (SAR) and optical images are two major sources in environment remote sensing. Optical imagery has good spatial resolution, and is easy for human beings to interpret. However, optical imagery has the limitation in weather conditions. SAR imagery takes the advantages of all-weather and day-and-night capabilities to detect object information in microwave bands. Thus, the integration of these two datasets can help us to obtain more useful information. Geometrically, Rational Function Model (RFM) has advantages of standardization for satellites 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) generation of Rational Polynomial Coefficients (RPCs) for SAR imagery (2) RPCs refinement for SAR and optical imagery (3) 3D object positioning, and (4) validation. Most high-resolution optical satellite companies provide the imagery with RPCs instead of the ephemeris data, but SAR satellite companies do by contraries. Thus, the generation of RPCs for RFM starts from radar back projection in the first step. Then we employ the ground control points to adjust the RPCs 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. This study tests ALOS images including PALSAR and PRISM. The experiment results show that using RFM can successfully integrate SAR and optical images to determine 3D coordinates for objects.