Stereo radargrammetry using airborne SAR images with parameter optimization

Elevation measurement using Synthetic Aperture Radar (SAR) is one of crucial applications in remote sensing, since the use of SAR in elevation measurement makes it possible to measure a wide range of planar area. Most of conventional methods need Ground Control Points (GCPs) to achieve accurate 3D measurement, where GCP acquisition is a time-consuming and cost-intensive task. Addressing the above problem, this paper proposes a stereo radargrammetry method using airborne SAR images without GCP. We define a new sensor model with only parameters provided in the SAR image acquisition process which derives from the principle of stereo vision. We employ bundle adjustment so as to minimize reprojection errors in 3D measurement, since the proposed sensor model is based on stereo vision. We also employ Phase-Only Correlation (POC), which is a sub-pixel image matching method using phase information obtained by Discrete Fourier Transform (DFT) of given images, to obtain dense and accurate correspondence between two SAR images. Through an experiment using SAR images, we demonstrate that the proposed method using only online parameters exhibits efficient performance of radargrammetry compared with Interferommetric SAR (InSAR).