Refinement of interferometric SAR parameters using digital terrain model as an external reference

摘要

Cross-track interferometry (CTI) for synthetic aperture radars (SARs) is a useful technique that has been widely used to retrieve a digital surface model (DSM). One aim of CTI observations is to measure the heights of objects in a target scene, and a straightforward approach for this purpose is to subtract an external reference of the digital terrain model (DTM) from the CTI DSM. On the other hand, the refinement of parameters for CTI, namely interferometric SAR (InSAR) parameters, using an external reference is often required before subtraction. To avoid undesired degradation caused by potential differences in the terrain height between the references used for subtraction and refinement, it is preferable to use a single DTM as a common reference. However, InSAR parameters cannot be refined correctly if a DTM is used as an external source for GCPs without careful considerations since a CTI DSM contains objects unlike a DTM. In this context, we propose a novel method that refines InSAR parameters based on a DTM. The features of the proposed method are that automatically extracted footprints of vertical structures are selected as ground control point (GCP) candidates and that GCPs expected to lie at the terrain level are iteratively selected by fitting the histogram of the height difference with one or two normal distributions. This enables us to refine InSAR parameters with a single CTI DSM dataset and an external DTM without any interactive operations in the process. An experiment based on a real CTI dataset for a complex scene and a laser DTM demonstrates the promising performance of the proposed method. The median and interquartile range of the height error in terrain areas for the test scene are -0.18 m and 1.81 m, respectively, which are acceptable for various applications. The degrees of improvement resulting from the use of two novel ideas in the test scene are found to be comparable. The proposed method is predicted to be effective for developed areas such as urban and residential areas owing to its inherent limitations.