A multiangle image aggregation analysis and association algorithm for GNSS-based InSAR

• Published in: Remote sensing letters Vol. 14; no. 4; pp. 402 - 412
• Main Authors: Wang, Zhanze, Liu, Feifeng, Shang, Runze, Zhang, Shuyao
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis 03.04.2023; Taylor & Francis Ltd
• Subjects: 3D deformation retrieval; Agglomeration; Aggregation; aggregation analysis; Algorithms; Analysis; Deformation; elevation error compensation; Global navigation satellite system; GNSS-based InSAR; Image processing; Interferometric synthetic aperture radar; Interferometry; multiangle association; Navigation; Navigational satellites; SAR (radar); satellites; synthetic aperture radar; Texture
• ISSN: 2150-704X; 2150-7058; 2150-7058
• DOI: 10.1080/2150704X.2023.2204410

In the global navigation satellite system-based synthetic aperture radar interferometry (GNSS-based InSAR) system, 3D deformation retrieval needs to associate multiangle images, but due to the low 2D resolution, traditional texture-based algorithm cannot be used in GNSS-based system. At the same time the association error introduced by the elevation error also cannot be compensated for. In this paper, a multiangle images aggregation analysis and association algorithm is proposed under elevation error conditions. Instead of using texture information, focus positions from different angles are adopted here. First, the focus position with elevation error is modelled in the bistatic configuration. Then, the images association is achieved based on the aggregation analysis, which is further quantitatively expressed through minimum circle principle. Raw data from four satellites are used to demonstrate the validity of the proposed algorithm.