A Modified SweepSAR Mode with Dual Channels for High Resolution and Wide Swath

In this study, an imaging mode of the modified SweepSAR is proposed with performance analysis for a high-resolution and wide swath coverage. To reduce the overall antenna size required for the solution of the azimuth ambiguity problem, different pulse repetition frequencies (PRFs) are utilized for different transmitters, respectively. For each imaging mode, system performance parameters are used for simulation, analysis, wide swath prediction, and comparison between conventional ScanSAR mode and SweepSAR mode based on scan-on-receive (SCORE). The system parameters of AASR, RASR, and NESZ will be estimated and suggested on the imaging mode by using appropriate reflector antenna with the effectiveness of a modified SweepSAR employing dual channels

Motion Compensation for Near-Range Synthetic Aperture Radar Applications

The work focuses on the analysis of influences of motion errors on near-range SAR applications and design of specific motion measuring and compensation algorithms. First, a novel metric to determine the optimum antenna beamwidth is proposed. Then, a comprehensive investigation of influences of motion errors on the SAR image is provided. On this ground, new algorithms for motion measuring and compensation using low cost inertial measurement units (IMU) are developed and successfully demonstrated

小型衛星搭載の合成開口レーダー用の集中型送受信システムを有する２偏波対応進行波型アンテナ

学位の種別: 課程博士審査委員会委員 : （主査）東京大学教授 齋藤 宏文, 東京大学教授 橋本 樹明, 東京大学教授 保立 和夫, 東京電機大学教授 小林 岳彦, 東京工業大学教授 廣川 二郎University of Tokyo(東京大学

Growing stock volume estimation in temperate forsted areas using a fusion approach with SAR Satellites Imagery

Forest monitoring plays a central role in the context of global warming mitigation and in the assessment of forest resources. To meet these challenges, significant efforts have been made by scientists to develop new feasible remote sensing techniques for the retrieval of forest parameters. However, much work remains to be done in this area, in particular in establishing global assessments of forest biomass. In this context, this Ph.D. Thesis presents a complete methodology for estimating Growing Stock Volume (GSV) in temperate forested areas using a fusion approach based on Synthetic-Aperture Radar (SAR) satellite imagery. The investigations which were performed focused on the Thuringian Forest, which is located in Central Germany. The satellite data used are composed of an extensive set of L-band (ALOS PALSAR) and X-band (TerraSAR-X, TanDEM-X, Cosmo-SkyMed) images, which were acquired in various sensor configurations (acquisition modes, polarisations, incidence angles). The available ground data consists of a forest inventory delivered by the local forest offices. Weather measurements and a LiDAR DEM complete the datasets. The research showed that together with the topography, the forest structure and weather conditions generally limited the sensitivity of the SAR signal to GSV. The best correlations were obtained with ALOS PALSAR (R2 = 0.61) and TanDEM-X (R2 = 0.72) interferometric coherences. These datasets were chosen for the retrieval of GSV in the Thuringian Forest and led with regressions to an root-mean-square error (RMSE) in the range of 100─200 m3ha-1. As a final achievement of this thesis, a methodology for combining the SAR information was developed. Assuming that there are sufficient and adequate remote sensing data, the proposed fusion approach may increase the biomass maps accuracy, their spatial extension and their updated frequency. These characteristics are essential for the future derivation of accurate, global and robust forest biomass maps