Results 121 to 130 of about 1,079 (177)

TomoSAR from Theory to Practice – Overview of the Advancements and Challenges

IGARSS 2025 - 2025 IEEE International Geoscience and Remote Sensing Symposium
Synthetic Aperture Radar Tomography (TomoSAR) is a transformative technique for multi-dimensional imaging, enabling detailed analysis of complex environments. This paper provides an overview of TomoSAR, exploring its technological advancements and the practical challenges.
Aghababaei, Hossein, Ferraioli, Giampaolo   +1 more
openaire   +3 more sources

Adaptive quality indicator for subband multi-baseline TomoSAR filter

International Journal of Remote Sensing
The development of Synthetic Aperture Radar (SAR) techniques has been ongoing for a few decades due to the continuous expansion of SAR technologies. However, the source of decorrelations among other noise artefacts constitutes one of the main limitations to all interferometric-based processes including Tomography (TomoSAR).
Hocine, Faiza, Hadj-Rabah, Karima, Budillon, Alessandra, Schirinzi, Gilda, Daoud, Ishak   +4 more
openaire   +2 more sources

Unsupervised TomoSAR Image Reconstruction Through Virtual Multiple Measurement Explorations

2025 IEEE Radar Conference (RadarConf25)
Tomographic synthetic aperture radar (TomoSAR) reconstruction produces 3D imaging of scenes from measurements and has recently been combined with data-driven deep learning techniques.
Liang Liu, Tianjiao Zeng, Mou Wang, Jun Shi, Shunjun Wei, Xiaoling Zhang, Xu Zhan   +6 more
openaire   +2 more sources

Plug-And-Play TomoSAR Imaging With Prior Information

IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium
Synthetic aperture radar (SAR) tomography (TomoSAR) is an advanced remote sensing technology that has the ability to acquire three-dimensional information of targets.
Kun Wang, Jie Li, Yizhe Fan, Bingchen Zhang   +3 more
openaire   +2 more sources

Spaceborne L-Band Forest Tomosar: A First Case Study

IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium
In this work we present a first spaceborne L-band forest SAR Tomography (TomoSAR). We process a stack of 9 real SAOCOM acquisitions over Amazonas, a scenario mostly consisting of tropical rainforest with average tree height of about 25 m to 35 m.
Francesco Banda, Naomi Petrushevsky, Stefano Tebaldini, Andrea Monti-Guarnieri   +3 more
openaire   +2 more sources

Model-based polarimetric scattering decomposition for TomoSAR

2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2017
SAR Tomography, or TomoSAR, is one of the powerful SAR data analysis tool with multi-baseline data set, especially for height estimation of scattering centers. On the other hand, PolSAR, or Polarimetric SAR, is also powerful tool for scattering characteristic discrimination of terrain. Several PolSAR analyses have applied to the TomoSAR.
Hiroyoshi Yamada, Masanori Gocho, Motofumi Arii, Shoichiro Kojima, Ryoichi Sato, Yoshio Yamaguchi   +5 more
openaire   +1 more source

TomoSAR Application for Early Warning in Infrastructure Health Monitoring

IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019
Earth observation using spaceborne sensors with short revisiting time has forgone the limits of conventional assessment methods. In this paper, we investigate the use of SAR Tomography (TomoSAR) to monitor infrastructures, using Morandi Bridge in Genoa, Italy, as a case study.
Budillon, A, Ferraioli, G, Johnsy, AC, Pascazio, V, Schirinzi, G   +4 more
openaire   +2 more sources

Exploring Spatial Feature Regularization in Deep-Learning-Based TomoSAR Reconstruction: A Preliminary Study and Performance Analysis

IEEE Transactions on Geoscience and Remote Sensing
Tomographic synthetic aperture radar (TomoSAR) shows great potential for high-quality 3-D mapping, especially in urban areas. As TomoSAR reconstruction methods advance into the deep learning (DL) era, current studies have demonstrated DL’s strengths in ...
Tianjiao Zeng, Xu Zhan, Yu Ren, Xiangdong Ma, Liang Liu, Jun Shi, Shunjun Wei, Mou Wang, Xiaoling Zhang   +8 more
semanticscholar   +1 more source

Robust TomoSAR focusing for forest height retrieval

2018 IEEE International Conference on Environmental Engineering (EE), 2018
This paper aims to discuss and present analysis on robust reconstruction of vertical structure of forested area suing multi-baseline synthetic aperture radar (SAR) data. To deal with problem of low signal to noise (SNR) ratio, robust non-local (NL) techniques of covariance matrix estimation are employed and compared with classical multi-looking ...
Aghababaee, Hossein, Ferraioli, Giampaolo, Pascazio, Vito, Schirinzi, Gilda   +3 more
openaire   +2 more sources

L1/2-Norm Regularization Outlier Removal and Moving Least Squares-Based TomoSAR Point Cloud Optimization of Mountain Areas

IEEE Geoscience and Remote Sensing Letters
Tomographic synthetic aperture radar (TomoSAR) enables high-resolution 3-D reconstruction of mountainous terrain, but TomoSAR point clouds often suffer from outliers and height errors due to estimation noise and geometric distortions.
Jingjing Zhang, Qi Guo, Shuang Jin, L. Pang, Feng Yang, Hui Bi   +5 more
semanticscholar   +1 more source