@inproceedings{3ec9b2ba5aba411c9e1c4dbee3921240,
title = "Non-Local SAR Tomography for Large-Scale Urban Mapping",
abstract = "Multi-baseline synthetic aperture radar (SAR) interferometric techniques, such as SAR tomography, is well established for 3-D reconstruction in the urban area. These methods usually require fairly large interferometric stacks (> 20 images) for a reliable reconstruction. Hence, they are usually not directly applicable for large-scale 3-D urban mapping using TanDEM-X data where only a few acquisitions are available in average for each city. This work proposes a new SAR tomographic processing framework to those extremely small stacks. The applicability of the algorithm is demonstrated using a TanDEM-X multi-baseline stack with five bistatic interferograms over the whole city of Munich, Germany. Systematic comparison of our result with TanDEM-X raw digital elevation models (DEM) and airborne LiDAR data shows that the relative height accuracy is two meters, which outperforms the TanDEM-X raw DEM. The promising performance of the proposed algorithm paved the first step towards high quality large-scale 3-D urban mapping.",
keywords = "Non-Local filtering, Robust estimator, TomoSAR",
author = "Yilei Shi and Yuanyuan Wang and Zhu, {Xiao Xiang} and Richard Bamler",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 ; Conference date: 28-07-2019 Through 02-08-2019",
year = "2019",
month = jul,
doi = "10.1109/IGARSS.2019.8897890",
language = "English",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "5197--5200",
booktitle = "2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Proceedings",
}