基于多主影像TomoSAR的高质量大规模三维城市测绘
High Quality Large-Scale 3-D Urban Mapping with Multi-Master TomoSAR
AI总结：
针对TanDEM-X数据采集少的问题，提出集成非局部滤波的SAR层析成像框架，实现大规模三维城市测绘，精度优于原始DEM。
摘要：
多基线干涉合成孔径雷达（InSAR）技术是获取城市区域三维信息的有效方法。为了获得合理的重建结果，需要使用大堆栈干涉图。因此，这些方法通常不适用于利用TanDEM-X数据进行的大规模三维城市测绘，因为每个城市平均只有少量采集。本文提出了一种新的SAR层析成像处理框架，用于处理这些极小堆栈，该框架将非局部滤波集成到SAR层析成像反演中。利用覆盖德国慕尼黑全城的5幅双基干涉图的TanDEM-X多基线堆栈，验证了该算法的适用性。与机载LiDAR数据的系统比较表明，三分之二建筑物的相对高度精度在2米以内，优于TanDEM-X原始DEM。该算法表现出的良好性能为高质量大规模三维城市测绘迈出了第一步。
英文摘要：
Multi-baseline interferometric synthetic aperture radar (InSAR) techniques are effective approaches for retrieving the 3-D information of urban areas. In order to obtain a plausible reconstruction, it is necessary to use large-stack interferograms. Hence, these methods are commonly not appropriate 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 work with those extremely small stacks, which integrates the non-local filtering into SAR tomography inversion. The applicability of the algorithm is demonstrated using a TanDEM-X multi-baseline stack with 5 bistatic interferograms over the whole city of Munich, Germany. Systematic comparison of our result with airborne LiDAR data shows that the relative height accuracy of two third buildings is within 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.
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