Maximum-likelihood estimation for multi-aspect multi-baseline SAR interferometry of urban areas
Maximum-likelihood estimation for multi-aspect multi-baseline SAR interferometry of urban areas
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DOI：
10.1016/j.isprsjprs.2013.10.006
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发表时间：
2014
影响因子：
12.7
通讯作者：
M. Schmitt;Uwe Stilla
中科院分区：
文献类型：
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作者：
M. Schmitt;Uwe Stilla
利用干涉合成孔径雷达（SAR）数据重建城市地区的数字地表模型（DSM）是一项具有挑战性的任务。特别是合成孔径雷达固有的停留和阴影效应，需要应付复杂的处理策略。本文提出了一种从多方位多基线干涉合成孔径雷达图像重建DSM的最大似然估计方法。在这个框架中，冗余以及矛盾的意见，利用统计上最佳的方式。所提出的方法，这是特别适合于单通SAR干涉仪，使用由实验机载毫米波SAR图像的测试数据进行检查。可实现的精度进行评估，通过比较激光雷达衍生的参考数据。结果表明，所提出的估计过程比可比的非统计重建方法更好。
The reconstruction of digital surface models (DSMs) of urban areas from interferometric synthetic aperture radar (SAR) data is a challenging task. In particular the SAR inherent layover and shadowing effects need to be coped with by sophisticated processing strategies. In this paper, a maximum-likelihood estimation procedure for the reconstruction of DSMs from multi-aspect multi-baseline InSAR imagery is proposed. In this framework, redundant as well as contradicting observations are exploited in a statistically optimal way. The presented method, which is especially suited for single-pass SAR interferometers, is examined using test data consisting of experimental airborne millimeterwave SAR imagery. The achievable accuracy is evaluated by comparison to LiDAR-derived reference data. It is shown that the proposed estimation procedure performs better than a comparable non-statistical reconstruction method.