Urban scene reconstruction from a reduced number of tomographic SAR data
Urban scene reconstruction from a reduced number of tomographic SAR data
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DOI：
10.1109/igarss.2014.6947149
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发表时间：
2014-07
期刊：
影响因子：
--
通讯作者：
S. Guillaso;O. D’Hondt;O. Hellwich
中科院分区：
文献类型：
--
作者：
S. Guillaso;O. D’Hondt;O. Hellwich
本文采用减少层析SAR数据数量的方法，对城市复杂场景进行了分析。首先，使用标准MUSIC算法对层析数据进行处理，该算法需要估计数据协方差矩阵和估计源数。引入层析双边滤波器（to - moblf）来改进协方差矩阵的估计，并提出了一种新的基于层析熵参数TomoH的模型阶数选择方案。然后利用层析信噪比（TomoSNI）算法提取感兴趣点。
This paper describes the analysis of complex scenario of urban area by means of a reduced number of tomographic SAR data. First, the tomographic data are processed using the standard MUSIC algorithm, which requires an estimation of the data covariance matrix and an estimation of number of sources. We introduce the tomographic bilateral filter (To-moBLF) to improve the estimation of the covariance matrix and we propose a new model order selection scheme using the tomographic entropy parameters TomoH. Then point of interest are extracted using the Tomographic Signal-to-Noise Index (TomoSNI) algorithm.