Urban scene reconstruction from a reduced number of tomographic SAR data

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.