3-D Imaging of Persistent Scatterers in Urban Areas using an ENVISAT/ASAR Interferometric Stack
Frey, Othmar1; Hajnsek, Irena2; Wegmuller, Urs3; Werner, Charles L.3
1ETH Zurich / Gamma Remote Sensing, SWITZERLAND; 2ETH Zurich / DLR, SWITZERLAND; 3Gamma Remote Sensing, SWITZERLAND

SAR tomography supports the extraction of information in complex 3-D target scenarios thereby supporting different SAR applications, such as forest parameter retrieval, or retrieval of additional point targets for persistent scatterer interferometry (PSI)-based deformation measurements in urban scenarios. Using spaceborne SAR data, typically 25 up to 50 or even more repeat-pass interferometric data sets of the same area with spatial baselines perpendicular to the line of sight are needed in order to distinguish different scatterers also in elevation direction. However, applying SAR tomography techniques to an interferometric stack of spaceborne SAR data over urban areas can not only provide three-dimensional information in the form of a tomographic image but it has also the potential to discriminate multiple persistent scatterers occurring within one range pixel. These "mixed" targets that fall into a single pixel would otherwise not be selected as persistent scatterer candidates. Separating these scatterers using tomographic processing techniques increases the number and the level of detail of persistent scatterer localizations.
Various authors have successfully demonstrated the application of tomographic techniques to obtain 3-D information within urban scenarios [1]-[6]. In addition, the concept of differential SAR tomography was proposed by Lombardini [7] and most recently extended to superresolution techniques employing 2-D adaptive spectral estimation [8] to resolve multiple scatterers in the third dimension and time. Nevertheless, further research and development is still required to bring the spaceborne tomography techniques to a more operational level, particularly, in the context of their role for persistent scatterer interferometry [9].
In this work, we combine tomographic focusing algorithms, as demonstrated in our recent work on airborne SAR tomography [10]-[11], with an interferometric point target analysis (IPTA) approach [12] to estimate (1) tomographic profiles and to (2) separate "mixed" point target candidates for PSI processing in urban areas using spaceborne SAR data. In the following the processing methodology is sketched.

Tomographic processing of spaceborne repeat-pass data requires that low-frequency phase contributions are estimated and isolated prior to focusing the data in the elevation direction. These low-frequency phase contributions are determined by a PSI processing sequence.
The preprocessing steps include:
1) Selection of reference scene from a stack of SLC data sets.
2) Geocoding using the multilook intensity image of the reference scene.
3) Coregistration including a refinement step using offset estimates between the data sets of the stack.
Then, persistent scatterer candidates are selected based on spectral diversity and the temporal variability of the backscattering. In a next step, point differential interferograms are obtained in an iterative manner. For each persistent scatterer candidate, the topographic and orbital phases are simulated and subtracted from the point-wise complex-valued interferogram followed by unwrapping and filtering in order to isolated the spatially correlated phase contributions from high-frequency phase contributions such as the residual topographic phase.
After an initial acceptable PSI solution has been obtained, tomographic processing is applied for one of the following options, or a combination thereof:
- To extract tomographic profiles (Beamforming, Capon, MUSIC, etc.)
- To separate scatterers within one resolution cell and thereby increase the number of persistent scatterers that can be detected. This is then followed by:
- Application of point target selection algorithms on different layers with tomographically processed data to select and update the point list.
- Further iteration of PSI processing using the larger updated point list.

The proposed tomographic technique is demonstrated by means of an interferometric stack of 30 Envisat/ASAR stripmap-mode SLC data sets over the city of Bucharest, Romania. This data set has already been used for ground displacement measurements using persistent scatterer interferometry within the European Commission FP7 project PanGeo.
In the final paper, the different tomographic techniques are compared and, in addition, the point densities obtained with the different (and also without support from) tomographic methods are assessed.

[1] G. Fornaro and A. Pauciullo, ''LMMSE 3-D SAR focusing,'' IEEE Trans. Geosci. Remote Sens., vol. 47, no. 1, pp. 214-223, Jan. 2009.
[2] G. Fornaro and F. Serafino, ''Imaging of single and double scatterers in urban areas via SAR tomography,'' IEEE Trans. Geosci. Remote Sens., vol. 44, no. 12, pp. 3497-3505, 2006.
[3] N. Adam, X. X. Zhu, C. Minet, W. Liebhart, M. Eineder, and R. Bamler, ''Techniques and examples for the 3D reconstruction of complex scattering situations using TerraSAR-X,'' in Proc. IEEE Int. Geosci. Remote Sens. Symp., vol. 3, 2009.
[4] S. Sauer, L. Ferro-Famil, A. Reigber, and E. Pottier, ''Three-dimensional imaging and scattering mechanism estimation over urban scenes using dual-baseline polarimetric InSAR observations at L-band,'' IEEE Trans. Geosci. Remote Sens., vol. PP, no. 99, pp. 1-14, 2011.
[5] D. Reale, G. Fornaro, A. Pauciullo, X. X. Zhu, and R. Bamler, ''Tomographic imaging and monitoring of buildings with very high resolution SAR data,'' IEEE Geosci. Remote Sens. Lett., vol. 8, no. 4, pp. 661-665, July 2011.
[6] X. X. Zhu and R. Bamler, ''Demonstration of super-resolution for tomographic SAR imaging in urban environment,'' IEEE Trans. Geosci. Remote Sens., no. 99, pp. 1-8, 2011, early Access.
[7] F. Lombardini, ''Differential tomography: a new framework for SAR interferometry,'' IEEE Trans. Geosci. Remote Sens., vol. 43, no. 1, pp. 37-44, 2005.
[8] F. Lombardini and M. Pardini, ''Superresolution differential tomography: Experiments on identification of multiple scatterers in spaceborne sar data,'' IEEE Trans. Geosci. Remote Sens., vol. 50, no. 4, pp. 1117-1129, Apr. 2012.
[9] ''Fringe 2011 sorted recommendations,'' ESA, Frascati, Italy, Sept. 2011.
[10] O. Frey and E. Meier, ''Analyzing tomographic SAR data of a forest with respect to frequency, polarization, and focusing technique,'' IEEE Trans. Geosci. Remote Sens., vol. 49, no. 10, pp. 3648-3659, Oct. 2011.
[11] O. Frey and E. Meier, ''3-D time-domain SAR imaging of a forest using airborne multibaseline data at L- and P-bands,'' IEEE Trans. Geosci. Remote Sens., vol. 49, no. 10, pp. 3660-3664, Oct. 2011.
[12] U. Wegmuller, D. Walter, V. Spreckels, and C. Werner, ''Nonuniform ground motion monitoring with TerraSAR-X persistent scatterer interferometry,'' IEEE Trans. Geosci. Remote Sens., vol. 48, no. 2, pp. 895-904, Feb. 2010.