International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B7, 2012
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia
TOMOGRAPHIC SAR INVERSION FROM MIXED REPEAT- AND SINGLE-PASS DATA
STACKS - THE TERRASAR-X/TANDEM-X CASE
Xiao Xiang Zhu *°, Richard Bamler *°
* German Aerospace Center (DLR), Remote Sensing Technology Institute (IMF), Oberpfaffenhofen, 82234 Wessling,
Germany. (xiao.zhu, richard.bamler)@dlr.de
b Technische Universität München, Lehrstuhl für Methodik der Fernerkundung, Arcisstraße 21, 80333
Munich, Germany
Commission VII/2: SAR Interferometry
KEY WORDS: Tomographic SAR Inversion, TanDEM-X data, SLIMMER
ABSTRACT:
This paper presents the first demonstration of high precision very high resolution tomographic SAR inversion with the assistance of
TanDEM-X data. The data quality of TerraSAR-X and TanDEM-X is investigated. TomoSAR algorithms such as SVD-Wiener,
Nonlinear Least Squares and SLIMMER are extended for mixed repeat- and single-pass data stacks. A systematic approach is
proposed for the fusion of TerraSAR-X and TanDEM-X data in which the different data quality provided by the TerraSAR-X and
TanDEM-X data are taken into account by introducing a weighting according to the noise covariance matrix. The proposed approach
is evaluated with simulated data. The simulation result shows that the reconstruction accuracy of tomographic SAR inversion can be
improved significantly by using jointly fused TerraSAR-X and TanDEM-X data.
1. INTRODUCTION
Tomographic SAR Inversion (Lombardini, 2003; Fornaro et al.,
2009; Zhu and Bamler, 2010a), including SAR tomography
(TomoSAR) and differential SAR tomography (D-TomoSAR),
aims at real and unambiguous 3D, 4D (space-time) or even
higher dimensional SAR imaging and is one of the most
advanced SAR techniques.
TomoSAR uses typically 20-100 multi-pass SAR
interferometric data sets of the same area taken from
approximately the same, but slightly different, orbits to
establish a synthetic aperture in the elevation direction. It aims
at deriving the full scattering density, ie. the reflectivity
profile, in elevation by spectral analysis with special
consideration of the difficulties caused by sparse and irregular
sampling of the aperture. From this reconstructed profile in
elevation multiple scatterers in any azimuth-range pixel are
separated, and hence the full 3D (azimuth, range and elevation)
reflectivity distribution is obtained. Therefore, TomoSAR is the
strictest way of 3D SAR imaging while classical INSAR can be
regarded as the limiting case of parametric TomoSAR. D-
TomoSAR uses the fact that the different acquisitions are taken
at different times and introduces new dimensions to the
TomoSAR system model attributing to the possible motion of
the scatterers, linear and nonlinear, single component or multi-
component. By means of higher dimensional spectral analysis,
D-TomoSAR is capable of retrieving elevation and deformation
information even of multiple scatterers inside a single SAR
pixel. Persistent Scatterer Interferometry (PSI) is a special case
of D-TomoSAR where only a single scatterer inside a pixel is
assumed.
The new generation of SAR sensors, such as TerraSAR-X and
Cosmo-Skymed, have proven to open up new opportunities for
tomographic SAR inversion. Among all other advantages, such
as high absolute geometric accuracy, precise orbit
determination and short revisit time, this new class of SAR
sensors deliver SAR data with a very high spatial resolution of
up to | m compared to the medium (10-30 m)- and high (3-10
m)-resolution SAR systems available so far. For the first time,
the 3D shape and complex motion of single buildings can be
reconstructed and enables tomographic SAR inversion to
monitor urban infrastructure from space (Zhu and Bamler,
2010; Zhu and Bamler, 2012b).
The estimation accuracy of the 3D position and motion
parameters depends on the signal-to-noise ratio (SNR), number
of images used (typically 20-100), motion model assumption
and the coupling effect between the spatial baseline and
temporal base functions (Zhu and Bamler, 2012a; Zhu and
Bamler, 2011). The state-of-the-art reconstruction accuracy of
tomographic SAR inversion is limited, since:
- The SNR of many pixels is very low, typically 0~10dB;
- Although the underlying motion is complex, the motion
model order is limited and assumed to be up to 2, e.g. a
geodynamically induced linear motion and a thermal
dilation induced seasonal motion, which must be
estimated, although it is often regarded as a nuisance
parameter.
— The coupling effect between the phases attributed to the
underlying topography and motion cannot be neglected
using repeat-pass data stack acquired by a single antenna
SAR sensor.
Fig.1 presents a 3D view of the scatterers reconstructed by
TomoSAR of city blocks in downtown Las Vegas, using a stack
of 30 images acquired by TerraSAR-X. This limited accuracy
can be obviously observed from the outliers and noisy building
surfaces.
Along with the launch of TanDEM-X in 2010, for the first time
(after SRTM) there is a real multi-antenna system in space,
even though only with a single baseline. It enables us to acquire
data pairs simultaneously and repeatedly in time. The
TanDEM-X data pairs are free of motion, atmosphere and
temporal decorrelation, and hence possess much higher data
quality. The fusion of TerraSAR-X and TanDEM-X data, i.e.
adding a couple of TanDEM-X acquisition pairs to the
TerraSAR-X data stacks, can be used to improve the result of
tomographic SAR inversion from the above mentioned three
aspects on the one hand, and to explore the limits of
tomographic reconstruction on the other hand.
This paper presents the first demonstration of high precision
very high resolution tomographic SAR inversion with the
assistance of TanDEM-X data. The data quality of TerraSAR-X
and TanDEM-X is investigated (Section II). TomoSAR
algorithms such as SVD-Wiener, Nonlinear Least Squares and
