CrossCompatibility of ERSSLC Products
A. Barmettler, P. Pasquali,
D. Small and D. Nüesch
 
Remote Sensing Laboratories (RSL)
University of Zürich, Winterthurerstrasse 190, CH8057 Zürich, Switzerland
barmettler@rsl.geo.unizh.ch
http://www.geo.unizh.ch/rsl/

  


The SAR image products (ERSSLC) from the ERS AMI sensor are produced
and distributed by various PAFs, such as CPRF, IPAF and DPAF.
For high end applications that fully exploit the phase information
of the coherent recording system (i.e. interferometric applications
/ DEM generation) the feasibility of combining products from different
processing facilities is important. During this study, the level
of crosscompatibility of SLCs was assessed by comparing interferograms
and coherence maps which exploit combinations of pairs of SLCs.
This included autointerferograms from different processors. The
conclusions is that the tested SLC products can be exchanged without
a significant increase of the phase noise. Nevertheless, high
precision measurements must take into account the systematic errors
 phase offset and trend  introduced into the data.


Keywords  SARInterferometry,
Phase Noise, Image Quality, SLC, PAF
The user community has an interest in performing
SAR Interferometry by using existing SLC (Single Look Complex)
images, without having to take into account which PAF (Processing
and Archiving Facility) produced them. The requirements for SLC
images are described in the ERS.SAR.SLCI Product Specifications
(ESA Pub., 1995), where a number of tests
are defined, e.g. to confirm the phase preservation during the
processing. However, these tests do not ensure the crosscompatibility
of the images processed by different SAR processors for high quality
SAR interferometry, since they check mainly the quality of the
azimuth compression algorithm rather than the overall performance
of the processor.
The interferometric phase depends heavily on
the surface structure. To be representative of as many applications
as possible, the chosen test scenes included areas with a large
variety of coherences. We used two different tandem scenes, acquired
over Bern (Switzerland) and Cairo (Egypt), respectively. The Bern
tandem data from 13/14 August 1995 covers agricultural, forest
and urban areas as well as lakes: a mid to low level of coherence
was observed in this area.
The Cairo scene comprises larger regions with
rocks and dry areas to provide a completely different coherence
distribution. The desert area southwest of Cairo showed high
temporal coherence on the tandem 1day repeat data from 19/20
November 1995.
The SLC images received from SAR processors
used at CPRF (Central Processing Reference Facility, ESRIN) 
ESA VMP (Verification Mode Processor)  and IPAF (ASI) were analysed
and their CEOS parameters and Doppler spectra compared. This was
important for the interpretation of the interferograms and its
statistics, which were processed subsequently from each pair of
the SLC products. The InSAR processing was performed using our
inhouse developed interferometric SAR processor ISP and Zürich
InSAR Processor (ZIP).
The azimuth spectrum contains information about
the Doppler shift, and its bandwidth is related to the spatial
resolution in the azimuth direction. For the interpretation of
the coherence map statistics the knowledge of the relative resolution
between the SLC images is required.
Figure 1 presents
the averaged total azimuth power spectra for the Cairo SLC. It
is evident that ERS1 and ERS2 spectra have their maxima at a
different Doppler frequency (i.e. the Doppler centroid frequency)
due to different squint angles. In interferometric processing,
one has to avoid relating the not common spectral parts by filtering.
However, the systems have the same spectral shape and the same
processed and even a corresponding halfpower bandwidth of about
605 Hz (both, Cairo and Bern, 36% of the PRF of 1679.9 Hz). On
the other hand, the values indicated for the processed Doppler
bandwidth in the CEOS header differ significantly, probably using
different definitions of the term "bandwidth".
The Doppler centroid frequency (the frequency
of the spectra's maximum) is a main driver for accurate azimuth
focusing. Since it depends on the Earth's rotation and satellite
yaw steering, it varies in slant range. This dependency is usually
approximated by a polynomial of small degree. In Figure 2
the polynomials given in the header files are plotted and compared
with the calculated average of the Doppler Centroid frequency
for the ERS2 SLC processed by RSL. All PAFs use polynomials of
small degree to represent the range dependency of the Doppler
Centroid frequency. The CEOS third order polynomials used by the
CPRF and DPAF show inconsistencies compared to our own estimation
from raw data, whereas IPAF represents an acceptable linear fit.
The Centroid shows a high dependence on the
mean altitude above sea level. For ERS the azimuthal displacement
is in the order of 100 m per 1000 m change in altitude, which
corresponds to 30 Hz. Therefore it is important to use an algorithm
that takes as many azimuth samples as possible into account to
mitigate this topographic influence. If this is not the case,
the Doppler Centroid is expected to show a significant dependence
on azimuth position, and thus shows a high variability compared
to the mean value of the Doppler Centroid over the whole scene.
If one estimates the Doppler Centroid by exploiting
the final SLC product one finds a good representation of the polynomial
used during focusing, as expected since the Doppler Centroid is
projected into the data.
However, the polynomials used at CPRF and DPAF
show significantly different coefficients and the IPAF even a
different polynomial degree, hence the parameters or the software
to estimate the Doppler centroid frequency must be different among
these PAFs.
More than a dozen interferograms were computed
and analysed. To distinguish autointerferograms and tandem interferograms,
the terms Singletrack and Multitrack are
introduced. Singletrack means that the identical original
raw data from the sensor is processed at different PAFs and that
these products are compared. Multitrack is the common
tandem configuration of ERS1 and ERS2. ERS1 is considered the
master track within this report.
Singletrack interferograms provide a useful
way to compare the SAR processors. To calculate the phase difference
of the two images, a coregistration had to be performed. This
resulted in a shift in range of none to several pixels, whereas
the azimuth offset additionally showed a subpixel offset. The
observed range offset must be explained by inaccurate timereferencing
of the SAR processors. The azimuth shift of up to thousands of
pixels is originated by the nonstandardized starting time of
the frames and differences in the sensor velocities used for focusing,
together with inaccurate azimuth timereferencing.
The phase statistics of the coregistered autointerferograms
are compiled in Table 1. The value
of the interferometric phase between SLC from the various PAF
was almost constant but nonzero. According to the requirement
of Phase Preservation of the SLC (ESA Pub., 1995),
the zero phase of the azimuth filters are designated to the zero
Doppler point in the time domain. Since the autointerferograms
act similar to the interferometric offset processing test proposed
in (ESA Pub., 1995), we expected a mean
phase of less than 0.1 degrees. The observed phase bias leads
to the assumption that at least one of the tested SAR processors
has problems with phase preservation. Most likely this is due
to differences in the Doppler centroid estimation.
This observed variability of the mean interferometric
phase implies that absolute phase measurement (besides the 2
ambiguity) is still not possible. However, each processor passes
the requirement on the standard deviation of the interferometric
phase. It lies below the limit of 5 degrees.
It was a surprise to observe that the CPRF and
DPAF processors do not show a smaller standard deviation, since
both are assumed to use identical source code. Though, if the
start time in azimuth is different between CPRF and DPAF, the
final products are not identical, and could show the observed
variation on the same level as two different processors do. Therefore
it is still possible that the processors have the same source
code.
This random phase offset could be a problem
when mosaicing full frame or quarter scene images: the phase continuity
at the border would not be guaranteed.
In the following we tested for a systematic
error in the phase, i.e. a dependency on range or azimuth position.
Figure 3 reveals no phase trend in
azimuth for the autointerferograms. Moreover, the mean phase
stays in the interval of 0.1 degrees.
On the other hand, Figure 4
reveals a systematic phase trend in the range direction on the
order of 0.6 degrees. This phase trend in range is most probably
due to differences in the polynomial used to approximate the Doppler
Centroid frequency as a function of range, and hence the Doppler
Centroid estimation software.
We believe that it is less important that the
Doppler Centroid estimation is a perfect representation of the
physical Doppler Centroid frequency than that the various PAFs
calculate the data using the same algorithm and polynomial order.
The generation of the multitrack interferogram
is the conventional task of producing a tandem interferogram.
Figure 5 and 6
show the 2 fringes of the flattened interferogram.
The resulting phase fringes have a periodicity equivalent to a
change in height of about 150 m for the Bern interferogram and
of about 40 m for Cairo.
The two interferograms confirm the choice of the two test sites:
on the one hand there is the accurate and highresolution interferogram
from the flat and dry area around Cairo, which could be used for
direct phase unwrapping without any further processing steps;
on the other hand, the Bern interferogram appears noisy even in
the oneday repeat tandem configuration and the rather short baseline.
The production of a DEM would require numerous user interactions
during the unwrapping task.
The coherence histograms and statistics are
an indicator for the quality of the various processors. The processing
of image pairs from the same raw data in particular reveals the
relative phase differences introduced by the different processors.
Figure 7 shows the
coherence that can be achieved when combining products from different
SAR processors in the singletrack case. Notice how a difference,
even if small, is present in the phase information provided by
different focusing programs starting from the same raw data. The
level of phase noise is directly related to the correlation coefficient
(Bamler R. and Just D., 1993): the results
presented in Figure 7 concerning the coherence
distribution confirm the results seen in Table 1
in terms of phase noise.
In this case no systematic phase trends need
to be considered as a source of coherence loss, since the estimation
of the correlation coefficient is performed on relatively small
subwindows. No temporal decorrelation effects are present in this
combination: only image misregistration, differential defocusing
and different processor noise levels are possible sources for
this small loss of coherence.
The multitrack tandem coherence maps are also
affected by the temporal decorrelation. The histograms in Figure 10
and 11 confirm again the choice of two
completely different sites, by showing distinct distribution and
maxima values.
For the Bern site (Figure 10),
all calculated interferograms show about the same probability
distribution function. Very small differences in the estimated
coherence values are noticeable only when analysing the numerical
results. No reasons appear from this test to suggest that one
must necessarily use SLC pairs focused by the same processor to
produce interferometric images.
For the Cairo site (Figure 9)
some differences can be noticed between the different coherence
maps obtained from the various SLC combinations. Table 2
compiles the figures of statistics. The mean coherence of an interferogram
produced using SLCs from different processors is not necessarily
lower than that obtained from SLC produced by the same processor:
on the contrary, the maximum value of coherence for this site
was obtained by exploiting two data sets focused by different
processors.
The observed coherence differences can be explained
in terms of residual defocusing effects (Monti Guarnieri A., 1996),
differences in the focusing algorithms and considering the normal
variability of the phase noise introduced by every processor.
Although this study revealed some remarkable
qualitative results, we could not perform further tests to get
better statistics for quantitative data extraction. It should
be kept in mind that only a small data set has been used within
this analysis.
The investigated SLC image did not show any
anomalies, i.e. sidelobe artefacts or saturated areas. However,
the tested processors are not compatible with respect to the Doppler
Centroid estimation. The values for this frequency deviates by
as much as 50 Hz compared at one specific range distance. The
Doppler Centroid frequency dependency on range is represented
by polynomials of a degree not consistent among all PAFs. This
uncertainty may be the source for a random phase offset introduced
into the SLCs. In turn, this may lead to a phase inconsistency
when stepping quarter scenes to full frames (or full frame images
to larger mosaics), and makes reconstruction of the absolute phase
of the interferometric products without the use of ground control
points impossible.
Auto and differential interferograms showed
a phase trend in the range direction over a quarter scene swath,
whereas the mean interferometric phase in the azimuth direction
was observed to be constant. This phase trend is probably introduced
by the SAR processors and leads to systematic errors in the reconstructed
DEMs. The influence of this trend is larger in interferometric
applications with small baselines.
The product specifications (ESA Pub., 1995)
point out that SLCI products consist of a full frame. To date,
most of the operational SAR processors (suitable for SAR interferometry)
have only been capable of processing single quarter scenes at
a time. Thus, for largerscale interferometry, a full scene is
assembled from four independently processed parts, with the possibility
of introducing a phase inconsistency at the borders. Hence, the
phase trends and discontinuity will become more severe when considering
full frames.
Most important, the InSAR processing of SLC
data from different PAFs did not increase phase noise. The user
can combine SLCs from various PAFs for producing interferograms
without a loss of the overall quality.
However, there are some secondary restrictions
to the crosscompatibility: e.g. areas covered by the SLC are
not standardized, especially the azimuth times. This may lead
to a shift of up to 25% of the length of corresponding quarter
scenes. The parameters included within the CEOS header are defined
differently for each PAF (i.e. IPAF and CPRF even indicate different
wavelengths, pulse repetition frequencies, and spatial resolutions).
Some of these data seem to be in disagreement with the image positions.
ESA has announced its intention to harmonize the timereferencing
of the processors and CEOS header format used at ESA PAFs.
This work emerged from an ESA contract study
addressed to ESRIN, Rome. We like to thank ESA for the generous
provision of the required ERS images.
 Bamler R. and Just D., 1993
 Phase Statistics and Decorrelation in SAR Interferograms,
Proc. IGARSS `93, pp. 980984.
 Barmettler A., et. al., 1996
 CrossCompatibility of ERSSLCI Products, Report
to the ESA/ESRIN, RSL Zürich.
 Cattabeni M., et. al., 1994
 Estimation and Improvement of Coherence in SAR Interferometry,
Proc. IGARSS '94, pp. 720722.
 ESA Pub., 1995
 ERS.SAR.SLCI Product Specifications, ESA Doc., Issue
1.
 Goodman N.R., 1963
 Statistical Analysis Based on a Certain Multivariate Complex
Gaussian Distribution, Ann. Math. Statist., Vol. 34, No.
152, pp. 152180.
Monti Guarnieri A., 1996
Residual SAR Focusing: An Application to
Coherence Improvement, in IEEE Trans. GRS, Vol. 34, No. 1,
pp. 201211.
Keywords: ESA European
Space Agency  Agence spatiale europeenne,
observation de la terre, earth observation,
satellite remote sensing,
teledetection, geophysique, altimetrie, radar,
chimique atmospherique, geophysics, altimetry, radar,
atmospheric chemistry
