Nach oben pdf Coherent scatterers detection in glacier environments by means of TerraSAR-X images

Coherent scatterers detection in glacier environments by means of TerraSAR-X images

Coherent scatterers detection in glacier environments by means of TerraSAR-X images

A relevant class of point scatterers are the so called Coherent Scatterers (CSs) characterised by a stable spectral correlation. Accordingly, spectral correlation techniques have been proposed for their detection. The advantage of CSs compared to other point scat- terers is that they can be estimated on a single image basis. The concept of CSs has been introduced and discussed in [2] where a first extensive analysis of their amplitude, polarimetric and interferometric properties has been performed on the basis of air- borne data. Up to now, CSs detection has been inves- tigated primarily in urban environments. In this work, the detection of CSs in terms of wide-band space- borne SAR systems in natural scenarios, like ice and glacier terrain, is investigated and the properties of the detected CSs are analysed.
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Coherent scatterers detection: application over glacier terrain
using TerraSAR-X time series data

Coherent scatterers detection: application over glacier terrain using TerraSAR-X time series data

azimuth between two images is employed (obtained from their cross-correlation) [5]. Given the range-azimuth shift map, for each detected CS in the first image it is possible to fix a range-azimuth window in which that CS is likely to be in the second image. Figure 3(a) shows the candidate pairs to be the same CS after 11 days, obtained with a window as big as the 10% of the shift. By increasing the detection window [e.g. 90% in Figure 3(b)], the number of candidate pairs increases, at the cost of a possible increase of the number of the false pairs. Anyway, an indication has been obtained that a number of CSs can be retrieved in an image pair following the glacier movement. Similar results can be observed between the pair image 2 – image 3 in Figure 4.
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SAR tomography as an add-On to PSI: Detection of coherent scatterers in the presence of phase instabilities

SAR tomography as an add-On to PSI: Detection of coherent scatterers in the presence of phase instabilities

Abstract: The estimation of deformation parameters using persistent scatterer interferometry (PSI) is limited to single dominant coherent scatterers. As such, it rejects layovers wherein multiple scatterers are interfering in the same range-azimuth resolution cell. Differential synthetic aperture radar (SAR) tomography can improve deformation sampling as it has the ability to resolve layovers by separating the interfering scatterers. In this way, both PSI and tomography inevitably require a means to detect coherent scatterers, i.e., to perform hypothesis testing to decide whether a given candidate scatterer is coherent. This paper reports the application of a detection strategy in the context of “tomography as an add-on to PSI”. As the performance of a detector is typically linked to the statistical description of the underlying mathematical model, we investigate how the statistics of the phase instabilities in the PSI analysis are carried forward to the subsequent tomographic analysis. While phase instabilities in PSI are generally modeled as an additive noise term in the interferometric phase model, their impact in SAR tomography manifests as a multiplicative disturbance. The detection strategy proposed in this paper allows extending the same quality considerations as used in the prior PSI processing (in terms of the dispersion of the residual phase) to the subsequent tomographic analysis. In particular, the hypothesis testing for the detection of coherent scatterers is implemented such that the expected probability of false alarm is consistent between PSI and tomography. The investigation is supported with empirical analyses on an interferometric data stack comprising 50 TerraSAR-X acquisitions in stripmap mode, over the city of Barcelona, Spain, from 2007–2012.
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Coherent vs. Persistent Scatterers: A Case Study.

Coherent vs. Persistent Scatterers: A Case Study.

The search for point-like scatterers in SAR images is linked, principally, to the possibility to measure the phase of the radar signal, received from those scatterers in different acquisitions, very accurately minimizing any fluctuations due to stochastic contributions. This is a very important requirement for SAR interferometric applications and even more for measuring Line of Sight (LOS) displacements by means of Differential Interferometry. The Permanent Scatterers (PSs) selection is achieved through the estimation of the phase stability of the resolution cell backscattering [1]. Accordingly, assuming the availability of large time series of data, it is possible to analyze the amplitude dispersion of the image pixels or alternatively the value of Signal to Clutter Ratio (SCR) estimated [2]. Both quantities, indeed, have been demonstrated to be related with the phase error of the signal received from the illuminated target. A different approach, based on the spectral properties of a point-target, is considered for the Coherent Scatterers (CSs) technique [3]. Ideal point- like scatterers, in fact, are characterized by a completely correlated spectrum. One slice of the object spectrum is acquired in a SAR image thus, image sub-look spectral correlation can be used to separate deterministic from distributed targets. In this case no temporal analyses are involved in the procedure and the detection can be applied on a single image basis. In the following the CSs temporal stability has been investigated and the complementarities between the two techniques have been addressed.
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Sea surface wind field by X-band TerraSAR-X and Tandem-X

Sea surface wind field by X-band TerraSAR-X and Tandem-X

Although missing opportunity to compare the retrieved sea surface wind with in situ measurements due to an approaching typhoon, a pre-ordered TD-X image was acquired which images the typhoon Nanmadol over the Luson Strait, as indicated by the two yellow rectangles in Fig. 6. The calibrated TD-X ScanSAR image is shown in Fig. 10 (a). The dark patterns in the north-east and south-west of the image indicate attenuation of radar backscatter induced by strong rainfall of typhoon, which is, however, not the same as the rain effect in the case described above. The camiguin island is near to eye of the typhoon Nanmadol. The Mount Camiguin occupying the southwester tip of the island has an elevation of 712 metres. The large contrast between of backscatter in the north-west and south-east of the island indicates that orography of the island has an influence on the sea surface wind field. The retrieved sea surface wind field for this case using XMOD2 is shown in Fig. 10 (b). The retrieved wind field shows light wind speed in the eye is of around 5 m/s – 10 m/s. Away from the eye, the higher wind speed appears in eye wall area. In the south-east of the eye and north- west of the inner rain band, the sea surface wind speed is of around 25 m/s. However, we found a large area in the southwester of the eye, i.e., in front of the Camiguin island, which shows a higher wind speed above 30 m/s.
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Northeast Greenland outlet glacier velocities and high resolution elevation from TerraSAR-X and TanDEM-X data

Northeast Greenland outlet glacier velocities and high resolution elevation from TerraSAR-X and TanDEM-X data

TDM-GIMP DEM difference over most of the glaciated area of Zachariae Isstrøm. Nioghalvfjersfjorden does not show such a pronounced surface el- evation change. The large differences in the mountainous terrain can be attributed to radar shadow and the higher resolution of the TDM DEMs.

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Complex Statistics of Synthetic Aperture Radar Data Using High Resolution TerraSAR-X Images

Complex Statistics of Synthetic Aperture Radar Data Using High Resolution TerraSAR-X Images

• In order to describe the second-order properties of complex random signals completely, it is necessary to use two moments: the classical covariance function, and the pseudo-covariance function. As a direct consequence, PSD and pseudo-PSD should be employed

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Modeling and Parameter Estimation of TerraSAR-X Images for Scene Classification and Recognition

Modeling and Parameter Estimation of TerraSAR-X Images for Scene Classification and Recognition

Interferogram denoising by anisotropic phase diffusion. The fringes are well preserved and we obtain a very low number of residuals. The diffusion is driven by estimates of the local geometry given by a structure tensor. Coherent structures are enhanced.

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First demonstration of Azimuth Phase Coding Technique by TerraSAR-X

First demonstration of Azimuth Phase Coding Technique by TerraSAR-X

The key role played by spaceborne Synthetic Aperture Radar (SAR) in remote sensing and Earth observation is testified by the amount of missions started in the last years and planned for the future, e.g. ALOS-PALSAR, TerraSAR-X, COSMO-SkyMed, RADARSAT, Tan- DEM-X, Sentinel-1, PAZ [1]-[5]. In fact, SAR images are today an established essential tool for geological, hydrological, oceanographic, agricultural, urban and environmental applications, such as ice and water dy- namics analysis, vegetation classification, biomass and moisture retrieval, environmental threats and disasters monitoring. Nevertheless, a basic limitation still affects current SAR imaging: high spatial resolution and wide coverage are contradicting requirements, which cannot be simultaneously satisfied without a degradation of the other image quality parameters [6]. In particular, a dis- turbance due to range and azimuth ambiguities arises. In order to solve this basic limitation of current SAR systems a number of methods have been proposed, which enable mitigating the effect of the ambiguities [7]-[9]. Among the techniques for ambiguity suppres- sion, the one proposed by Dall and Kusk [9], denoted as Azimuth Phase Coding (APC), stands out for its indis- criminate applicability to point and distributed range ambiguities and its low implementation complexity. In more detail, the APC is based on three main steps: i) azimuth phase modulation on transmission; ii) azi- muth phase demodulation on reception; iii) filtering of the SAR azimuth signal over the processed Doppler
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Soil Moisture Estimation Using Dual-Polarimetric Coherent (HH/VV) TerraSAR-X and TanDEM-X Data

Soil Moisture Estimation Using Dual-Polarimetric Coherent (HH/VV) TerraSAR-X and TanDEM-X Data

For inversion, the SAR-derived α 1 is compared with its modelled counterpart for a range of expected ε- values, in order to obtain the best match between data and model for the respective dielectric constant of the soil and via the transfer polynomial of [6] also the soil moisture (see Figure 2).

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Detection and tracking of offshore platform’s oily slicks in TerraSAR-X imagery

Detection and tracking of offshore platform’s oily slicks in TerraSAR-X imagery

Thanks the low TerraSAR-X orbit altitude and relatively high latitude location of the Forties oil field, leaks from the same platforms have been observed with temporal interval of less than 13 h. While most previous studies on tracking oil spills assume that the observed slicks by consecutively acquired SAR images are the same and spatial displaced by the drift effect [2], a completely different situation is outlined by the analysis in [3]. By model simulation it is shown that leaks were not start-stop but continuous with only part of the old oil being drifted.
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Automated Detection of Precipitation induced Artefacts in X-band SAR Images

Automated Detection of Precipitation induced Artefacts in X-band SAR Images

As commercial synthetic aperture radar (SAR) satellites like TerraSAR come into operation, the control of prod- uct quality becomes increasingly of high relevance. The propagation path can under certain conditions greatly im- pair the imaging performance, particularly in the case of heavy precipitation events in the troposphere. Calcula- tions of the specific attenuation [dB/km] for rain-intensities of 40 mm/hr deliver values up to 1 dB/km for radar sys- tems operating in X–band[1, 2, 3]. Depending on the total length of the propagation path, the attenuation of the sig- nals in X–band may add up to 20 dB considering a path length through the precipitation medium of 10 km one way traversal [4, 5].
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Comparison of Orientation Angle Estimation Methodes over Coherent Scatterers

Comparison of Orientation Angle Estimation Methodes over Coherent Scatterers

The beta orientation angle was shown to be constrained to the subset of symmetrical scatterers (scatterers whose scattering matrices can be condiagonalized by unitary ro- tation transformation [7]) [9]. This drawback happens for distributed as well as for coherent scattering as shown in [9] and hence the procedure will not be considered here. However, the modification of the beta angle proposed in [10] belongs, as will be shown, to a class of procedures that can retrieve the orientation angle of more generalized scatterers. The polarization signature method requires a maximization procedure and as it belongs, by definition, to a class of routines that will be treated in the following, it will also not be specifically addressed.
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Oil seepage polarimetric contrast analysis in a time series of TerraSAR-X images

Oil seepage polarimetric contrast analysis in a time series of TerraSAR-X images

Natural hydrocarbon seeps are broadly distributed across the Gulf of Mexico. Such seeps emit oil and gas into the water column, increasing the phytoplankton biomass and impacting regionally the productivity, carbon and nutrient cycling [1]. A fraction of this oil reaches to the sea surface and can be detected by SAR data. Although the ability of SAR data to detect oil features present in ocean's surface is wide exploited in the literature, it is known that the detection of those features is also a challenge. The SAR image interpretation became more difficult when the meteorological and oceanographically data are unavailable, the wind speed is too high or oil look-alikes are present (these features, e.g. low-wind conditions and algal blooms, can be misinterpreted as oil by conventional oil spill detector). In order to improve the SAR capability in detection oil seepages, the potential of the multi-polarization SAR data have been successfully exploited [2]. The latter have been shown to provide also a rough estimation of oil damping properties.
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Pol-DinSAR: Polarimetric SAR Differential Interferometry Using Coherent Scatterers

Pol-DinSAR: Polarimetric SAR Differential Interferometry Using Coherent Scatterers

This means that a rotation about the LOS direction of a scatterer with reflection asymmetric characteristics induces a phase difference in the scattering matrix elements. This phenomenom will have implications in single polarization SAR differential interferometry, where the phase difference between acquisitions is the main input and is normally related to a displacement along the LOS direction. In such situations, the phase difference between the scattering matrix channels may be mis-interpreted, since the scatterer has rotated around and not moved along the LOS direction.

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Localization of Scatterers in Railway Environments for Train-to-Train Propagation

Localization of Scatterers in Railway Environments for Train-to-Train Propagation

In general, position estimations of consecutive measure- ments of one MPC spread to one side and the corresponding ambiguity to the other side of the scatterer. The spreading of the estimated positions is caused by the comparison of the Doppler calculated by (5) for the measurements or (4) for the 2D-model with all Doppler values of possible scatterer positions along the ellipse by (6). The rotation angle ϕ dependent Doppler of four different delays is shown in Fig. 8. The red continuous line can be seen as worst case and the black dashed line as best case for estimating ϕ. For example, a MPC with a short delay, would be described by the Doppler of the red line. In this case, a Doppler change by 10 Hz between two consecutive measurements would result in either an angular change by 85 deg or by 0.3 deg depending on the location of the scatterer along the ellipse. This behavior leads to a wide spread of the position estimation. The black dashed line represents a MPC with a long delay. The angular changes are more constant for similar Doppler changes. As a result, the spreading of the position estimation is reduced as for example for case D in Fig. 7.
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FPGA Prototyping of a High-Resolution TerraSAR-X Image Processor for Iceberg Detection

FPGA Prototyping of a High-Resolution TerraSAR-X Image Processor for Iceberg Detection

To provide the maritime community with up-to-date information on the presence and location of icebergs, the high-resolution radar images provided by the satellite are processed automat[r]

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Localization of Discrete Mobile Scatterers in Vehicular Environments Using Delay Estimates

Localization of Discrete Mobile Scatterers in Vehicular Environments Using Delay Estimates

of (9) requires at least three independent measurements. The required static environment mitigation, i.e. the displacement of any delay estimates close to static components (see Sec. III-B), however, reduces the amount of delay estimates assigned to a specific mobile scatterer. Thus, a rich static MPC environ- ment reduces the overall localization capabilities. This holds particularly for very sparse networks, such as the three-link network considered in this section, since an outage in any link impedes localization. Besides static MPCs, also the LoS impacts the localization capability due to the so called blind zone problem [12]. That means, induced MPCs of scatterers located close to the baseline between a transmitting and receiving node are hardly to detect. The estimation results of the described experiment confirm these blind zones, since it is not possible to expose mobile MPCs when the car is located in the proximity of the individual link baselines. This accounts for the links to Rx 1 and to Rx 2 in the region between −10 m
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Gas Detection by Means of Surface Plasmon Resonance Enhanced Ellipsometry

Gas Detection by Means of Surface Plasmon Resonance Enhanced Ellipsometry

Sensing gases and the determination of gas concentrations is important in sev- eral areas of life. Certain gases, in defined concentrations, can cause immense damage, for example through explosions or the death of human beings. Gas sensors are important equipment e.g.in the chemical industry: The concentra- tion of pollutant gases (e.g. sulphur dioxide and nitrogen oxides) has to be determined in oil drilling and refineries, in the steel industry or wastewater treatment. Toxic gases (e.g. carbon monoxide or hydrogen sulphide) have to be determined in very low concentrations in order to warn persons working in metal and coal mines. Ecologically harmful gases (e.g. carbon dioxide or ozone) need to be detected for environmental monitoring or in the automobile industry. Explosive or flammable gases (e.g. hydrocarbons or hydrogen) are to be determined below their lower explosive limit (LEL) in oil rigs or refinery and drilling sites. Devices for sensing gas are utilized in the private sector as well, e.g. in apartment buildings (domestic gas), hospitals (oxygen), or tun- nels (automotive exhaust emissions) [1]. Requirements for gas sensors are fast detection, distinction between gas types and chemical and physical stability.
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Coherent shift estimation for stacks of SAR images

Coherent shift estimation for stacks of SAR images

With coherent (and incoherent) speckle tracking the per- formances are in the order of the resolution element for a few independent samples, that is to say typically much larger than the wavelength and thus much worse than interferometric figures. However we could be interested in this technique for a number of reasons. Coherent tracking is suited for homogeneous areas with no features to track. It will work also in the along-track direction (azimuth), where interferometric tools cannot be applied, because it is a direction orthogonal to range. Moreover, the immunity to phase ambiguity makes speckle tracking useful also in the range direction, where it can support the phase unwrapping problem that inevitably rises in SAR interferometry. This use is detailed in [1] and [2]. Correlation techniques become more and more interesting for geophysical applications as high-resolution SAR systems (in range and/or in azimuth) become progressively available. Examples of coherent speckle tracking can be found in [3] and [4].
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