Andreas Danklmayer

Assessment of Atmospheric Propagation Effects in SAR Images

TerraSAR-X, the first civil German synthetic aperture radar (SAR) satellite, was successfully launched on June 15, 2007. After 4.5 days, the first processed image was obtained. The overall quality of the image was outstanding; however, suspicious features could be identified which showed precipitation-related signatures. These rain-cell signatures are thoroughly investigated, and the physical background of the related propagation effects is provided. In addition, rain-cell signatures from former missions like SIR-C/X and the Shuttle Radar Topography Mission are provided for comparison. During the commissioning phase of TerraSAR-X, a total of 12 000 scenes were investigated for potential propagation effects, and about 100 scenes revealed atmospheric effects to a visible extent. Some of the particularly interesting events were selected and are discussed in greater detail. An interesting case of data acquisition over New York will be presented, which shows typical rain-cell signatures, and the SAR image will be compared with weather-radar data acquired nearly simultaneously (within the same minute). By comparing the images, it can be clearly seen that reflectivities in the weather-radar image of 50 dBZ may cause visible artifacts in SAR images. Furthermore, in this paper, we discuss the influence of the atmosphere (troposphere) on the external calibration of TerraSAR-X. By acquiring simultaneous weather-radar data over the test site and the SAR acquisition, it was possible to flag affected SAR images and to exclude them from the procedure to derive the absolute calibration constant. Thus, it was possible to decrease the 1 sigma uncertainty of the absolute calibration factor by 0.15 dB.

Correction of ionospheric distortions in low frequency interferometric SAR data

In this paper we propose some ionospheric correction schemes for space-borne synthetic aperture radar (SAR) and polarimetric interferometric SAR (PolInSAR). The spatial and temporal variation of the free electron density in the upper-most atmosphere affects the propagation of the radar pulse resulting in image distortions. We estimate the total electron content (TEC) by applying the Appleton-Hartree equation to the distortions in the focusing, polarimetry, and interferometry. Then we propose a combined estimator that yields comprehensive differential TEC estimations. The effect of vertical structures of the ionosphere on interferometric phase is further discussed.

Signal: SAR for ice, glacier and global dynamics

SIGNAL is an innovative earth exploration mission proposal with the main objective to estimate accurately and repeatedly topography and topographic changes associated with mass change or other dynamic effects on glaciers, ice caps and polar ice sheets. Elevation measurements are complemented with glacier velocity measurements, providing valuable additional information for a better understanding of the hydrology of glacierized basins and of the Arctic and Antarctic water cycle. SIGNAL is capable of monitoring all critical regions with a high spatial resolution and an adequate revisit time. This paper gives an overview about the actual mission design status and provides a brief description of the topography (DEM - digital elevation map) self-calibration strategy and the estimated global interferometric performance.

Joint French-German radar measurements for the determination of the refractive index in the maritime boundary layer

To predict the performance of coastal and shipborne radars, it is essential to assess the propagation characteristics of electromagnetic waves in the maritime boundary layer. To be independent upon environmental measurements, which are generally not as precise and reliable as they have to be for a proper input to simulation programs, usually based upon parabolic equation models, a method to retrieve the refractive index gradients in the low troposphere is the Refractivity from Clutter (RFC) algorithm. The propagation factor is computed from the received clutter power and is iteratively processed in order to retrieve the refractive index profiles. Under a respective French-German technical agreement a measurement program concerning radar propagation in the maritime boundary layer has been initiated, with contributions from ONERA-CERT, DGA MI / TN, Fraunhofer-FHR and the German Technical Center for Ships and Naval Weapons (WTD 71). The paper gives an overview on the RFC method with examples from the previous campaigns. It describes the experimental set-up and its methodology.

Comparison of methods for extracting and utilizing radar target characteristic parameters

A comparative analysis of different representations of polarimetric SAR data has been carried out. Each representation is considered in terms of the amount and type of information it provides. The investigation is motivated by the fact that, although a large number of decomposition methods are available, a detailed assessment of their characteristics has been missing in the past and still has to be further elaborated. Moreover, some new methods have been recently presented, derived from fields different from radar polarimetry. The features provided by these methods are worthy of a closer investigation and a direct comparison with methods used until now. This is the case, for example, of the principal component analysis (PCA) adapted to polarimetry by Lüneburg and not yet practically tested. On this background, a series of classification tests have been carried out, comparing the results in terms of their accuracy. This approach allows for a quantitative estimate of the information content of the different polarimetric parameters under consideration.

Analysis of Atmospheric Propagation Effects in TerraSAR-X Images

TerraSAR-X, the first civil German synthetic aperture radar (SAR) satellite has been successfully launched in 2007, June 15th. After 4.5 days the first processed image has been obtained. The overall quality of the image was outstanding, however, suspicious features could be identified which showed precipitation related signatures. These rain-cell signatures motivated a further in-depth study of the physical background of the related propagation effects. During the commissioning phase, a total of 12000 scenes have been investigated for potential propagation effects and about 100 scenes have revealed atmospheric effects to a visible extent. An interesting case of a data acquisition over New York will be presented which shows typical rain-cell signatures and the SAR image will be compared with weather-radar data acquired nearly simultaneously (within the same minute). Furthermore, in this contribution we discuss the influence of the atmosphere (troposphere) on the external calibration (XCAL) of TerraSAR-X. By acquiring simultaneous weather-radar data over the test-site and the SAR-acquisition it was possibleto improve the absolute calibration constant by 0.15 dB.

Propagation experiment in the littoral at 94 GHz

Propagation above the sea surface depends on many parameters related to the meteorological and oceanographic conditions, the measurement geometry and the system parameters. In this contribution we report on an experiment performed at the Gulf of Mexico in 2012. A dataset consisting of measurements from a 94 GHz radar system above the sea surface towards a fixed corner reflector was established in the frame of the SMARTEX campaign together with the oceanographic and meteorological characterization. In this contribution we show a subset of the measurement results obtained in comparison with some modelling examples.

Comparison of precipitation effects in space-borne X- and Ka-band SAR imaging

As the operating frequencies of SAR-systems are increasing, the visible distortions due to precipitation in SAR-images are becoming more frequent. This holds especially for the case of convective rain events. The German space-borne satellite TerraSAR-X has delivered a series of measurement examples, which were used to study precipitation effects in SARimages. Based on these valuable data takes and simultaneous weather radar measurements, a quantitative estimation of precipitation effects in SAR-images is presented. In a further step, an attempt is made to extrapolate the observed effects to systems operating at higher nominal frequency-bands, i.e. Ka-band, being taken under consideration for future SARsystems.

Principal Component Analysis (PCA) in the Context of Radar Polarimetry

Statistical and computational techniques for revealing the internal structure that underlies the set of random correlated data exists in a great variety at present; and target decomposition theorems, either in the coherent or incoherent formulation, are well established. In spite of this fact a rather innovative and new concept is presented in this contribution. In turn the Principal Component Analysis (PCA) is considered to possibly add value to existing approaches, and it allows for an interpretation of polarimetric synthetic aperture radar measurements using variables obtained via linear transformation. Starting with the Sinclair backscatter matrix S which will be further transformed into the so called target feature vector by stacking column elements of S and generating the covariance matrices averaged over a certain pixel array, we show, how the Sinclair backscatter matrix is decomposed into the sum of a maximum of four 2 x 2 elementary point scatter matrices which are weighted by the principal components, whereas the variances of these components agree with the eigenvalues of the covariance matrix. This mathematical development defines a decomposition which expresses scattering mechanism from distributed targets in terms of scattering matrices via an incoherent step.

Application of principal component analysis in radar polarimetry

Second order moments of multivariate (often Gaussian) joint probability density functions can be described by the covariance or normalised correlation matrices or by the Kennaugh matrix (Kronecker matrix). In Radar polarimetry the application of the covariance matrix is known as target decomposition theory, which is a special application of the extremely versatile principal component analysis (PCA). The basic idea of PCA is to convert a data set, consisting of correlated random variables into a new set of uncorrelated variables. The concept of PCA to radar polarimetry is applied to a polarimetric Lband SAR data set. Therefore, new uncorrelated random variables will be introduced by means of linear transformations with well determined loading coefficients. This in turn, will allow the decomposition of the original random backscattering target variables into four point targets with new random uncorrelated variables whose variances agree with the eigenvalues of the covariance matrix. Keywords-Radar Polarimetry, Principal Component, Target Decomposition;