Andreas Reigber

First demonstration of airborne SAR tomography using multibaseline L-band data

In synthetic aperture radar (SAR) interferometry, the phase differences between two different sensor positions are used to estimate the terrain topography. Although it is possible in this way to find a three-dimensional (3D) surface representation, the distribution of the different scatterers in the height direction at a fixed range and azimuth position remains unknown. Contrary to this, tomographic techniques enable a real geometric resolution capability in the height direction and introduce new possibilities for many applications and inversion problems. Even misinterpretations in SAR images caused by layover and foreshortening effects can be solved by the tomographic processing. In this paper, the successful experimental realization of polarimetric airborne SAR tomography is demonstrated for the first time. The authors present the concept of aperture synthesis for tomographic imaging for the case of a multibaseline imaging geometry and discuss the constraints arising from the limited number of flight tracks. They propose a method for reduction of the height ambiguities associated to the irregular and undersampled spatial distribution of the imaging positions. Finally, they address the experimental requirements for polarimetric airborne SAR tomography and show experimental results using a multibaseline data set acquired in L-band by DLRs experimental SAR (E-SAR) of a test-site near Oberpfaffenhofen, Germany.

A new technique for noise filtering of SAR interferometric phase images

This paper addresses the noise filtering problem for SAR interferogram phase images. The phase noise is characterized by an additive noise model, and a filtering algorithm based on this noise model was developed by filtering noise along fringes. In addition, this filter adaptively adjusts the amount of filtering according to the coherence. The effectiveness of this filter is demonstrated using SIR-C/X-SAR multi-pass generated interferograms.

Estimation of Forest Structure, Ground, and Canopy Layer Characteristics From Multibaseline Polarimetric Interferometric SAR Data

This paper concerns forest parameter retrieval from polarimetric interferometric synthetic aperture radar (PolInSAR) data considering two layers, one for the ground under the vegetation and one for the volumetric canopy. A model is designed to combine a physical model-based polarimetric decomposition with the random-volume-over-ground (RVoG) PolInSAR parameter inversion approach. The combination of a polarimetric scattering media model with a PolInSAR RVoG vertical structure model provides the possibility to separate the ground and the volume coherency matrices based on polarimetric signatures and interferometric coherence diversity. The proposed polarimetric decomposition characterizes volumetric media by the degree of polarization orientation randomness and by the particle scattering anisotropy. Using the full model enhances the estimation of the vertical forest structure parameters by enabling us to estimate the ground-to-volume ratio, the temporal decorrelation, and the differential extinction. For forest vegetation observed at L-band, this model accounts for the ground topography, forest and canopy layer heights, wave attenuation in the canopy, tree morphology in the form of the angular distribution and the effective shapes of the branches, and the contributions from the ground level consisting of surface scattering and double-bounce ground-trunk interactions, as well as volumetric understory scattering. The parameter estimation performance is evaluated on real airborne L-band SAR data of the Traunstein test site, acquired by the German Aerospace Center (DLR)s E-SAR sensor in 2003, in both single- and multibaseline configurations. The retrieved forest height is compared with the ground-truth measurements, revealing, for the given test site, an average root-mean-square error (rmse) of about 5 m in the repeat-pass configuration. This implies an improvement in rmse by over 2 m in comparison to the pure coherence-based RVoG PolInSAR parameter inversion.

NL-SAR: A Unified Nonlocal Framework for Resolution-Preserving (Pol)(In)SAR Denoising

Speckle noise is an inherent problem in coherent imaging systems such as synthetic aperture radar. It creates strong intensity fluctuations and hampers the analysis of images and the estimation of local radiometric, polarimetric, or interferometric properties. Synthetic aperture radar (SAR) processing chains thus often include a multilooking (i.e., averaging) filter for speckle reduction, at the expense of a strong resolution loss. Preservation of point-like and fine structures and textures requires to adapt locally the estimation. Nonlocal (NL)-means successfully adapt smoothing by deriving data-driven weights from the similarity between small image patches. The generalization of nonlocal approaches offers a flexible framework for resolution-preserving speckle reduction. We describe a general method, i.e., NL-SAR, that builds extended nonlocal neighborhoods for denoising amplitude, polarimetric, and/or interferometric SAR images. These neighborhoods are defined on the basis of pixel similarity as evaluated by multichannel comparison of patches. Several nonlocal estimations are performed, and the best one is locally selected to form a single restored image with good preservation of radar structures and discontinuities. The proposed method is fully automatic and handles single and multilook images, with or without interferometric or polarimetric channels. Efficient speckle reduction with very good resolution preservation is demonstrated both on numerical experiments using simulated data, airborne, and spaceborne radar images. The source code of a parallel implementation of NL-SAR is released with this paper.

Adaptive spectral estimation for multibaseline SAR tomography with airborne L-band data

In the recent years there has been growing interest in exploiting multibaseline (MB) SAR interferometry in a tomographic framework, to produce full 3D imaging e.g. of forest layers. However, Fourier-based MB SAR tomography is generally affected by unsatisfactory imaging quality due to a typically low number of baselines and their irregular distribution. In this work, we apply the more modern adaptive Capon spectral estimator to the vertical image reconstruction problem, using real airborne MB data. A first demonstration of possible imaging enhancement in real-world conditions is given. Keywordssynthetic aperture radar interferometry, electromagnetic tomography, forestry, spectral analysis.

TOPS Interferometry With TerraSAR-X

This paper presents results on SAR interferometry for data acquired in the Terrain Observation by Progressive Scans (TOPS) imaging mode. The rationale to retrieve accurate interferometric products in this mode is expounded, emphasizing the critical step of coregistration. Due to the particularities of the TOPS mode, a high Doppler centroid is present at burst edges, demanding a very high azimuth coregistration performance. A coregistration accuracy of around one tenth of a pixel, as it is usually recommended for stripmap interferometric data, could result in large undesired azimuth phase ramps in each TOPS burst. This paper presents two approaches based on the spectral diversity technique to precisely estimate this coregistration offset with the required accuracy and evaluates their performance. The effect of squint at burst edges in terms of an undesired impulse response shift during focusing and the impact on the interferometric coregistration performance is also addressed. Repeat-pass TOPS data acquired experimentally by TerraSAR-X are used to validate the proposed approaches.

Comparison of Topography- and Aperture-Dependent Motion Compensation Algorithms for Airborne SAR

This letter presents a comparison between three Fourier-based motion compensation (MoCo) algorithms for airborne synthetic aperture radar (SAR) systems. These algorithms circumvent the limitations of conventional MoCo, namely the assumption of a reference height and the beam-center approximation. All these approaches rely on the inherent time-frequency relation in SAR systems but exploit it differently, with the consequent differences in accuracy and computational burden. After a brief overview of the three approaches, the performance of each algorithm is analyzed with respect to azimuthal topography accommodation, angle accommodation, and maximum frequency of track deviations with which the algorithm can cope. Also, an analysis on the computational complexity is presented. Quantitative results are shown using real data acquired by the Experimental SAR system of the German Aerospace Center (DLR).

Scene characterization using subaperture polarimetric SAR data

In synthetic aperture radar (SAR) polarimetry, the measured polarimetric signatures are used to analyze physical scattering properties of the imaged media. It is generally assumed that the sensor has a fixed orientation with respect to the objects. However, SAR sensors operating at lower frequencies, like L- and P-band, have a wide azimuth beamwidth, i.e., during the formation of the synthetic aperture, multiple squint angles are integrated to build the full-resolution SAR image. Variations in the polarimetric properties with the azimuthal look angle remain unconsidered. In this paper, a fully polarimetric subaperture analysis method is introduced. Using deconvolution, synthesized SAR images are decomposed into subaperture datasets, which correspond to the scene responses under different azimuthal look angles. A statistical analysis of the polarimetric parameters permits to clearly discriminate media showing a nonstationary behavior during the SAR integration. Finally, a method is proposed, which eliminates the influence of azimuthal backscattering variations in conventional polarimetric SAR data analysis. The effectiveness of the new methods is demonstrated on fully polarimetric SAR data, acquired by the German Aerospace Center (DLR) airborne experimental SAR sensor (E-SAR) at L-band.

Very-High-Resolution Airborne Synthetic Aperture Radar Imaging: Signal Processing and Applications

During the last decade, synthetic aperture radar (SAR) became an indispensable source of information in Earth observation. This has been possible mainly due to the current trend toward higher spatial resolution and novel imaging modes. A major driver for this development has been and still is the airborne SAR technology, which is usually ahead of the capabilities of spaceborne sensors by several years. Todays airborne sensors are capable of delivering high-quality SAR data with decimeter resolution and allow the development of novel approaches in data analysis and information extraction from SAR. In this paper, a review about the abilities and needs of todays very high-resolution airborne SAR sensors is given, based on and summarizing the longtime experience of the German Aerospace Center (DLR) with airborne SAR technology and its applications. A description of the specific requirements of high-resolution airborne data processing is presented, followed by an extensive overview of emerging applications of high-resolution SAR. In many cases, information extraction from high-resolution airborne SAR imagery has achieved a mature level, turning SAR technology more and more into an operational tool. Such abilities, which are today mostly limited to airborne SAR, might become typical in the next generation of spaceborne SAR missions.

Topography-dependent motion compensation for repeat-pass interferometric SAR systems

This letter presents a new motion compensation algorithm to process airborne interferometric repeat-pass synthetic aperture radar (SAR) data. It accommodates topography variations during SAR data processing, using an external digital elevation model. The proposed approach avoids phase artifacts, azimuth coregistration errors, and impulse response degradation, which usually appear due to the assumption of a constant reference height during motion compensation. It accurately modifies phase history of all targets before azimuth compression, resulting in an enhanced image quality. Airborne L-band repeat-pass interferometric data of the German Aerospace Center experimental airborne SAR (E-SAR) is used to validate the algorithm.