Harald Anglberger

Fast ISAR image generation through localization of persistent scattering centers

Imagery data acquired by recently launched space borne SAR systems demonstrate a very good spatial resolution (e.g. one meter with TerraSAR-X). The designs of such complex systems make it compulsory to do SAR end-to-end simulations to optimize image quality (e.g. spatial and radiometric resolution, ambiguity suppression, dynamic range, etc.). The most complex, critical and challenging modules have to be designed for the generation of SAR raw data and SAR image generation, because the limits of computability and memory requirements are reached very quickly. Moreover, the analysis of SAR images is a demanding task, because of their sensor specific effects. Therefore, a simulation tool is under development to analyze realistic target features and make the scattering processes transparent to the user. With the method presented in this paper, SAR images of complex scattering bodies can be generated in a very efficient way. This is done by directly localizing scattering centers and identifying their persistency along the synthetic aperture. Thus the usual raw data generation and processing steps are dropped. The resulting images show a very good similarity to reality, because scattering centers due to multipath propagation effects are also handled. Furthermore this toolkit makes it possible to visualize the scattering centers and their evolution, by mapping them on the 3D structure of the scattering body. This results in transparency of the whole scattering process, which greatly improves the understanding of the image effects. The paper presents this new approach for the application of inverse SAR (ISAR) and first simulation results.

Applications of simulation techniques for high resolution SAR systems

The interpretation of radar imagery can often be very challenging due to specific imaging effects. Additionally, a fusion with other remote sensing data is not easy to accomplish, because of the imaging radars slant range coordinate system. Simulation techniques are able to provide essential assistance or even practical solutions to such challenges. This paper shows the usage of a developed simulator in practical applications for signature analysis, data fusion and acquisition planning of spaceborne radar systems, but also for parametric end-to-end simulations of a very high resolution ground based radar.

Transforming optical image data into a SAR system's range-based image space

The fusion of image data from different sensor types is an important processing step for many remote sensing applications to maximize information retrieval from a given area of interest. The basic process to fuse image data is to select a common coordinate system and resample the data to this new image space. Usually, this is done by orthorectifying all those different image spaces, which means a transformation of the image’s projection plane to a geographic coordinate system. Unfortunately, the resampling of the slant-range based image space of a space borne synthetic aperture radar (SAR) to such a coordinate system strongly distorts its content and therefore reduces the amount of extractable information. The understanding of the complex signatures, which are already hard to interpret in the original data, even gets worse. To preserve maximum information extraction, this paper shows an approach to transform optical images into the radar image space. This can be accomplished by using an optical image along with a digital elevation model and project it to the same slant-range image plane as the one from the radar image acquisition. This whole process will be shown in detail for practical examples.

Depth-of-focus issues on spaceborne very high resolution SAR

Higher resolutions mean a more complex challenge on the SAR imaging not only in dealing with an at least quadratically growing data amount, but the more with stronger conditions on the focusing of the SAR image. In this study the defocusing effect is evaluated quantitatively by measuring the resulting resolution of a simulated ideal point scatterer depending on its height distance to the focusing plane. The simulations indicate a linear dependence of the depth-of-focus on the square of the nominal cross range resolution.

An image acquisition planning tool for optimizing information content in image data of spaceborne SAR systems

In contrast to remote sensing with optical sensors, synthetic aperture radar (SAR) satellites require a slant imaging geometry for image acquisition. This fact and because SAR systems operate their sensors actively emphasize that the resulting shadowing effects can have crucial influence on the information content of the image product. Additionally, information retrieval is aggravated by layover effects, where e.g. signatures of target objects superimpose with clutter information. Especially for security applications, the prediction of the expected information content and the calculation of layover and shadow regions during mission planning could greatly improve the image product. This paper presents a toolset to optimize imaging geometry parameters for the image acquisition of a SAR sensor, that performs simulation techniques for finding layover and shadow regions in a given target scene. The described methods will be verified by applying them to TerraSAR-X system parameters and image data.

A simulation-based approach towards automatic target recognition of high resolution space-borne radar signatures

Specific imaging effects that are caused mainly by the range measurement principle of a radar device, its much lower frequency range as compared to the optical spectrum, the slanted imaging geometry and certainly the limited spatial resolution complicates the interpretation of radar signatures decisively. Especially the coherent image formation which causes unwanted speckle noise aggravates the problem of visually recognizing target objects. Fully automatic approaches with acceptable false alarm rates are therefore an even harder challenge. At the Microwaves and Radar Institute of the German Aerospace Center (DLR) the development of methods to implement a robust overall processing workflow for automatic target recognition (ATR) out of high resolution synthetic aperture radar (SAR) image data is under progress. The heart of the general approach is to use time series exploitation for the former detection step and simulation-based signature matching for the subsequent recognition. This paper will show the overall ATR chain as a proof of concept for the special case of airplane recognition on image data from the space borne SAR sensor TerraSAR-X.

Analysis of SAR images by simulation

Accurate simulation tools for the design of space borne synthetic aperture radar systems (SAR) are compulsory for the analysis of the systems capabilities, because ground based experimental tests are in most cases impossible and very costly. Through a simulation process it is possible to analyze the image quality parameters for a given system configuration or evaluating the effects in SAR images when this configuration is changed. A new fast SAR image simulator (SARIS) is currently under development on the basis of an existing toolset called SAR end-to-end simulator (SETES). This image simulator produces SAR images by using the point spread function (PSF) of a focused point target response in contrast to SETESs very expensive raw data generation module. In SARIS the SAR image is produced through a convolution of the PSF with the so-called reflectivity map of the scene. In this paper first simulation results with a prototype of SARIS are given to show effects like motion errors and low peak-to-side-lobe ratios.

Fusion of very high resolution SAR and optical images for the monitoring of urban areas

Remote sensing data from SAR and optical sensors provide complementary information, with each type of data being better suited for certain tasks. In this paper, the potential of using both types of data together for the monitoring of urban areas will be shown. This is illustrated using a dataset of very high resolution SAR and optical images of the city of Oslo (Norway), containing over three years of TerraSAR-X images acquired with different orbits and incidence angles, and aerial optical images that were photogrammetrically processed to obtain a DSM and a true ortho mosaic.

Improved characterization of scenes with a combination of MMW radar and radiometer information

For security related applications MMW radar and radiometer systems in remote sensing or stand-off configurations are well established techniques. The range of development stages extends from experimental to commercial systems on the civil and military market. Typical examples are systems for personnel screening at airports for concealed object detection under clothing, enhanced vision or landing aid for helicopter and vehicle based systems for suspicious object or IED detection along roads. Due to the physical principle of active (radar) and passive (radiometer) MMW measurement techniques the appearance of single objects and thus the complete scenario is rather different for radar and radiometer images. A reasonable combination of both measurement techniques could lead to enhanced object information. However, some technical requirements should be taken into account. The imaging geometry for both sensors should be nearly identical, the geometrical resolution and the wavelength should be similar and at best the imaging process should be carried out simultaneously. Therefore theoretical and experimental investigations on a suitable combination of MMW radar and radiometer information have been conducted. First experiments in 2016 have been done with an imaging linescanner based on a cylindrical imaging geometry [1]. It combines a horizontal line scan in azimuth with a linear motion in vertical direction for the second image dimension. The main drawback of the system is the limited number of pixel in vertical dimension at a certain distance. Nevertheless the near range imaging results where promising. Therefore the combination of radar and radiometer sensor was assembled on the DLR wide-field-of-view linescanner ABOSCA which is based on a spherical imaging geometry [2]. A comparison of both imaging systems is discussed. The investigations concentrate on rather basic scenarios with canonical targets like flat plates, spheres, corner reflectors and cylinders. First experimental measurement results with the ABOSCA linescanner are shown.

Mapping detailed 3D information onto high resolution SAR signatures

Due to challenges in the visual interpretation of radar signatures or in the subsequent information extraction, a fusion with other data sources can be beneficial. The most accurate basis for a fusion of any kind of remote sensing data is the mapping of the acquired 2D image space onto the true 3D geometry of the scenery. In the case of radar images this is a challenging task because the coordinate system is based on the measured range which causes ambiguous regions due to layover effects. This paper describes a method that accurately maps the detailed 3D information of a scene to the slantrange-based coordinate system of imaging radars. Due to this mapping all the contributing geometrical parts of one resolution cell can be determined in 3D space. The proposed method is highly efficient, because computationally expensive operations can be directly performed on graphics card hardware. The described approach builds a perfect basis for sophisticated methods to extract data from multiple complimentary sensors like from radar and optical images, especially because true 3D information from whole cities will be available in the near future. The performance of the developed methods will be demonstrated with high resolution radar data acquired by the space-borne SAR-sensor TerraSAR-X.