Synthetic Aperture Radar Data Processing Research Articles

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.

Feature-Enhancing Inverse Methods for Limited-View Tomographic Imaging Problems

In this paper we overview current efforts in the development of inverse methods which directly extract target-relevant features from a limited data set. Such tomographic imaging problems arise in a wide range of fields making use of a number of different sensing modalities. Drawing these problem areas together is the similarity in the underlying physics governing the relationship between that which is sought and the data collected by the sensors. After presenting this physical model, we explore its use in two classes of feature-based inverse methods. Microlocal techniques are shown to provide a natural mathematical framework for processing synthetic aperture radar data in a manner that recovers the edges in the resulting image. For problems of diffusive imaging, we describe our recent efforts in parametric, shape-based techniques for directly estimating the geometric structure of an anomalous region located against a perhaps partially-known background.

The Frequency Scaling Algorithm and interferometric Spotlight SAR processing

Synthetic Aperture Radar (SAR) is a well-established technique for air- and spaceborne high resolution imaging. This paper demonstrates the phase preservation of the new Frequency Scaling Algorithm for Spotlight SAR data processing and investigates differences between Stripmap and Spotlight illumination. The algorithm performs the range cell migration correction for non-chirped raw data without interpolation by using a novel frequency scaling operation. The azimuth processing is based on a spectral analysis approach that is made highly accurate by azimuth scaling. In almost all processing stages, a subaperture approach is introduced for efficient azimuth processing. The maximum scene size for air- and spaceborne spotlight parameter examples is estimated. A method is proposed, which shows how to process Stripmap mode raw data in the Spotlight mode. Point target simulations and real raw data processing, including the generation of Spotlight interferograms prove the phase preservation of the Frequency Scaling Algorithm. The same SAR Stripmap raw data set of DLR's airborne system is processed in Stripmap and in Spotlight mode and the resulting detected images and interferograms are compared to each other. The differences due to the different range of squint angles used for the azimuth focusing are discussed.

Sub-aperture algorithm for motion compensation improvement in wide-beam SAR data processing

The effects of strong motion errors in wide-beam azimuth synthetic aperture radar (SAR) processing are analysed and discussed, using simulated data, as well as data collected by the airborne experimental SAR system of the Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR) (E-SAR). A new sub-aperture approach for residual motion error compensation in wide-beam azimuth processing is proposed.

Damage Detection in Urban Areas by SAR Imagery

Synthetic aperture radar (SAR) provides high-quality images in all weather and all time conditions. It shows promise for acquiring spatial and temporal data for urban analysis. The objective of this study is threefold. First, the mathematical theory and physical background of SAR data acquisition and processing are described and introduced to the civil and engineering mechanics community. Second, a simulation tool based on the electromagnetic formulation is used to simulate SAR imagery of real-sized buildings as a proof of concept to demonstrate the usefulness of SAR applications and their imaging potentials and characteristics relevant to urban areas. Our third and last objective is to study the capabilities of damage and change diagnostic schemes based on simulated complex SAR images of pre- and post-events. A SAR image is obtained from a coherent imagery system and can be described in three dimensions, sometimes referred to as a complex imagery system, whereby two dimensions represent the spatial event of the image and the third dimension represents the phase content of the image. The phase information is relevant to the detection of the finer details in the image.

Speckle filtering of SAR images based on adaptive windowing

Speckle noise usually occurs in synthetic aperture radar (SAR) images owing to coherent processing of SAR data. The most well-known image domain speckle filters are the adaptive filters using local statistics such as the mean and standard deviation. The local statistics filters adapt the filter coefficients based on data within a fixed running window. In these schemes, depending on the window size, there exists trade-off between the extent of speckle noise suppression and the capability of preserving fine details. The authors propose a new adaptive windowing algorithm for speckle noise suppression which solves the problem of window size associated with the local statistics adaptive filters. In the algorithm, the window size is automatically adjusted depending on regional characteristics to suppress speckle noise as much as possible while preserving fine details. Speckle noise suppression gets stronger in homogeneous regions as the window size increases succeedingly. In fine detail regions, by reducing the window size successively, edges and textures are preserved. The fixed-window filtering schemes and the proposed one are applied to both a simulated SAR image and an ERS-1 SAR image to demonstrate the excellent performance of the proposed adaptive windowing algorithm for speckle noise.

Comparison of SIR‐C SAR wavenumber spectra with WAM model predictions

During April and October of 1994, the Space Radar Laboratory (SRL) flew on the space shuttle Endeavour at the relatively low altitude of 215 km. Using horizontal polarization, C‐band signal from the spaceborne imaging radar (SIR‐C), an onboard processor, designed and fabricated by the Johns Hopkins University Applied Physics Laboratory, formed synthetic aperture radar (SAR) images and computed over 100,000 corresponding image spectra. The low altitude, small look angle (23°–25°) and the use of horizontal polarization minimized both the loss of azimuth resolution caused by ocean surface motion and the relative contribution of the hydrodynamic component of the modulation transfer function. As a result, the SIR‐C SAR was able to image azimuth‐traveling waves with minimal distortion. After using linear inversions to convert image spectra to wave height‐variance spectra, the distributions of wavenumber and propagation direction from the processor‐derived spectra were consistent with wave model (WAM) predictions. Although the SAR wave height‐variance spectra underestimated significant wave height (SWH) at the higher SWHs, this error is compensated for by a simple linear correction. We collected 57 pairs of crossover spectra where the ground track pairs were nearly orthogonal. The crossovers were separated by 6 hours. Crossover comparisons show that the retrieved spectral parameters are independent of wave propagation direction. At this altitude and configuration, the SAR range and azimuth responses are nearly equal. The real‐time processing of spaceborne SAR data to produce accurate estimates of wavenumber, propagation direction, and SWH is clearly feasible with the orbital and instrument geometry of SIR‐C.

A short discussion on the exact compensation of the SAR range-dependent range cell migration effect

Efficient and precise compensation of the range cell migration (RCM) effect is a key point for a fast and accurate synthetic aperture radar (SAR) data processor. In particular the range-dependent nature of the range cell migration effect complicates the compensation operation. It has been recently shown that an exact compensation of the range-dependent RCM (RDRCM) phenomenon can be carried out either by applying the chirp scaling algorithm or the chirp z-transform procedure. This paper investigates the relationship between the two methods. In particular, it is shown that the chirp z-transform based approach represents a particular implementation of the chirp scaling algorithm. A final discussion is dedicated to show how the chirp z-transform and the chirp scaling procedure can be applied within a SAR data processing algorithm.

Comparative evaluation of ALMAZ, ERS-1, JERS-1, and Landsat-TM for discriminating wet tundra habitats

AbstractSystematic image-classification methods were applied to ALMAZ, ERS-1, and JERS-1 synthetic aperture radar (SAR) and Landsat-TM multispectral satellite images to evaluate the relative information content of the satellite data for discriminating wet tundra habitats in northern Alaska. Results suggest that SAR data can be used to concurrently detect a maximum of four or five landcover classes using the methods of this study. Combining two or more SAR images from different satellites improved the detection of some classes, particularly water bodies. Combining full-resolution SAR data with Landsat-TM did not improve the detection capabilities of Landsat-TM alone. Further research is needed to assess other image-classification and SAR data processing methods.

Northern forest classification using temporal multifrequency and multipolarimetric SAR images

Characterizing forest ecosystem dynamics for global change studies requires updated knowledge in terms of species composition, carbon storage, and biophysical functioning. Often, significant areas of forest are obscured by clouds or are under reduced solar illumination conditions, which limit acquisition of optical satellite data. Synthetic aperture radar (SAR) images, however, can be acquired under these conditions. Several SAR image data sets were acquired over the Northern Experimental Forest near Howland, Maine as part of the Forest Ecosystem Dynamics-Multisensor Aircraft Campaign. A SAR data processing and analysis sequence, from calibration through classification, is described. The usefulness of multifrequency temporal polarimetric SAR image data for identifying ecosystem classes is discussed. Our results show that with principal component analysis of temporal data sets (winter and late summer) SAR images can be classified into general forest categories such as softwood, hardwood, regeneration, and clearing with better than 80% accuracy. Other nonforest classes such as bogs, wetlands, grass, and water were also accurately classified. Classifications from single date images suffered in accuracy. The winter image had significant confusion of softwoods and hardwoods with a strong tendency to overestimate hardwoods. Modeling results suggest that increased double-bounce scattering of the radar beam from conifer stands because of lowered dielectric constant of frozen needles and branches was the contributing factor for the misclassifications.

New approaches in interferometric SAR data processing

It is known that interferometric synthetic-aperture radar (SAR) images can be inverted to perform surface elevation mapping. Among the factors critical to the mapping accuracy are registration of the interfering SAR images and phase unwrapping. A registration algorithm is presented that determines the registration parameters through optimization. A figure of merit is proposed that evaluates the registration result during the optimization. The phase unwrapping problem is approached through a new method involving fringe line detection. The algorithms are tested with two SEASAT SAR images of terrain near Yellowstone National Park. These images were collected on SEASAT orbits 1334 and 1420, which were very close together in space, i.e. less than 100 m. >

Multistage imaging process in digital SAR imaging

Synthetic aperture radar (SAR) is a type of imaging radar which has high spatial resolution, but the digital imaging processing of SAR data requires a large amount of computation, making real-time imaging difficult. Owing to the fact that different kinds of terrain structure and artificial target require different spatial resolutions, the idea of imaging in multistages to reduce the computation requirement arises.In the paper, the fundamental theory of the multistage imaging process is described. The problems peculiar to this process are discussed, such as the autoadaptation of spatial resolution, and the mosaic of images formed from different stages of the imaging process. The computation requirement of the multistage imaging process is also roughly estimated in the paper, and an experimental software system and results are described.

Knowledge-Based SAR Processing and Geocoding: The Elementary Components of the German Processing and Archiving Facility for High Throughput and High-Precision Processing of ERS-1 SAR Data

Future microwave sensors such as the active microwave instrument (AMI) of the first European remote sensing satellite (ERS-1) to be launched in 1990 will be increasingly conducted in an operational mode. This fact implies an increased amount of synthetic aperture radar (SAR) data to be processed systematically, and, furthermore, combines with the growing needs of the user community in terms of various product levels, adequate production, and organization schemes. Among these needs are the requirements regarding much improved radiometric and absolute geometric accuracy of the generated SAR images. Therefore, an end-to-end SAR processing system has been designed that is significantly different from existing ones. The challenging requirements for high precision combined with high throughput of the generated products will be met by two systems: the knowledge-based intelligent SAR processor (ISAR) and the geocoding system. They represent the backbone of a distributed computer network engaged in SAR processing and image restitution within the German Processing and Archiving Facility (D-PAF) for ERS-1, which shall be built up and operated by the German Aerospace Research Establishment (DFVLR). This paper describes the requirements for the system as well as the specific hardware and software concepts.

Concepts and techniques for real-time optical synthetic aperture radar data processing

The paper discusses the processing of synthetic-aperture-radar (SAR) data from an optical perspective, with emphasis on real-time operations. To appreciate the problem of storing and processing the large quantity of data derived from recent, and projected, satellite-borne SAR missions a brief review of optical and digital techniques is presented. It is evident that there are still severe difficulties to be overcome in achieving real-time processing of satellite-borne SAR data with present digital electronic systems. In the paper several specific optical solutions to the data processing bottleneck are examined in detail, all are based on charge coupled devices (CCDs) configured to perform multichannel processing integrated with a variety of acoustooptic architectures. These systems have the potential to rival the performance of present digital electronic systems and offer substantial reductions in size, weight and power consumption. With future increases in SAR data throughput requirements in a wide range of applications it is argued that both present and future optical systems can offer a cost-effective processing facility which may complement digital electronic computers.

Review Article. Theory of digital imaging from orbital synthetic-aperture radar

Abstract Digital synthetic-aperture radar (SAR) imaging techniques have previously only been reported in the literature in a fragmentory manner. This article presents a comprehensive review of the theory of digital SAR imaging from Earth-orbiting satellites. The digital SAR imaging process is explained, including a discussion of various aspects which are specific to satelliteborne SAR. A number of relevant digital-processing techniques are reviewed and it is shown how these techniques may be applied to the processing of digital SAR data. The range migration problem is discussed and various techniques for overcoming it are presented. The paper should be useful not only to the designer of SAR processors, but also to the user of digital SAR data and images.

COMPARISON OF DIFFERENT SIGNAL AVERAGING METHODS TO IMPROVE THE SNR FOR THE NDT OF COARSE GRAINED MATERIALS NONDESTRUCTIVE TESTING COMMUNICATIONS

Abstract Four different signal-averaging methods for NDT of coarse grained materials based on the concept of synthetic aperture radar data processing are compared. Experiments with 1.8 MHz vertical longitudinal wave and 45° shear wave insoni-fication demonstrate that, the spatial RF-averaging with TOF-correction is the most powerful one.