Besides traditional remote sensing based on synthetic aperture radar (SAR) satellites that deliver high-resolution and well-georeferenced images from Earth’s surface, there is a big and steadily increasing need for continuous observation of small local areas that cannot be satisfied by the current satellite programs. In contrast to the aforementioned monostatic satellite missions, bistatic configurations employing satellites of opportunity as illuminators and locally separated stationary (passive) receivers observing the local scene of interest feature some attractive benefits like moderate costs and short repeat intervals. In this letter, we highlight the challenges of imaging radar using geostationary satellites as transmitting sources. As an example, data from an experiment of this bistatic configuration obtained with a low-cost receiver system is analyzed and presented. For comparison, the parameters and results of an experiment using the high-resolution SAR satellite PAZ as a transmitter are also shown.

Image registration is a crucial step in interferometric synthetic aperature radar (InSAR) and in SAR tomography. Generally, a displacement of the sensors, e.g. due to different flight tracks, causes an image distortion that is dependent on the terrain height that is being observed. While ground truth digital elevation map (DEM) data are often available to roughly compensate this distortion, there are application scenarios where the acquisition paths are too irregular or DEMs are not available. In such cases, image registration via image processing is a suitable choice. While the SAR community prefers patch-based correlation techniques, the computer vision community has investigated the same issue from technically different points of view. In this article, we study the performance of correlation-and computer vision-based image registration techniques for the image registration problem in SAR, in particular in airborne SAR without ground truth. We show that computer vision algorithms can outperform correlation-based techniques.

Deep learning models have achieved remarkable success in many different fields and attracted many interests. Several researchers attempted to apply deep learning models to Synthetic Aperture Radar (SAR) data processing, but it did not have the same breakthrough as the other fields, including optical remote sensing. SAR data are in complex domain by nature and processing them with Real-Valued (RV) networks neglects the phase component which conveys important and distinctive information. A Complex-Valued (CV) end-to-end deep network is developed in this study for the reconstruction and classification of CV-SAR data. Azimuth subaperture decomposition is utilized to incorporate physics-aware attributes of the CV-SAR into the deep model. Moreover, the correlation coefficient amplitude (Coherence) of the CV-SAR images depends on the SAR system characteristics and physical properties of the target. This coherency should be considered and preserved in the processing chain of the CV-SAR data. The coherency preservation of the CV deep networks for CV-SAR images, which is mostly neglected in the literature, is evaluated in this study. Furthermore, a large-scale CV-SAR annotated dataset for the evaluation of the CV deep networks is lacking. A semantically annotated CV-SAR dataset from Sentinel-1 Single Look Complex StripMap mode data (S1SLC_CVDL dataset) is developed and introduced in this study. The experimental analysis demonstrated the better performance of the developed CV deep network for CV-SAR data classification and reconstruction in comparison to the equivalent RV model and more complicated RV architectures, as well as its coherency preservation and physics-aware capability.

Despite the state-of-the-art performance of the deep learning methods for Synthetic Aperture Radar (SAR) data classification, the Real-Valued (RV) networks neglect the phase component of the Complex-Valued (CV) SAR data and lose a lot of useful information. CV deep architectures have been developed in the recent years to exploit the amplitude and phase components of the CV data, in different fields. However, the superiority of CV models over RV models are proved to be different for each application, and more investigation into the advantages and disadvantages of implementing CV models for SAR data classification is necessary. In this study, the performance of the CV Convolutional Neural Network (CV-CNN) for Polarimetric SAR (PolSAR) data classification is compared with its RV equivalent network, in different contexts.

With the start of the Spanish PAZ system, another earth observation satellite has become available to the scientific community. Following the launch of the PAZ science phase, we performed a number of ground experiments using different modes of the satellite SAR instrument, measuring the transmitted radar signal as well as its ground reflections using the HITCHHIKER receiver. The data acquired in these experiments is analyzed and used in collaboration with the PAZ calibration team at Instituto Nacional De Técnica Aerospacial (INTA) to characterize the PAZ instrument, thus verifying the system calibration. Furthermore, we obtained bistatic radar images from the data of the HITCHHIKER ground receiver.

Real-time imaging products using Spaceborne Trinodal Pendulum synthetic aperture radar formation can provide valuable information in certain applications. The onboard orbit determination data of the spaceborne SAR platform is essential for the SAR imaging procedure. For real-time SAR imaging, the onboard orbit determination data is relatively low in accuracy compared with the orbit data obtained by off-line processing for the focusing of SAR data. The influence of errors in onboard real-time orbit determination data on SAR image quality should be considered. This paper proposes a Monte Carlo simulation model for inspecting the influence of onboard orbit determination data on imaging quality. This simulation model and its result may be helpful for the development of SAR real-time imaging focusing on providing terrain change information in a short time.

This paper presents a new bistatic point target reference spectrum. It is derived by using the 2-D principle of stationary phase which is first applied in the synthetic aperture radar (SAR) community. The spectrum contains two hyperbolic range-azimuth coupling terms and thus is very similar to the monostatic spectrum. It shows the characteristic of the conventional monostatic SAR besides an additional azimuth scaling term. Therefore, it makes the common Doppler-based monostatic processing algorithms readily suitable to handle the Bistatic SAR (BiSAR) data in the moderate-squint azimuth-variant configurations with two moving platforms. Based on the spectrum, two Doppler-based monostatic imaging algorithms [i.e., range-Doppler algorithm (RDA) and chirp-scaling algorithm (CSA)] are readily implemented to deal with the moderate-squint azimuth-variant BiSAR data. Compared to the processing procedure for the monostatic SAR, the RDA and CSA for the BiSAR need only the adjustment of Doppler parameters. Finally, the potential and limitation of the spectrum are analyzed, and the real raw data in the spaceborne/airborne configurations are used to validate the proposed spectrum and processing methods.

A lot of bistatic experiments have recently been performed by different researchers to show the differences between monostatic and bistatic SAR. The acquired data was needed to verify the developed bistatic processing algorithms. To extend the conventional bistatic SAR experiments, we investigated whether bistatic systems can be used in the field of bistatic interferometry and polarimetry, also shown by [3]. For this purpose we have used our stationary receiver system together with TerraSAR-X as transmitting satellite. This paper describes the experiments and shows some results we obtained using single and repeat pass SAR configurations.

In this paper, the development of a stationary SAR receiver system using TerraSAR-X as transmitter is described. First the bistatic geometry and expected resolution are considered. After giving an overview of the hardware setup, the expected performance of the system is evaluated. The paper ends with the processed results of a measurement campaign performed in summer and fall 2009, and a comparison with the monostatic data acquired by the TerraSAR-X satellite.

The conventional monostatic SAR shows a limitation of achieving a high azimuth (angular) resolution if a forward-looking geometry is used. Bistatic SAR offers a possibility of the forward-looking formation image, e.g. one platform operates as a separated illuminator while another works in a forward-looking mode. In this special bistatic configuration, the forward-looking beam will introduce two problems. The first one is the significant Doppler shift, which will produce the range-azimuth coupling. The second one is that the targets located at symmetrically about the flight path of the forward-looking platform have the same antenna-to-target range which would cause the range migration ambiguity of the receiver. This paper will develop a mathematical model to describe the Doppler characteristic of bistatic forward-looking SAR (BFLSAR). Based on this model, the previous bistatic point reference spectrum (BPTRS) can be applied. Using the BPTRS, a modified range-Doppler algorithm is proposed to handle the two problems and focus BFLSAR data in the azimuth-invariant configuration. Finally, simulation experiment is used to validate the proposed model and processing approach.

In this paper, we present a motion error model for a Frequency-Modulated Continuous-Wave (FMCW) SAR system, and analyze the characteristics of the intrapulse motion error. Furthermore, we develop an effective compensation approach to handle motion errors based on our previous result. Finally, we validate the formulated signal model and compensation method by using simulated FMCW SAR data.

The spatial separation of the transmitter and the receiver in bistatic synthetic aperture radar (SAR) enables a variety of data acquisition geometries to achieve benefits like the increased information content of bistatic SAR data. In the case of hybrid bistatic SAR constellations where the transmitter is spaceborne and the receiver is onboard an aircraft, one has to deal with a huge discrepancy between platform velocities. This paper presents bistatic spaceborne/airborne SAR experiments, where the radar satellite TerraSAR-X is used as a transmitter and the airborne SAR sensor Phased Array Multifunctional Imaging Radar (PAMIR) of the Fraunhofer Institute for High Frequency Physics and Radar Techniques (FHR) is used as a receiver. Both sensors are equipped with phased-array antennas, which offer the possibility of beam steering and could be used for the first time for the “double sliding spotlight mode.” In this mode, the space- and airborne sensors operate with different sliding factors (ratio between footprint and platform velocity). The performance of two different experiments is analyzed, and the novel double sliding spotlight mode is presented. This paper describes the experimental setups, the synchronization system, and the data acquisition. The image results were processed by a modified backprojection algorithm and a frequency-domain algorithm. The analysis of the final bistatic images comprises the spatial resolution and the scattering behavior of selected objects. Parts of the bistatic SAR images are compared with the corresponding monostatic images of PAMIR and TerraSAR-X. It will be shown that hybrid bistatic SAR is a worthwhile and helpful addition to current monostatic SAR.

The combination of frequency-modulation continuous-wave (FMCW) technology and synthetic aperture radar (SAR) promises a lightweight, cost-effective, and high-quality imaging sensor for remote sensing. However, the long signal duration time leads to the failure of the conventional start/stop approximation of the pulsed SAR. In this paper, a signal model is proposed to address the effects of the continuous motion during the transmit time on the echoed signal. Based on the model, an analytical point target reference spectrum is derived. From the spectrum, it will be seen that the continuous motion introduces an additional range-azimuth coupling term and a range walk term compared with the conventional pulsed SAR. The range walk term is well known, whereas the foregoing range-azimuth coupling term is formulated for the first time in the FMCW SAR community. For the squint and spotlight modes, these range walk and range-azimuth coupling terms might significantly degrade the image quality. In this paper, based on the proposed analytical signal model, we further discuss the application of the wavenumber domain algorithm for the FMCW SAR data. In addition, different approximations of the Stolt mapping are made to highlight the effect of the range-dependent higher-order range-azimuth coupling terms on the 2-D impulse responses. Finally, X-band simulated experiments and Ka-band real FMCW SAR data are used to validate the signal model and the processing method.

This paper presents a frequency-domain-based focusing algorithm for the bistatic synthetic aperture radar (BiSAR) data in airborne/stationary configuration. In this bistatic configuration, only the moving platform contributes to the azimuth modulation, whereas the stationary platform introduces a range offset (RO) to the range migration trajectories of targets at the same range. The offset is determined by the azimuth position of different targets with respect to the stationary platform. Since the RO is position dependent, monostatic SAR imaging algorithms are not able to focus the bistatic data collected in this configuration. In this paper, an analytical bistatic point-target reference spectrum is derived, and then, a frequency-domain-based algorithm is developed to focus the bistatic data. It uses an interpolation-free wavenumber-domain algorithm as a basis and performs a range-variant interpolation to correct the position-dependent RO in the image domain after coarse focusing. The proposed algorithm is validated by the simulated data and the real BiSAR data acquired by the Forschungsgesellschaft fu¿r Angewandte Naturwissenschaften's airborne SAR system, PAMIR, in December 2007. In this BiSAR experiment, an X-band transmitter was stationary operated on a hill with PAMIR as the receiver mounted on a Transall C-160.

This paper focuses on the bistatic synthetic aperture radar (SAR) data processing in a spaceborne/airborne hybrid bistatic configuration. Due to the extreme differences in platform velocities and slant ranges, the airborne system operates in the inverse sliding-spotlight mode, while the spaceborne system works in the sliding-spotlight mode to achieve a tradeoff between azimuth scene size and azimuth resolution. In this extreme bistatic configuration, our original bistatic formula shows a limitation of accurately describing the bistatic point-target reference spectrum, owing to the assumption of equal contributions of transmitter and receiver to the total Doppler spectrum. We extend our previous formula using the weighting operation where the weighting factor is the ratio of the azimuth time-bandwidth product (TBP) of the platform to the total azimuth TBP. In this paper, the bistatic-deformation and azimuth-dependent range-cell-migration terms were removed with phase multiplications performed blockwise in range-azimuth subsections. The remaining quasi-monostatic term shows the characteristic of the conventional monostatic SAR besides an additional azimuth-scaling term. For the monostatic characteristic, any precision monostatic SAR processing algorithms can handle. In this paper, we prefer the wavenumber-domain algorithm (also known as Omega-K), since it can accurately correct the range dependence of the range-azimuth coupling, as well as the azimuth-frequency dependence. For the azimuth-scaling term, an inverse scaled Fourier transformation is performed to correct it. Finally, a hybrid spaceborne/airborne simulation experiment is conducted to validate the proposed processing procedure.

This paper discusses the processing method for bistatic SAR data in the constant-offset configuration. The constant-offset configuration is also known as the azimuth stationary or invariant configuration where transmitter and receiver follow each other, moving on identical velocity vector. In this paper, the proposed processing method for bistatic SAR data is based on Loffeld's bistatic formula that consists of two terms, i.e., the quasi-monostatic (QM) term and bistatic-deformation (BD) term. Our basic idea is to linearize the aforementioned two terms and then incorporate the BD term into the QM term to obtain an analogous monostatic spectrum. Based on the new spectrum, any efficient 2-D frequency or range-Doppler domain processor can easily be employed to process the bistatic data, where the Doppler phase parameters of the processor need to be adjusted. In this paper, we concentrate on the application of chirp-scaling-algorithm (CSA) processor. In addition, a bistatic-motion error model is developed where the position deviations of the two platforms are simplified as the bistatic slant-range displacement in the zero Doppler plane. Using this model, the monostatic motion-compensation technique is applied and integrated into CSA to compensate the trajectory deviations of transmitter and receiver. Finally, real and simulated data are used to validate the proposed processing method.

Image registration is known as an important part of generating Digital Elevation Models (DEM) with Interferometric SAR (InSAR) processing and is one of the critical preprocessing steps in remote sensing. It is used in the formation of 3-D models based on 2-D images taken at different view points as well as for mosaicking applications. The paper gives an overview of the information measures which can be used for automatic generation of reference points und finding the correspondences in the second image. The approach is validated with simulated and real image pairs originate from the TerraSAR-X satellite. Additionally to the classic correlation based methods, we will employ, compare and combine theoretical methods, based on information theory, such as mutual information, alignability in conjunction with automated bin size determination to achieve optimally. Considering the co-registration of single look complex SAR data, where correlation approaches are standard, the exploitation of similarity measures and transformation, based on information theory, is rather novel. Comparing these novel approaches with standard references with respect to quality and quantitative measures, will broaden the scientific understanding, and, furthermore, provide new insights concerning co-registration techniques for interferometric applications.

In the SAR community there are many methods offered for solving the problem of unwrapping the phase obtained from a noisy interferometric SAR (InSAR) image [2-5]. Generally a Kalman filter is a powerful tool to obtain accurate model based estimates out of different sources of information. All the given information is fused in a efficient way and also the noise is cancelled optimally. Because of this a Kalman filter based data fusion approach to unwrap and simultaneously filter the phases of interferometric SAR images is developed. The data fusion concept exploits phase information, extracted from the complex interferogram rather than from the phase image and fuses that information with phase slope information extracted from the power spectral density of the interferogram. The paper explains a Kalman filter method for phase unwrapping purposes and discusses the pros and cons of this approach.

A crucial problem in most airborne Synthetic Aperture Radar (SAR) systems is the compensation of motion errors to prevent the image degradation. If these errors are not compensated, some undesired effects will appear, such as loss of geometric resolution and radiometric accuracy, reduction of image contrast, azimuth ambiguities and strong phase distortions. For the bistatic airborne SAR systems, the motion errors become more complex since two separate trajectory deviations contribute to these errors. This paper proposes an approach that will compensate the bistatic motion errors in the frequency domain.

The individual azimuth contribution of transmitter and receiver phase terms has been optimized by weighting them unequally based on a weighting factor mu, in Loffeld's bistatic formula (LBF). Analytical results are verified with the simulations.

This paper concentrates on the bistatic SAR (BiSAR) signal processing for the spaceborne/airborne hybrid bistatic configuration. A bistatic SAR experiment based on this hybrid configuration is being planned in cooperation with FGAN/FHR and DLR. Due to the extreme differences of the platform's velocities and altitudes, the spaceborne system works in the sliding spotlight mode, while the airborne system operates in the inverse sliding spotlight mode. In this paper, our previous work (i.e. ISFT) is applied to focus the hybrid bistatic SAR data based on the extended Loffeld's Bistatic Formula (ELBF).

The visualization of synthetic aperture radar (SAR) data involves the mapping from high dynamic range amplitude values to gray values of a lower dynamic range display device. This dynamic range reduction process controls the amount of information in the displayed result and is therefore an important part of each SAR visualization system. Interactive systems provide the user with immediate feedback on the changes of the reduction method and its parameters. In this letter, we examine different dynamic range reduction techniques known from the tone mapping of optical images. The techniques are analyzed, regarding their applicability to SAR data, and incorporated into our interactive visualization framework based on programmable graphics hardware.

A bistatic point target reference spectrum (BPTRS) based on Loffeld's bistatic formula (LBF) is derived in this letter. For LBF, the same contributions of the transmitter and receiver to the total azimuth modulation are assumed. This assumption results in the failure of LBF in the extreme configuration (i.e., spaceborne/airborne configuration). For general bistatic configurations, the azimuth modulations are unequal for the transmitter and receiver due to the different slant ranges and velocities. Therefore, the azimuth time-bandwidth products (TBPs) from the transmitter and receiver are different; in some cases (e.g., spaceborne/airborne case), one of them might be very small, which might even result in a serious error of the principle of stationary phase. This letter uses TBP to weight the azimuth phase modulation contributions of the transmitter and receiver to the common azimuth spectrum to approximately obtain the point of stationary phase of the total azimuth phase history. Simulations show that the proposed BPTRS can work well for spaceborne/airborne configurations.

This paper considers the problem of unwrapping the phase image obtained from a noisy interferometric synthetic aperture radar (InSAR) image. The implicit nonlinearity of the problem is reflected, as well as the drawbacks of this nonlinearity on the performance of phase unwrapping approaches. Some general concepts concerning basic estimation techniques are shortly reviewed. On this background, a Kalman filter-based data fusion approach to unwrap and simultaneously filter the phases of InSAR images is developed. The data fusion concept exploits phase information extracted from the complex interferogram rather than from the phase image and fuses that information with phase slope information extracted from the power spectral density of the interferogram.

For modern SAR data acquisition, bi- and multistatic SAR missions become increasingly important. Established methods for processing monostatic SAR signals need to be adapted to new algorithms for signal processing. In order to support the evolution and development of these new algorithms simulated SAR raw data of arbitrary bi- and multistatic SAR scenarios are essential. This paper refers to a modular SAR simulator, which is able to simulate complex bi- and multistatic SAR scenarios. It focuses on the geometrical simulation approach of the simulator and the computationally intensive synthesis of SAR raw data. The main part descripts the parallel implementation of the radar lobe footprint scan and of the succeeding SAR raw data generation executed on a compute cluster. An example will be shown, which compares the simulation of the same SAR scenario on three different compute systems and their runtimes.

Synthetic aperture radar data presents specific problems for interactive visualization. The high amount of multiplicative speckle noise has to be reduced. The high dynamic range of the amplitude data must be mapped to the lower dynamic range of display devices in a way that makes image features appropriately visible. In addition to interactive navigation in the data, it is desirable to allow interactive selection of despeckling and dynamic range reduction methods and adjustment of their parameters. Graphics processing units (GPUs) can be seen as ubiquitous parallel coprocessors with extreme computational power. In this paper, we propose a GPU-based framework for interactive visualization of SAR data. Data management techniques are used to make full use of the GPU. We reworked well-known despeckling and dynamic range reduction techniques for the GPU programming model and implemented them in our framework. Both navigation in large data sets and adjustment of processing parameters are fully interactive.

In addition to the promising and well known features in the field of monostatic interferometry and polarimetry, TanDEM-X can also be used for bistatic purposes. In this Helix orbit concept one TerraSAR-X satellite (TSX) serves as transmitter whereas the reflected signal is received by the transmitter as well as by an almost identical satellite (TDX), which has a similar orbit as the first one. This paper focuses the bistatic possibilities and restrictions of this space borne formation. In the bistatic mode of TanDEM-X it is possible to receive the echoes simultaneously by the two receiving sensors. From this it follows that there is no temporal decorrelation. For having an idea of how this configuration works in the bistatic mode and how the bistatic raw data looks like, we simulated realistic orbit data. Using zero Doppler steering we generated raw data which was processed by the bistatic processing approach of our institute. Another basic issue of the paper is the bistatic parameter estimation for this special configuration.

Common efficient SAR processing algorithms are based on nominal operational conditions. Unfortunately, due to atmospheric turbulences and maneuvering errors, these conditions are often violated in real SAR systems. Hence, a crucial problem in most airborne SAR systems is the compensation of motion errors; if not corrected, the image quality will considerably degrade. A first-order motion compensation (MoCo) technique was developed at our institute, based on a precise knowledge of the position and the velocity of the transmitter and the receiver. The problem arose while proceeding with our processing algorithm, since the reconstructed image was better focused but not completely focused. Our paper proposes a second-order MoCo technique that will considerably improve the reconstruction of the SAR image. While the first-order MoCo considered the range and azimuth times, the second-order MoCo approximation will consider the frequencies. Experiments with different sets of bistatic airborne SAR data are performed based on this solution, and some promising results are given.

Bistatic synthetic aperture radar (SAR) processing requires precise knowledge about geometrical parameters of the flown bistatic constellation, whereas estimation of these parameters is even more important than in the monostatic case. As it is impossible to separate the individual semimonostatic parameters from the bistatic raw data, the searched parameters are derived from the tracks of the moving platforms. For this reason, global positioning system (GPS) and inertial navigation system (INS) position and velocity data of transmitter and receiver are combined in an optimal way by a Kalman filter approach. As a consequence of model-based interpolation, we can easily determine varying parameters like Doppler centroid frequency, azimuth velocity, and the bistatic parameters a2and a0referring to the illuminated scene at each time instant. Accurately determined position and velocity of the transmitter and receiver enable a first-order bistatic motion compensation (MC), which is also described in this paper. In verifying our approach, GPS/INS tracks and raw data of a bistatic airborne SAR experiment flown in 2003 were used, where the data were provided by Forschungsgesellschaft fu umlr Angewandte Naturwissenschaften e.V., Wachtberg, Germany. The focusing was done by a scaled inverse Fourier transformation processor for nearly parallel trajectories for transmitter and receiver. This paper focuses on analyzing the trajectories and antenna beams of bistatic missions to obtain accurate processing parameters and MC functions.

Following the goals of our cooperation treaty between FGAN and ZESS (University Siegen), we work closely together on the complex research field of bistatic exploration. Single tasks of the overall topic are for instance experimental missions, processing, image formation, position- and attitude estimation, synchronisation, simulation, parameter estimation, and visualization. This paper presents an overview about the common projects of FGAN, ZESS, and FOMAAS.

In this paper, the geometrical setup of an airborne/spaceborne SAR experiment is described. This experiment is planned in cooperation of ZESS (University of Siegen) and FGAN (Forschungsgemeinschaft fur angewandte Naturwissenschaften) [1]. While TerraSAR-X will be used as SAR illuminator, the reflected pulses will be received by FGAN's X-band system PAMIR. Due to the high difference between the velocities of the platforms, both systems must perform antenna steering to achieve an appropriate scene length in azimuth.

Bi- and multistatic SAR missions are becoming increasingly important for the SAR data acquisition. Established methods for processing monostatic SAR signals and for mission planning have to be adapted to the bi- and multistatic case. To support this evolution, a suitable flexible and powerful simulation tool is essential, which is able to handle such complex scenarios and to provide corresponding simulation data. This paper presents a new simulator architecture. In particular, the modular approach to implement and to simulate this kind of bi- and multistatic SAR scenarios is discussed and an example is given.

This paper presents a bistatic focusing solution for the general case, when transmitter and receiver trajectories move along non parallel trajectories with different velocities. Processing in the general case turns out to be additionally truly azimuth time variant. This problem is solved by implementing a novel 2D inverse scaled FFT algorithm. In the second part of the paper the focused bistatic SAR image bistatic processing quality will be evaluated by measuring the geometric registration, amplitude and resolution, ISLR and PSLR of simulated point targets.

Bistatic synthetic aperture radar (SAR) missions have become attractive in the last years, because of their higher degree of freedom in choosing transmitter and (passive) receiver motion trajectories. In order to take advantage of this increased imaging flexibility, adequate processing algorithms have to be developed, implemented and verified with experimental data. Currently some promising approaches have been published in this area. A further step in improving the focusing results within a bistatic SAR constellation where transmitter and receiver are mounted on different platforms essentially comprises the bistatic motion compensation (MC). We present a geometrical MC approach which requires high accurate position and velocity information of transmitter and receiver.

This paper presents a bistatic focusing solution for the general case, when transmitter and receiver trajectories move along nonparallel trajectories with different velocities. The approach in this paper is based on the point target reference spectrum for an arbitrary bistatic configuration, derived from our previous publications. Based on various simulations, the validity of the formula for both airborne and spaceborne configurations is demonstrated. Focusing for special bistatic azimuth time-invariant configurations, "tandem" and "translationally invariant" constellations are accomplished. All focusing algorithms have been developed in an interactive data language and verified with adequate simulation results. The bistatic algorithm was further successfully applied to real bistatic data acquired by the German Research Establishment for Applied Natural Sciences' PAMIR and AER-II synthetic aperture radar systems. Processing in the general case turns out to be additionally truly azimuth time variant. It is solved by implementing a novel two-dimensional inverse-scaled fast Fourier transform algorithm

Although this work is a bit theoretical and contains lots of derivations, it leads to very explicit practical results in bistatic focusing. Our approach is based on Loffelds bistatic formula describing the point targets reference spectrum for arbitrary bistatic configuration. Based on various simulations the validity of LBF for both airborne and spaceborne configurations is demonstrated. Focusing for special bistatic configurations like: Tandem and Translationally Invariant constellations is considered. The focusing for the Tandem configuration is solved analytically. Focusing in the TI case is realized by blockwise processing. All focusing algorithms are developed in IDL and adequate simulation results are presented. In the end of the paper outlines the conceptual solution of the most difficult bistatic General Case and presents some first focusing results.

With regard to multistatic configurations such as the Interferometric Cartwheel or the Interferometric Pendulum the need of satellite positioning with a high accuracy is increasing. Not only for baseline estimation but also for image focusing the precise knowledge of the antennas' absolute and relative positions is essential. This paper suggests a first approach and a possible way of data enhancement based on realistic orbit models

To achieve good on-board SAR processing results a precise knowledge of the position of the concerned satellites is essential. For this reason we develop real-time orbit estimation and calibration algorithms which in spite of the small time frame improve the position estimates in an efficient way. Considering future satellite cluster missions (e.g. Cartwheel, Pendulum, Techsat 21, ...), it will be possible to reduce the computing time by splitting of the processing load onto several algorithms that can be implemented in the individual satellites' hardware. The satellites can be considered as a distributed sensor network, which individual (sensor-) nodes have local processors that are used to calculate state estimates using all available data (we want to combine GPS derived and intersatellite distance measurements). A node to node communication is necessary to ensure that no information is lost in order to yield the best possible estimates. The paper specifies advantages and disadvantages of decentralized estimation and compares computational burden and estimation accuracy of decentralized and standard Kalman filter approaches and also analyzes the communication overhead

The paper derives a vectorial model for expressing transmitter and receiver trajectories for arbitrary transmitter and receiver motion (nonidentical velocity vectors) in a bistatic synthetic aperture radar constellation. The point target response is first modeled in the space-time domain and then transformed to the frequency domain by the method of stationary phase giving the point target reference spectrum. In the reference spectrum, two phasor functions can be identified, the first one resembling some quasi-monostatic contribution and the second one being a bistatic deformation phasor transforming into an elliptic arc in the spatial domain. The multiplication of the two phasors in the frequency domain transforms into a convolution like operation in the space-time domain, indicating that the bistatic dataset can be expressed as a convolution like (range and azimuth variant) mapping of a monostatic dataset. In this regard, the paper extends the solution for the constant offset case known from the geophysical literature (associated with "Rocca's smile operator") showing that this case is a specialization of the more general one considered in this work.

This paper suggests a way to calculate a "realistic" orbit model. A satellite is always subject to several perturbations caused by inhomogeneities in the Earth's gravitational field, atmospheric drag, solar pressure and further stochastic influences. For most of these perturbations, especially for gravitation and atmospheric drag there are models existing, whereas in this paper we will confine ourselves to the gravitational influence.

Former analysis revealed that the vertical height accuracy of digital elevation models (DEMs) generated by synthetic aperture radar interferometry (InSAR) mainly depends on the precise knowledge of baseline length, baseline tilt angle and interferometric phase offset. Recently slightly different formations of passive microsatellites which simultaneously receive signals transmitted from an active spaceborne radar system and have near circular orbits were proposed. This paper presents the sensitivity of DEMs generated from such constellations to important interferometric parameters. PALSAR (ALOS), ASAR (Envisat) and TerraSAR-X are considered as illuminating SAR systems and a three dimensional SAR geometry that includes an ellipsoidal Earth geometry (WGS84) is applied.

The paper derives a vectorial model for expressing transmitter and receiver trajectories for arbitrary transmitter and receiver motion (nonidentical velocity vectors) in a bistatic syn- thetic aperture radar constellation. The point target response is first modeled in the space-time domain and then transformed to the frequency domain by the method of stationary phase giving the point target reference spectrum. In the reference spectrum, two phasor functions can be identified, the first one resembling some quasi-monostatic contribution and the second one being a bistatic deformation phasor transforming into an elliptic arc in the spatial domain. The multiplication of the two phasors in the fre- quency domain transforms into a convolution like operation in the space-time domain, indicating that the bistatic dataset can be ex- pressed as a convolution like (range and azimuth variant) mapping of a monostatic dataset. In this regard, the paper extends the solu- tion for the constant offset case known from the geophysical liter- ature (associated with Rocca's smile operator) showing that this case is a specialization of the more general one considered in this work.

We derive models and relations which might be useful for the calibration and orbit determination of cartwheel configurations such as proposed by Massonnet (2001). The aim is to develop a method to obtain precise position and velocity estimates for each individual cartwheel satellite from noisy and erroneous measurements (e.g. GPS). For later interferometric SAR processing precise estimates of the baseline vectors between the satellites are essential, because every error in the position of the antenna leads to a multiple error in height of the digital elevation model. The whole approach is based on state space arguments giving rise to Kalman filtering methods.