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Through formation flying, the distributed spaceborne SAR(synthetic aperture radar) system can increase the number of spatial degree of freedoms (DOFs) and provide flexible multi-baselines for SAR-GMTI (ground moving target indication), which improves the system performance. This paper proposes an a priori knowledge-based adaptive clutter cancellation and moving target detection technique applied to the distributed spaceborne SAR-GMTI systems. Firstly, the adaptive clutter cancellation technique is exploited to suppress the ground clutter. A priori knowledge, such as road network information, is integrated to the adaptive clutter cancellation processor to reduce any moving target steering vector mismatch. Secondly, adaptive matched filter (AMF) and adaptive beamformer orthogonal rejection test (ABORT) are exploited as adaptive detection techniques for moving target detection. Due to the dense road network, the moving target steering vector estimation may be ambiguous for the different position and orientation of the roads. The multiple hypothesis testing (MHT) technique is proposed to detect the moving targets and resolve the potential ambiguities. A scheme is exploited to detect, classify, and relocate the moving targets. Finally, simulation experiments and performance analysis have demonstrated the effectiveness and robustness of the proposed technique.

Skilled at representing the chirp signal, Radon-Wigner distribution (RWD) plays an important role in parameters estimation for moving targets. By searching for the best time-frequency angle, the conventional RWD estimation method suffers from the tradeoff between the estimation accuracy and computation complexity. In this paper, an efficient RWD estimation method is proposed by exploiting the geometry information in the RWD domain, and extensive parameters searching is replaced by only two parameters computation, then the computation complexity is effectively reduced from O(MN) to O(2N). The proposed efficient RWD method is applied in moving targets velocity estimation, which is emerging issue for smart city. The non-ideal factors in real circumstance are considered, and three robust methods are proposed to improve the estimation accuracy by exploiting the geometry information in the RWD domain further. A clutter suppression RWD (CSRWD) method is proposed to cancel the clutter but preserve the moving target in the RWD domain, and a learned RWD (LRWD) method is proposed to minimize the estimation error caused by measurement error. Then, CSRWD is combined with LRWD to obtain a unified robust RWD (URRWD), which possesses the advantages of CSRWD and LRWD simultaneously. Simulation and real data processing results validate the proposed methods, and lower implementation complexity is proven under the same accuracy assumption. It can be considered as the geometry information opens a window for the searching-based estimation method to make the original bleak searching process suddenly bright. The concept can also be expanded to the other searching-based estimation methods, such as Radon transform, fractional Fourier transform and so on.

With the maturity of the instantaneous full-polarisation measurement, the instantaneous full-polarimetric system is becoming an important development direction of the polarimetric synthetic aperture radar (POLSAR); however, as an important research branch of the synthetic aperture radar (SAR), the along-track interferometry (ATI) technology for the ground moving target indication (GMTI) is still largely confined to be single polarimetric. In order to facilitate the study of GMTI using a full-polarimetric along-track interferometric SAR (AT-POLINSAR), this study first models the transmitting and receiving signals of AT-POLINSAR and points out its realisability in the existing technical condition of POLSAR. Then, the 6D vector interferometric model for the full-polarimetric echoes is established, where the differences of data processing with the single-polarimetric ATI are analysed. Finally, two simulation methods of the AT-POLINSAR images are given for the generation of signal-level and image-level data, where the results have shown that both the data quality of the interferometric system and its detection performance for moving targets can be improved by the introduction of full polarisation.

This article addresses the problem of clutter cancelation for slowly moving target detection and localization in multichannel passive radar onboard mobile platforms. A post-Doppler space-time adaptive processing (STAP) approach is exploited in the case of an angle-dependent imbalance affecting the receiving channels. While the clutter suppression capability is ensured by the adaptivity of space-time filtering, different solutions are compared, aimed at recovering the detection performance losses associated with channel calibration errors. A space-time generalized-likelihood ratio test (GLRT) scheme is considered, where the steering vector is not specified in the spatial domain, resulting in a noncoherent integration of target echoes across the receiving channels. This is compared with a fully coherent GLRT scheme where echoes from the stationary scene are exploited for the proper calibration of spatial steering vector mismatch. The first scheme proves to be a simple solution for target detection in the passive radar case, offering comparable clutter cancelation capability. The second scheme, at the expense of an additional stage, offers slightly better detection performance and preserves target direction-of-arrival (DoA) estimation capability. Finally, the STAP scheme is employed for the maximum-likelihood estimation of target DoA, evaluating the role of the steering vector calibration against the negative impact of channel imbalance. The effectiveness of the proposed approaches is tested against both simulated and experimental data from a DVB-T-based mobile passive radar.

This paper deals with the problem of detection and direction of arrival (DOA) estimation of slowly moving targets against clutter in multichannel mobile passive radar. A dual cancelled channel space-time adaptive processing (STAP) scheme is proposed, aiming at reducing the system computational complexity, as well as the amount of required training data, compared to a conventional full array solution. The proposed scheme is shown to yield comparable target detection capability and DOA estimation accuracy with respect to the corresponding full array solution, despite the lower computational cost required. Moreover, it offers increased robustness against adaptivity losses, operating effectively even in the presence of a limited set of training data, as often available in the highly non-homogeneous clutter scenarios experienced in bistatic passive radar. The effectiveness of the proposed scheme and its suitability for passive GMTI are demonstrated against both simulated and experimental data collected by a DVB-T-based multichannel mobile passive radar.

This article addresses the problem of direct signal interference (DSI) and clutter cancellation for passive radar systems on moving platforms employing displaced phase centre antenna (DPCA) approach. Attention is focused on the development of signal processing strategies able to compensate for the limitations deriving from amplitude and phase imbalances that affect the two channels employed on receive. First, we show that using the signal received from the illuminator of opportunity as a source for channels calibration might be ineffective when DSI and clutter echoes have different directions of arrival, due to the effect of angle-dependent channel imbalance. Then, a two-stage strategy is proposed, consisting of a preliminary DSI removal stage at each receive channel, followed by a clutter-based calibration approach that basically enables an effective DPCA clutter suppression. Different strategies for channel calibration are proposed, aimed at compensating for potential angle and range-dependent channel errors, based on the maximization of the cancellation performance. Effectiveness of this scheme is shown against the experimental data from a DVB-T based moving passive radar, in the presence of both real and synthetic moving targets.

International audience; When using multichannel synthetic aperture radar (MSAR) to perform moving target detection, the coherence between the received signals is closely linked to the detection capacities of the system. In airborne MSAR context, because of the platform movement, the antenna patterns, as well as the phase shifts between the channels, evolve in different ways during the integration time. In this paper, these dissimilarities are shown to cause a degradation of coherence, and hence of detection capacities. A method to enhance the coherence is then developed. This method is based on the estimation of the steering vector. It is applied on two sets of real data, and the obtained results validate the method.

Tesis (Magister en Aplicaciones de Información Espacial)--Universidad Nacional de Córdoba, Facultad de Matemática, Astronomía, Física y Computación, 2019. Maestría conjunta con el Instituto de Altos Estudios Espaciales "Mario Gulich"-CONAE El foco de este trabajo está puesto en el estudio y desarrollo de técnicas Ground Moving Target Indication (GMTI) aplicadas en imágenes SAR (Synthetic Aperture Radar), destinadas a detectar y estimar parámetros de velocidad de objetos en movimiento, como por ejemplo autos o camiones. Se propone un esquema de procesamiento de bajo costo computacional basada simplemente en transformadas de Fourier y multiplicaciones de exponenciales complejas. La validez y eficiencia del esquema propuesto es estudiado procesando imágenes COSMO-SkyMed (CSK) Single Look Complex (SLC) adquiridas en modo Spotlight sobre países distintos. Los resultados obtenidos verifican la teoría estudiada con su aplicación en datos reales, demostrando de este modo la factibilidad de implementación de técnicas GMTI sobre datos SAR. The focus of this work is on the study and development of Ground Moving Target Indication (GMTI) techniques applied in Synthetic Aperture Radar (SAR) images, aimed at detecting and estimating velocity parameters of moving targets, such as cars or trucks. A low-cost computational processing scheme is proposed based on Fourier transforms and multiplications of complex exponentials. The validity and efficiency of the proposed scheme is studied by processing COSMO-SkyMed (CSK) Single Look Complex (SLC) images acquired in Spotlight mode over different countries. The results obtained verify the theory studied with its application in real data, thus demonstrating the feasibility of implementing GMTI techniques on SAR data. Fil: Testa, Alejandro Iván. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía, Física y Computación; Argentina. Fil: Testa, Alejandro Iván. Universidad Nacional de Córdoba. Instituto de Altos Estudios Espaciales Mario Gulich; Argentina. Fil: Testa, Alejandro Iván. Comisión Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales Mario Gulich; Argentina.

Passive radar has reached a stage of maturity such that it can be mounted on mobile platforms for the purpose of moving-target-detection. However some constraints limit the capability of target detection within the Doppler spread clutter region which arises due to the receiver's movement. Typically employed terrestrial illuminators of opportunity transmit in the Very High Frequency/Ultra High Frequency band, which puts some constraints on the size and number of employed antenna elements. If two antenna elements are employed, the Displaced Phase Center Antenna (DPCA) approach provides a meaningful possibility to suppress the clutter. However, the performance of this clutter suppression technique is severely degraded in case of non-ideal DPCA condition or if the employed channels are not properly calibrated. Here we suggest a technique to re-establish inter-channel calibration based on the Minimum Variance clutter power spectrum estimation. Specifically, we regard the technique as a dedicated adaptive digital calibration stage in order to improve clutter cancellation. The validity of the proposed approach is tested against real data, showing improved clutter cancellation capability.

Synthetic aperture radar (SAR) was first invented in the early 1950s as the remote surveillance instruments to produce high resolution 2D images of the illuminated scene with weather-independent, day-or-night performance. Compared to the Real Aperture Radar (RAR), SAR is synthesising a large virtual aperture by moving a small antenna along the platform path. Typical SAR imaging systems are designed with the basic assumption of a static scene, and moving targets are widely known to induce displacements and defocusing in the formed images. While the capabilities of detection, states estimation and imaging for moving targets with SAR are highly desired in both civilian and military applications, the Ground Moving Target Indication (GMTI) techniques can be integrated into SAR systems to realise these challenging missions. The state-of-the- art SAR-based GMTI is often associated with multi-channel systems to improve the detection capabilities compared to the single-channel ones. Motivated by the fact that the SAR imaging is essentially solving an optimisation problem, we investigate the practicality to reformulate the GMTI process into the optimisation form. Furthermore, the moving target sparsities and underlying similarities between the conventional GMTI processing and sparse reconstruction algorithms drive us to consider the compressed sensing theory in SAR/GMTI applications. This thesis aims to establish an end-to-end SAR/GMTI processing framework regularised by target sparsities based on multi-channel SAR models. We have explained the mathematical model of the SAR system and its key properties in details. The common GMTI mechanism and basics of the compressed sensing theory are also introduced in this thesis. The practical implementation of the proposed framework is provided in this work. The developed model is capable of realising various SAR/GMTI tasks including SAR image formation, moving target detection, target state estimation and moving target imaging. We also consider two essential components, i.e. the data pre-processing and elevation map, in this work. The effectiveness of the proposed framework is demonstrated through both simulations and real data. Given that our focus in this thesis is on the development of a complete sparsity-aided SAR/GMTI framework, the contributions of this thesis can be summarised as follows. First, the effects of SAR channel balancing techniques and elevation information in SAR/GMTI applications are analysed in details. We have adapted these essential components to the developed framework for data pre-processing, system specification estimation and better SAR/GMTI accuracies. Although the purpose is on enhancing the proposed sparsity-based SAR/GMTI framework, the exploitation of the DEM in other SAR/GMTI algorithms may be of independent interest. Secondly, we have designed a novel sparsity-aided framework which integrates the SAR/GMTI missions, i.e. SAR imaging, moving target and background decomposition, and target state estimation, into optimisation problems. A practical implementation of the proposed framework with a two stage process and theoretically/experimentally proven algorithms are proposed in this work. The key novelty on utilising optimisations and target sparsities is explained in details. Finally, a practical algorithm for moving target imaging and state estimation is developed to accurately estimate the full target parameters and form target images with relocation and refocusing capabilities. Compared to the previous processing steps for practical applications, the designed algorithm consistently relies on the exploitation of target sparsities which forms the final processing stage of the whole pipeline. All the developed components contribute coherently to establish a complete sparsity driven SAR/GMTI processing framework.

With the growing number of operating spatial systems, SAR imagery has become a major topic of research in the remote sensing community. In France, most of the research focuses on the exploitation of satellite SAR images. On the contrary, given the lower availability of such data, the airborne domain concerns a smaller community. This report aims at presenting the specificities of high-resolution airborne radar imagery and their impacts on multi-channel applications.A first part is devoted to a theoretical analysis of airborne SAR processing in its different modalities. The various SAR processing approaches adapted to high resolution are presented from a geometric point of view rather than frequential point of view. Then, the principles of multichannel processing are presented with emphasis on the phenomenology associated with the improvement of the resolution: link between image registration and interferometric phase, behavior of point like scatterers, anisotropic or surfacic backscatters. A second part is dedicated to the impact of real acquisition systems on SAR processing and multichannel applications. Issues related to the radar hardware, the antenna particularities, non-linearities of the trajectories are discussed and illustrated on applications such as calibration of polarimetric data, 3D extraction, ground moving target detection .; Avec la multiplication des systèmes spatiaux, l’imagerie radar fait l’objet de nombreux travaux de recherche. En France, la majorité des travaux se concentre sur l’exploitation des images radar spatiales, de résolution de plus en plus fine. Le domaine aéroporté concerne une communauté plus restreinte étant donnée la moindre disponibilité de telles données. Ce rapport a pour vocation de présenter les spécificités de l’imagerie radar aéroportée haute résolution et d’en comprendre les impacts sur les applications multi-voies.Une première partie est consacrée à l’analyse théorique du traitement SAR aéroporté dans ses différentes modalités. Les diverses approches de traitement SAR adaptés à la haute résolution sont présentées selon un point de vue géométrique plutôt que fréquentiel. Puis, toujours sous ce même angle, les principes des traitements multivoies sont abordés en insistant sur les phénomènes apparaissant avec l’amélioration de la résolution : lien entre recalage d’images et phase interférométrique, comportement des rétrodiffuseurs ponctuels, surfaciques et anisotropes.Une deuxième partie est consacrée à l’étude de l’impact d’un système réel d’acquisition sur le traitement SAR et les applications multivoies. Les problématiques liées à la chaîne radar, aux diagrammes d’antennes, aux trajectoires non linéaires sont abordées.Enfin, différents travaux d’exploitation d’images radar haute résolution aéroportées (calibration de données polarimétriques, extraction du 3D sur les images SAR, détection de cibles mobiles) illustrent le propos.

With the growing number of operating spatial systems, SAR imagery has become a major topic of research in the remote sensing community. In France, most of the research focuses on the exploitation of satellite SAR images. On the contrary, given the lower availability of such data, the airborne domain concerns a smaller community. This report aims at presenting the specificities of high-resolution airborne radar imagery and their impacts on multi-channel applications.A first part is devoted to a theoretical analysis of airborne SAR processing in its different modalities. The various SAR processing approaches adapted to high resolution are presented from a geometric point of view rather than frequential point of view. Then, the principles of multichannel processing are presented with emphasis on the phenomenology associated with the improvement of the resolution: link between image registration and interferometric phase, behavior of point like scatterers, anisotropic or surfacic backscatters. A second part is dedicated to the impact of real acquisition systems on SAR processing and multichannel applications. Issues related to the radar hardware, the antenna particularities, non-linearities of the trajectories are discussed and illustrated on applications such as calibration of polarimetric data, 3D extraction, ground moving target detection ., Avec la multiplication des systèmes spatiaux, l’imagerie radar fait l’objet de nombreux travaux de recherche. En France, la majorité des travaux se concentre sur l’exploitation des images radar spatiales, de résolution de plus en plus fine. Le domaine aéroporté concerne une communauté plus restreinte étant donnée la moindre disponibilité de telles données. Ce rapport a pour vocation de présenter les spécificités de l’imagerie radar aéroportée haute résolution et d’en comprendre les impacts sur les applications multi-voies.Une première partie est consacrée à l’analyse théorique du traitement SAR aéroporté dans ses différentes modalités. Les diverses approches de traitement SAR adaptés à la haute résolution sont présentées selon un point de vue géométrique plutôt que fréquentiel. Puis, toujours sous ce même angle, les principes des traitements multivoies sont abordés en insistant sur les phénomènes apparaissant avec l’amélioration de la résolution : lien entre recalage d’images et phase interférométrique, comportement des rétrodiffuseurs ponctuels, surfaciques et anisotropes.Une deuxième partie est consacrée à l’étude de l’impact d’un système réel d’acquisition sur le traitement SAR et les applications multivoies. Les problématiques liées à la chaîne radar, aux diagrammes d’antennes, aux trajectoires non linéaires sont abordées.Enfin, différents travaux d’exploitation d’images radar haute résolution aéroportées (calibration de données polarimétriques, extraction du 3D sur les images SAR, détection de cibles mobiles) illustrent le propos.

In this paper, a novel method for enabling ground moving target capability for high-resolution wide-swath (HRWS) synthetic aperture radar (SAR) systems is presented. Such HRWS SAR systems are generally operated with very low pulse repetition frequencies (PRFs). With the novel method, moving target signals highly aliased in Doppler can be reconstructed and the targets’ motion parameters and actual positions can be estimated with high accuracy. A special matched reconstruction filter bank (MRFB) is introduced and incorporated into two novel low PRF ground moving target indication (GMTI) algorithms. Owing to the application of the MRFB, GMTI and HRWS SAR imaging can be performed simultaneously without the need of a separate high PRF system operation mode, which, so far, was necessary for achieving a reasonable GMTI performance. With the MRFB, the advantages of the HRWS imaging principle, i.e., the wide swath and the high resolution are preserved for both HRWS SAR imaging and GMTI. Potential applications are wide-area land and maritime traffic monitoring, where the benefit of the preserved high resolution could, for instance, be used for generating high-quality inverse SAR (ISAR) images for target recognition purposes.

This paper explores the ground moving target indication (GMTI) capabilities of the German Aerospace Center’s state-of-the-art airborne (F-SAR) and spaceborne (TerraSAR-X) synthetic aperture radars (SARs) when operating over maritime scenarios. The performance of classical dual channel GMTI techniques, such as displaced phase center antenna (DPCA) and along-track interferometry (ATI), as well as the promising adaptive techniques, like extended DPCA (EDPCA) and imaging space–time adaptive processing (ISTAP) have been analyzed on the basis of experimental acquisitions with both sensors. The objective of the paper is to highlight the limitations and challenges to be considered when processing real, multichannel GMTI data from pioneering SAR sensors for maritime surveillance. Different calibration or channel balancing strategies, on the basis of the digital balancing (DB) method, are studied, considering their impact on SAR-GMTI performance. An adaptive SAR processor, accounting for target kinematics and based on a matched filter bank (MFB) approach, is integrated in the SAR-GMTI processing chain in order to retrieve refocused images of the moving vessels.

Multi-input multi-output (MIMO) is usually defined as a radar system in which the transmit time and receive time, space and transform domain can be separated into multiple independent signals. Given the bandwidth and power constraints of the radar system, MIMO radar can improve its performance by optimize design transmit waveforms and receive filters, so as to achieve better performance in suppressing clutter and noise. In this paper, we cyclicly optimize the transmit waveform and receive filters, so as to maximize the output signal interference and noise ratio (SINR). From fixed pulse-to-pulse waveform to pulse-to-pulse waveform variations, we discuss the joint optimization under energy constraint, then extend it to optimizations under constant-envelope constraint and similarity constraint. Compared to optimization with fixed pulse-to-pulse waveform, the generalized optimization achieves higher output SINR and lower minimum detectable velocity (MDV), further improve the suppressing performance.

Recently we have introduced a set of novel low pulse repetition frequency (PRF) algorithms, which allow for simultaneous high-resolution wide-swath (HRWS) SAR imaging and moving target indication (MTI) without the need of changing the system operation mode and the pulse repetition frequency (PRF). The core of these novel HRWS-MTI algorithms is the so called Matched Reconstruction Filter Bank (MRFB). By applying the MRFB, low PRF moving target signals can be reconstructed and refocused. Additionally, accurate estimates of the target motion parameters are obtained. In this paper the experimental verification of the MRFB principle is presented for the first time. For the verification real multi-channel airborne data acquired with DLR's F-SAR sensor over a maritime scenario are used.

This paper describes a new approach for decoupling the slowly-moving targets and the clutter under multi-channel SAR (Synthetic Aperture Radar) scenarios. Given the phase histories received by different channels, the high-level data structures, e.g.The sparsities of moving targets, enable us to enforce advanced constraints on an optimisation problem to distinguish the dynamic targets from static background. Specifically, an iterative method is employed for the decomposition by alternatively updating the arguments. The dynamic parts can then be used for the subsequent analysis on states of the targets, and the static parts, in the case that the background does not change significantly over time, can be inherited in subsequent sub-Aperture processings. The presented approach is demonstrated on simulated three-channel SAR data.

Im Artikel werden die Aktivitäten des DLR Instituts für Hochfrequenztechnik und Radarsysteme im Bereich des Verkehrsmanagements bei Großereignissen und Katastrophen beschrieben. Insbesondere geht es um die Verkehrsbeobachtung mittels flugzeuggetragenen Radarsystemen und die Erzeugung hochaufgelöster vollpolarimetrischer Radarbilder.

Based on our previous work we propose to track multiple ground targetswith GMTI (Ground Moving Target Indicator) sensors as well as with imagery sensors.The scope of this paper is to fuse the attribute type information given by heterogeneoussensors with DSmT (Dezert Smarandache Theory) and to introduce the type results inthe tracking process to improve its performances.

Multichannel space-based SAR systems that exploit receiving antenna sub-arrays displaced in the along track-direction have been shown to provide the capability to detect ground moving targets and potentially estimate their radial motion velocity, thus making possible their correct relocation inside the SAR image of the background. However, the use of only two receiving channels to contain cost, mass and data-rate, imposes limitations in terms of potentiality of joint clutter cancellation and target velocity estimation. To overcome this problem we propose a full MIMO SAR scheme obtained by transmitting nearly orthogonal waveforms with the two sub-arrays achieved from a single antenna aperture, and receiving with the two sub-arrays. A complete processing chain for the joint detection, imaging and radial speed estimation is presented and the performance of the proposed MIMO system is deeply investigated and compared to the performance of conventional multichannel systems to assess the relative merits and drawbacks.

Multichannel space-based synthetic aperture radar (SAR) systems that exploit receiving antenna subarrays displaced in the along-track direction have been shown to provide the capability to detect ground moving targets and potentially estimate their radial motion velocity, thus making possible their correct relocation inside the SAR image of the background. However, the use of only two receiving channels to contain cost, mass, and data-rate, imposes limitations in terms of potentiality of joint clutter cancelation and target velocity estimation. To overcome this problem, we propose a full MIMO SAR scheme obtained by transmitting nearly orthogonal waveforms with the two subarrays achieved from a single antenna aperture and receiving with the same subarrays. A complete processing chain for the joint detection, imaging, and radial speed estimation is presented showing that by properly applying the clutter cancelation step before waveform compression, a good clutter removal performance is obtained despite the waveforms are not fully orthogonal. The performance of the proposed MIMO system is deeply investigated and compared to the performance of conventional multichannel systems to assess the relative merits and drawbacks.

Accurate and efficient moving target imaging is an important challenge for targets recognition in current synthetic aperture radar (SAR) combined with a ground moving target indication (GMTI) system. As the key but unknown parameter, the Doppler rates are estimated conventionally by searching any possible values for moving targets imaging. However, this conventional estimation method suffers from low accuracy or low efficiency due to the searching procedure. Focusing on these, we present a method to efficiently image the moving targets without the Doppler rate by Doppler delayed interferometry, and the imaged localization, which is parameterized pseudo-localization, is used to estimate the Doppler rate. In order to improve the estimation accuracy, an improved method based on the Newton method of approximation is proposed by exploiting the unused amplitude information. Compared with the conventional methods, the proposed improved method capable of high accuracy and low computation complexity simultaneously can meet the accurate and efficient requirements in the practical applications. Comparison simulations and real data processing results demonstrate the effectiveness of the proposed methods.

Although high-resolution wide-swath (HRWS) SAR imaging and ground moving target indication (GMTI) systems from the system architecture point of view look quite similar (both system types employ multiple receiving (RX) channels arranged along azimuth direction), they generally need to be operated in different modes, in particular with significantly different PRFs. HRWS systems require a comparatively low PRF, reflecting the overall length of the full antenna. The low PRF enables wide-swath imaging, and the multiple RX channels are used for signal spectrum reconstruction. In contrast, GMTI systems require a high PRF, reflecting the short length of the individual RX channel. The multiple RX channels are then used for clutter suppression and moving target parameter estimation. The high PRF additionally shall ensure that aliasing of the Doppler shifted moving target signal energy is avoided. It is known that the Doppler shift is proportional to the target’s velocity and inversely proportional to the radar wavelength. Thus, especially at Ka-band with small wavelengths in the millimeter range, the Doppler shift and, hence, the required PRF for avoiding aliasing may be very high. In general the high PRF required for GMTI prevents wide-swath SAR imaging as well as wide-swath GMTI. The resolution of this conflict is the issue addressed in this contribution. In the frame of a contract extension of the ESA-funded TRP Activity “Study of Multi-Channel Ka-Band SARs for Moving Target Indication”, novel low PRF system operation modes and processing approaches which allow for simultaneous GMTI and HRWS SAR imaging have been developed and investigated in detail. In particular, a special matched reconstruction filter bank (MRFB), which is the heart of all proposed processing approaches, has been developed. With the MRFB low PRF target signals acquired with a conventional HRWS system can be reconstructed and refocused. The application of the MRFB also provides accurate estimates of the target’s velocity. Furthermore, potential extensions of conventional HRWS systems have been proposed for additionally enabling effective clutter suppression without the need of increasing the PRF. In the final paper the results of the contract extension of the TRP Activity will be presented. The MRFB principle, the proposed and investigated HRWS-GMTI system concepts and the corresponding processing approaches will be introduced and explained in detail. The HRWS performance and the GMTI performance obtained from Monte-Carlo simulations will be presented and discussed. Also potential drawbacks of the proposed HRWS-GMTI modes will be addressed.

With the Sentinel-1 expected to be launched at the end of 2013, ESA is already funding activities to study the next generation of C-band SAR instruments. One of the drivers for these developments is the strong user re-quirement for high resolution and wide swath (HRWS) operations, which can be realized by using Multiple Azi-muth Phase centers (MAPS). The current reference system for a post-Sentinel-1 instrument features a 12.8 m long antenna divided along-track in 8 panels which, on receive, are sampled independently. To investigate the final performance in terms of surface current velocity estimation errors, a full multi-channel SAR simulator for open-oceans (OASIS: Ocean ATI-SAR SImulator) has been implemented. This simulator generates multi-channel raw data corresponding to a time-varying simulated ocean surface that includes all main environmental effects, and uses prototypes of the proposed processing algorithms. A detailed performance analysis in terms of final ATI performance is presented in this paper.

The paper presents a preliminary statistical evaluation of the sea clutter returns imaged by a spaceborne synthetic aperture radar (SAR) mission as TerraSAR-X. Two polarimetric data takes, Dual-polarized (Dual-Pol) and Quad-polarized (Quad-Pol), covering the range of incidence angles from 30 to 32 degrees, are considered for the stochastic characterization. The results show that the K-distribution, extendedly assumed statistics for high resolution radar sea clutter imaging, fits well the data's amplitude. This information jointly with the inverted sea spectrum are used to simulate SAR images of realistic scenarios that can be exploited for proper performance evaluation of ground moving target indication (GMTI) techniques and missions for maritime surveillance.

Modern multi-channel air- and spaceborne synthetic aperture radar (SAR) sensors allow for a variety of applications, independent of sunlight illumination and weather conditions. One application is ground moving target indication (GMTI) with the aim to detect moving targets on ground and to estimate their positions, velocities and moving directions. Although originated in the military field, nowadays GMTI also has gained relevance for civilian road traffic monitoring to ensure the mobility and to increase the safety of the road users. The actual chapter provides a comprehensive tutorial for GMTI with SAR systems. The effects on SAR imagery caused by moving targets are addressed in detail. Additionally, the basic moving target detection and parameter estimation techniques used in state-of-the-art multi-channel algorithms are treated. Finally an outlook to future trends is given.

The aim of this work is the development of processing techniques in order to provide the Cosmo-SkyMed (CSK) single-channel SAR system of Ground Moving Target Indication (GMTI) capabilities. To this purpose a two step processing chain is proposed: the first step performs stationary clutter suppression while the second step performs moving targets detection. For the last step two different detection schemes are proposed based respectively on a Bank of Chirp Scaling Algorithms (BCSA-MTD) and on a Change Detection approach (CD-MTD). The effectiveness of the proposed techniques is demonstrated against CSK data.