11 research outputs found

    Универсальный алгоритм автофокусировки радиолокационных изображений

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    Introduction. Random deviations of the antenna phase centre of a synthetic aperture radar (SAR) are a source of phase errors for the received signal. These phase errors frequently cause blurring of the radar image. The image quality can be improved using various autofocus algorithms. Such algorithms estimate phase errors via optimization of an objective function, which defines the radar image quality. The image entropy and sharpness are well known examples of objective functions. The objective function extremum can be found by fast optimization methods, whose realization is a challenging computing task.Aim. To synthesize a versatile and computationally simple autofocusing algorithm allowing any objective function to used without changing its structure significantly.Materials and methods. An algorithm based on substituting the selected objective function with a simpler surrogate objective function, whose extremum can be found by a direct method, is proposed. This method has been referred as the MM optimization in scientific literature. It is proposed to use a quadratic function as a surrogate objective function.Results. The synthesized algorithm is straightforward, not requiring recursive methods for finding the optimal solution. These advantages determine the enhanced speed and stability of the proposed algorithm. Adjusting the algorithm for the selected objective function requires minimal software changes. Compared to the algorithm using a linear surrogate objective function, the proposed algorithm provides a 1.5 times decrease in the standard deviation of the phase error estimate, with an approximately 10 % decrease in the number of iterations.Conclusion. The proposed autofocusing algorithm can be used in synthetic aperture radars to compensate the arising phase errors. The algorithm is based on the MM-optimization of the quadratic surrogate objective functions for radar images. The computer simulation results confirm the efficiency of the proposed algorithm even in case of large phase errors.Введение. Случайные перемещения фазового центра антенны радиолокатора с синтезированной апертурой (РСА) являются источником фазовых ошибок (ФО) траекторного сигнала, которые приводят к расфокусировке радиолокационного изображения (РЛИ). Для получения качественного РЛИ используются различные алгоритмы автофокусировки. Среди существующих алгоритмов автофокусировки можно выделить группу алгоритмов, которые позволяют оценить ФО посредством нахождения экстремума некоторой функции качества (ФК) РЛИ. Известными вариантами ФК являются, например, энтропия и резкость РЛИ. Для решения задачи поиска экстремума ФК необходимо применять быстрые методы, известные из теории оптимизации, реализация которых средствами бортового вычислителя является сложной задачей.Цель работы. Синтезировать универсальный и простой в плане вычислений алгоритм автофокусировки, который позволяет применять широкий спектр видов ФК РЛИ без изменения своей структуры.Материалы и методы. Для решения поставленной задачи предложен алгоритм, основанный на замене выбранной целевой ФК РЛИ на более простую при вычислениях суррогатную ФК, найти экстремум которой можно прямым способом. Данный метод получил в научной литературе название MM-метода оптимизации. В качестве суррогатной ФК предлагается использовать квадратическую функцию.Результаты. Синтезированный алгоритм является прямым и не предполагает использование рекурсивных методов поиска оптимального решения, что ускоряет его работу и повышает устойчивость. Алгоритм легко перестраивается под выбранную целевую функцию качества РЛИ. По сравнению с алгоритмом, использующим линейную суррогатную ФК, предлагаемый алгоритм дал среднеквадратическую ошибку (СКО) остаточной ФО, примерно в 1.5 раза меньшую при меньшем на 10 % количестве итераций.Заключение. Предложенный алгоритм автофокусировки может быть использован в РСА для компенсации ФО. Алгоритм основан на ММ-методе оптимизации квадратичных суррогатных функций качества РЛИ. Результаты математического моделирования подтверждают работоспособность рассмотренного алгоритма при больших значениях фазовых ошибок

    Factorized Geometrical Autofocus for Synthetic Aperture Radar Processing

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    This paper describes a factorized geometrical autofocus (FGA) algorithm, specifically suitable for ultrawideband synthetic aperture radar. The strategy is integrated in a fast factorized back-projection chain and relies on varying track parameters step by step to obtain a sharp image; focus measures are provided by an object function (intensity correlation). The FGA algorithm has been successfully applied on synthetic and real (Coherent All RAdio BAnd System II) data sets, i.e., with false track parameters introduced prior to processing, to set up constrained problems involving one geometrical quantity. Resolution (3 dB in azimuth and slant range) and peak-to-sidelobe ratio measurements in FGA images are comparable with reference results (within a few percent and tenths of a decibel), demonstrating the capacity to compensate for residual space variant range cell migration. The FGA algorithm is finally also benchmarked (visually) against the phase gradient algorithm to emphasize the advantage of a geometrical autofocus approach

    Computational Algorithms for Improved Synthetic Aperture Radar Image Focusing

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    High-resolution radar imaging is an area undergoing rapid technological and scientific development. Synthetic Aperture Radar (SAR) and Inverse Synthetic Aperture Radar (ISAR) are imaging radars with an ever-increasing number of applications for both civilian and military users. The advancements in phased array radar and digital computing technologies move the trend of this technology towards higher spatial resolution and more advanced imaging modalities. Signal processing algorithm development plays a key role in making full use of these technological developments.In SAR and ISAR imaging, the image reconstruction process is based on using the relative motion between the radar and the scene. An important part of the signal processing chain is the estimation and compensation of this relative motion. The increased spatial resolution and number of receive channels cause the approximations used to derive conventional algorithms for image reconstruction and motion compensation to break down. This leads to limited applicability and performance limitations in non-ideal operating conditions.This thesis presents novel research in the areas of data-driven motion compensation and image reconstruction in non-cooperative ISAR and Multichannel Synthetic Aperture Radar (MSAR) imaging. To overcome the limitations of conventional algorithms, this thesis proposes novel algorithms leading to increased estimation performance and image quality. Because a real-time imaging capability is important in many applications, special emphasis is placed on the computational aspects of the algorithms.For non-cooperative ISAR imaging, the thesis proposes improvements to the range alignment, time window selection, autofocus, time-frequency-based image reconstruction and cross-range scaling procedures. These algorithms are combined into a computationally efficient non-cooperative ISAR imaging algorithm based on mathematical optimization. The improvements are experimentally validated to reduce the computational burden and significantly increase the image quality under complex target motion dynamics.Time domain algorithms offer a non-approximated and general way for image reconstruction in both ISAR and MSAR. Previously, their use has been limited by the available computing power. In this thesis, a contrast optimization approach for time domain ISAR imaging is proposed. The algorithm is demonstrated to produce improved imaging performance under the most challenging motion compensation scenarios. The thesis also presents fast time domain algorithms for MSAR. Numerical simulations confirm that the proposed algorithms offer a reasonable compromise between computational speed and image quality metrics

    An Efficient Solution to the Factorized Geometrical Autofocus Problem

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    This paper describes a new search strategy within the scope of factorized geometrical autofocus (FGA) and synthetic-aperture-radar processing. The FGA algorithm is a fast factorized back-projection formulation with six adjustable geometry parameters. By tuning the flight track step by step and maximizing focus quality by means of an object function, a sharp image is formed. We propose an efficient two-stage approach for the geometrical variation. The first stage is a low-order (few parameters) parallel search procedure involving small image areas. The second stage then combines the local hypotheses into one global autofocus solution, without the use of images. This method has been applied successfully on ultrawideband CARABAS II data. Errors due to a constant acceleration are superposed on the measured track prior to processing, giving a 6-D autofocus problem. Image results, including resolution, peak-to-sidelobe ratio and magnitude values for point-like targets, finally confirm the validity of the strategy. The results also verify the prediction that there are several satisfying autofocus solutions for the same radar data

    Recent Techniques for Regularization in Partial Differential Equations and Imaging

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    abstract: Inverse problems model real world phenomena from data, where the data are often noisy and models contain errors. This leads to instabilities, multiple solution vectors and thus ill-posedness. To solve ill-posed inverse problems, regularization is typically used as a penalty function to induce stability and allow for the incorporation of a priori information about the desired solution. In this thesis, high order regularization techniques are developed for image and function reconstruction from noisy or misleading data. Specifically the incorporation of the Polynomial Annihilation operator allows for the accurate exploitation of the sparse representation of each function in the edge domain. This dissertation tackles three main problems through the development of novel reconstruction techniques: (i) reconstructing one and two dimensional functions from multiple measurement vectors using variance based joint sparsity when a subset of the measurements contain false and/or misleading information, (ii) approximating discontinuous solutions to hyperbolic partial differential equations by enhancing typical solvers with l1 regularization, and (iii) reducing model assumptions in synthetic aperture radar image formation, specifically for the purpose of speckle reduction and phase error correction. While the common thread tying these problems together is the use of high order regularization, the defining characteristics of each of these problems create unique challenges. Fast and robust numerical algorithms are also developed so that these problems can be solved efficiently without requiring fine tuning of parameters. Indeed, the numerical experiments presented in this dissertation strongly suggest that the new methodology provides more accurate and robust solutions to a variety of ill-posed inverse problems.Dissertation/ThesisDoctoral Dissertation Mathematics 201

    Analyse temps-frequence et traitement des signaux RSO à haute résolution spatiale pour la surveillance des grands ouvrages d'art

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    The thesis is composed of two research axis. The first one consists in proposing time-frequency signal processing tools for frequency modulated continuous wave (FMCW) radars used for displacements measurements, while the second one consists in designing a spaceborne synthetic aperture radar (SAR) signal processing methodology for infrastructure monitoring when an external point cloud of the envisaged structure is available. In the first part of the thesis, we propose our solutions to the nonlinearity problem of an X-band FMCW radar designed for millimetric displacement measurements of short-range targets. The nonlinear tuning curve of the voltage controlled oscillator from the transceiver can cause a dramatic resolution degradation for wideband sweeps. To mitigate this shortcoming, we have developed two time warping-based methods adapted to wideband nonlinearities: one estimates the nonlinear terms using the high order ambiguity function, while the other is an autofocus approach which exploits the spectral concentration of the beat signal. Onwards, as the core of the thesis, we propose a novel method for scattering centers detection and tracking in spaceborne SAR images adapted to infrastructure monitoring applications. The method is based on refocusing each SAR image on a provided 3D point cloud of the envisaged infrastructure and identifying the reliable scatterers to be monitored by means of four dimensional (4D) tomography. The refocusing algorithm is compatible with stripmap, spotlight and sliding spotlight SAR images and consists of an azimuth defocusing followed by a modified back-projection algorithm on the given set of points which exploits the time-frequency structure of the defocused azimuth signal. The scattering centers of the refocused image are detected in the 4D tomography framework by testing if the main response is at zero elevation in the local elevation-velocity spectral distribution. The mean displacement velocity is estimated from the peak response on the zero elevation axis, while the displacements time series for detected single scatterers is computed as double phase difference of complex amplitudes.Finally, we present the measurement campaigns carried out on the Puylaurent water-dam and the Chastel landslide using GPS measurements, topographic surveys and laser scans to generate the point clouds of the two structures. The comparison between in-situ data and the results obtained by combining TerraSAR-X data with the generated point clouds validate the developed SAR signal processing chain.Cette thèse s'articule autour de deux axes de recherche. Le premier axe aborde les aspects méthodologiques liés au traitement temps-fréquence des signaux issus d'un radar FMCW (à onde continue modulée en fréquence) dans le contexte de la mesure des déplacements fins. Le second axe est dédié à la conception et à la validation d'une chaîne de traitement des images RSO (radar à synthèse d'ouverture) satellitaire. Lorsqu'un maillage 3D de la structure envisagée est disponible, les traitements proposés sont validés par l'intercomparaison avec les techniques conventionnelles d'auscultation des grands ouvrages d'art.D'une part, nous étudions la correction de la non-linéarité d'un radar FMCW en bande X, à courte portée, conçu pour la mesure des déplacements millimétriques. La caractéristique de commande non linéaire de l'oscillateur à large bande, entraine une perte de résolution à la réception. Afin de pallier cet inconvénient, nous avons développé deux méthodes basées sur le ré-échantillonnage temporel (time warping) dans le cas des signaux à large bande non-stationnaires. La première approche estime la loi de fréquence instantanée non linéaire à l'aide de la fonction d'ambiguïté d'ordre supérieur, tandis que la deuxième approche exploite la mesure de concentration spectrale du signal de battement dans un algorithme d'autofocus radial.D'autre part, nous proposons un cadre méthodologique général pour la détection et le pistage des centres de diffusion dans les images RSO pour la surveillance des grands ouvrages d'art. La méthode est basée sur la ré-focalisation de chaque image radar sur le maillage 3D de l'infrastructure étudiée afin d'identifier les diffuseurs pertinents par tomographie 4D (distance – azimut – élévation – vitesse de déformation). L'algorithme de ré-focalisation est parfaitement compatible avec les images RSO acquises dans les différents modes (« stripmap », « spotlight » et « sliding spotlight ») : dé-focalisation en azimut suivie par rétroprojection modifiée (conditionnée par la structure temps-fréquence du signal) sur l'ensemble donné des points. Dans la pile d'images ré-focalisées, les centres de diffusion sont détectés par tomographie 4D : test de conformité à l'hypothèse d'élévation zéro dans le plan élévation – vitesse de déformation. La vitesse moyenne correspond au maximum à l'élévation zéro, tandis que la série temporelle des déplacements est obtenue par double différence de phase des amplitudes complexes pour chaque diffuseur pertinent.Nous présentons également les campagnes in situ effectuées au barrage de Puylaurent (et glissement de Chastel) : les relevés GPS, topographiques et LIDAR sol employées au calcul des maillages 3D. La comparaison entre les déplacements mesurés in situ et les résultats obtenus par l'exploitation conjointe de la télédétection RSO satellitaires et les maillages 3D valident la chaîne de traitement proposée.Teza cuprinde două axe principale de cercetare. Prima axă abordează aspecte metodologice de prelucraretimp-frecvenţă a semnalelor furnizate de radare cu emisie continuă şi modulaţie de frecvenţă (FMCW)în contextul măsurării deplasărilor milimetrice. În cadrul celei de-a doua axe, este proiectată şi validatăo metodă de prelucrare a imaginilor satelitare SAR (radar cu apertură sintetică) ce este destinatămonitorizării infrastructurii critice şi care se bazează pe existenţa unui model 3D al structurii respective.În prima parte a tezei, sunt investigate soluţii de corecţie a neliniarităţii unui radar FMCW în bandaX destinat măsurării deplasărilor milimetrice. Caracteristica de comandă neliniară a oscilatorului debandă largă determină o degradare a rezoluţiei în distanţă. Pentru a rezolva acest inconvenient, au fostelaborate două metode de corecţie a neliniarităţii, adaptate pentru semnale de bandă largă, ce se bazeazăpe conceptul de reeşantionare neuniformă sau deformare a axei temporare. Prima abordare estimeazăparametrii neliniarităţii utilizând funcţii de ambiguitate de ordin superior, iar cea de-a doua exploateazăo măsură de concentraţie spectrală a semnalului de bătăi într-un algoritm de autofocalizare în distanţă.În a doua parte a lucrării, este propusă o metodologie generală de detecţie şi monitorizare a centrilorde împrăştiere în imagini SAR în scopul monitorizării elementelor de infrastructură critică. Metoda sebazează pe refocalizarea fiecărei imagini radar pe un model 3D al structurii investigate în scopul identificăriicentrilor de împrăştiere pertinenţi (ţinte fiabile ce pot fi monitorizate în timp) cu ajutorul tomografiei SAR4D (distanţă-azimut-elevaţie-viteză de deplasare). Algoritmul de refocalizare este compatibil cu imaginiSAR achiziţionate în moduri diferite (« stripmap », « spotlight » şi « sliding spotlight ») şi constă într-odefocalizare în azimut urmată de o retroproiecţie modificată (condiţionată de structura timp-frecvenţă asemnalului) pe modelul 3D al structurii. Ţintele sunt identificate în stiva de imagini refocalizate cu ajutorultomografiei 4D prin efectuarea unui test de conformitate cu ipoteza că centrii de împrăştiere pertinenţivor avea elevaţie zero în planul local elevaţie-viteză. Viteza medie de deformare corespunde maximuluide pe axa de elevaţie nulă, iar seria temporară a deplasărilor se obţine printr-o dublă diferenţă de fază aamplitudinilor complexe corespunzătoare ţintelor identificate.În final sunt prezentate campaniile de măsurători pe teren efectuate la un baraj şi o alunecare de terendin regiunea Puylaurent (Franţa) destinate obţinerii modelului 3D al celor două elemente de infrastructurăprin măsurători GPS, topografice şi LIDAR. Comparaţia între deformările măsurate pe teren şi rezultateleobţinute prin combinarea imaginilor SAR cu modelele 3D au permis validarea metodologiei propuse

    Signal Processing for Synthetic Aperture Sonar Image Enhancement

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    This thesis contains a description of SAS processing algorithms, offering improvements in Fourier-based reconstruction, motion-compensation, and autofocus. Fourier-based image reconstruction is reviewed and improvements shown as the result of improved system modelling. A number of new algorithms based on the wavenumber algorithm for correcting second order effects are proposed. In addition, a new framework for describing multiple-receiver reconstruction in terms of the bistatic geometry is presented and is a useful aid to understanding. Motion-compensation techniques for allowing Fourier-based reconstruction in widebeam geometries suffering large-motion errors are discussed. A motion-compensation algorithm exploiting multiple receiver geometries is suggested and shown to provide substantial improvement in image quality. New motion compensation techniques for yaw correction using the wavenumber algorithm are discussed. A common framework for describing phase estimation is presented and techniques from a number of fields are reviewed within this framework. In addition a new proof is provided outlining the relationship between eigenvector-based autofocus phase estimation kernels and the phase-closure techniques used astronomical imaging. Micronavigation techniques are reviewed and extensions to the shear average single-receiver micronavigation technique result in a 3 - 4 fold performance improvement when operating on high-contrast images. The stripmap phase gradient autofocus (SPGA) algorithm is developed and extends spotlight SAR PGA to the wide-beam, wide-band stripmap geometries common in SAS imaging. SPGA supersedes traditional PGA-based stripmap autofocus algorithms such as mPGA and PCA - the relationships between SPGA and these algorithms is discussed. SPGA's operation is verified on simulated and field-collected data where it provides significant image improvement. SPGA with phase-curvature based estimation is shown and found to perform poorly compared with phase-gradient techniques. The operation of SPGA on data collected from Sydney Harbour is shown with SPGA able to improve resolution to near the diffraction-limit. Additional analysis of practical stripmap autofocus operation in presence of undersampling and space-invariant blurring is presented with significant comment regarding the difficulties inherent in autofocusing field-collected data. Field-collected data from trials in Sydney Harbour is presented along with associated autofocus results from a number of algorithms

    Phase error estimation for synthetic aperture imagery.

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    The estimation of phase errors in synthetic aperture imagery is important for high quality images. Many methods of autofocus, or the estimation of phase errors from the measured data, are developed using certain assumptions about the imaged scene. This thesis develops improved methods of phase estimation which make full use of the information in the recorded signal. This results in both a more accurate estimate of the image phase error and improved imagery compared to using standard techniques. The standard phase estimation kernel used in echo-correlation techniques is shear-average. This technique averages the phase-difference between each ping over all range-bins, weighted by the signal strength. It is shown in this thesis that this is not the optimal method of weighting each phase estimate. In images where the signal to clutter ratio (SCR) is not proportional to the signal amplitude, shear-average does not meet the predicted error bound. This condition may be met by many image types, including those with shadows, distributed targets and varying surface structure. By measuring the average coherence between echos at each range-bin, it is possible to accurately estimate the variance of each phase estimate, and weight accordingly. A weighted phase-difference estimation (WPDE) using this coherence weighting meets the performance bound for all images tested. Thus an improved performance over shear-average is shown for many image types. The WPDE phase estimation method can be used within the framework of many echo-correlation techniques, such as phase-gradient autofocus (PGA), phase curvature estimation, redundant phase-centre or displaced phase-centre algorithms. In addition, a direct centre-shifting method is developed which reduces bias compared to the centre-shifting method used in PGA. For stripmap images, a weighted phase curvature estimator shows better performance than amplitude weighted shear-average for images with high SCR. A different method of phase estimation, known as sharpness maximisation, perturbs an estimate of the phase error to maximise the sharpness of the reconstructed image. Several improvements are made to the technique of sharpness maximisation. These include the reduction of over-sharpening using regularisation and an improvement in accuracy of the phase estimate using range-weighting based on the coherence measure. A cascaded parametric optimisation method is developed which converges significantly faster than standard optimisation methods for stripmap images. A number of novel insights into the method of sharpness maximisation are presented. A derivation of the phase that gives maximum intensity squared sharpness is extended from a noncoherent imaging system to a coherent spotlight system. A bound on the performance of sharpness-maximisation is presented. A method is developed which allows the direct calculation of the result of a sharpness maximisation for a single ping of a spotlight synthetic aperture image. The phase correction that maximises sharpness can be directly calculated from the signal in a manner similar to a high-order echo-correlation. This calculation can be made for all pings in a recursive manner. No optimisation is required, resulting in a significantly faster phase estimation. The techniques of sharpness maximisation and echo-correlation can be shown to be closely related. This is confirmed by direct comparisons of the results. However, the classical intensity-squared sharpness measure gives poorer results than WPDE and different sharpness measures tested for a distributed target. The standard methods of shear average and maximisation of the intensity-squared sharpness measure, both perform well below the theoretical performance bound. Two of the techniques developed, WPDE and direct entropy minimisation perform at the bound, showing improved performance over standard techniques. The contributions of this thesis add considerably to the body of knowledge on the technique of sharpness maximisation. This allows an improvement in the accuracy of some phase estimation methods, as well as an increase in the understanding of how these techniques work on coherent imagery in general

    Efficient SAR MTI simulator of marine scenes

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    Tècniques de detecció de moviment amb radars d'apertura sintètica multicanals sobre escenaris marítims.[ANGLÈS] Multichannel spaceborne and airborne synthetic aperture radars (SAR) offer the opportunity to monitor maritime traffic through specially designed instruments and applying a suitable signal processing in order to reject sea surface clutter. These processing techniques are known as Moving Target Indication techniques (MTI) and the choice of the most adequate method depends on the radar system and operating environment. In maritime scenes the seas presents a complicated clutter whose temporal/spatial coherence models and background reflectivity depends on a large number of factors and are still subject of research. Moreover the targets kinematics are influenced by the sea conditions, producing in some situations high alterations in the imaged target. These aspects make difficult the detectability analysis of vessels in maritime scenarios, requiring both theoretical models and numerical simulations. This thesis looks into the few available MTI techniques and deals experimentally with them in a developed simulator for maritime SAR images. The results are also presented in a image format, giving the sequence for one trial simulation and the asymptotic probability of detection for the simulated conditions.[CASTELLÀ] Los radares de apertura sintética (SAR) multicanal a bordo de satélites o plataformas aerotransportadas ofrecen la oportunidad de monitorizar el tráfico marítimo a través de instrumentos especialmente diseñados y procesando los datos recibidos de forma adecuada para rechazar la señal provocada por la reflexión del mar. A estas técnicas se las conoce como Moving Target Indication techniques (MTI) y la elección de la más adecuada depende del sistema y del entorno de aplicación. En escenarios marinos, el mar presenta un clutter complicado de modelar, cuya coherencia espacio-temporal y reflectividad radar dependen de un gran número de factores que hoy en día todavía siguen siendo investigados. Por otra parte los parámetros dinámicos del target estan influenciados por las condiciones del mar, produciendo en algunas situaciones graves alteraciones en la formación de la imagen. Estos aspectos dificultan el análisis de la detección de las embarcaciones, requiriendo modelos teóricos y simulaciones numéricas. Este Proyecto Final de Carrera investiga las técnicas MTI disponibles, aplicándolas sobre las imágenes marítimas generadas por un simulador SAR. Los resultados son la generación de los productos MTI en formato imagen y el cálculo de la probabilidad de detección para cada target.[CATALÀ] Els radars d'obertura sintètica (SAR) multicanal embarcats en satèl·lits o plataformes aerotransportades ofereixen l'oportunitat de monitoritzar el tràfic marítim a través d'instruments especialment dissenyats i processant les dades rebudes de forma adequada per rebutjar la senyal provocada per la reflexió del mar. A aquestes tècniques se les coneix com Moving Target indication techniques (MTI) i l'elecció de la més adequada depèn del sistema i de l'entorn d'aplicació. En escenaris marins, el mar presenta un clutter complicat de modelar, la coherència espai-temporal i reflectivitat radar depenen d'un gran nombre de factors que avui dia encara segueixen sent investigats. D'altra banda els paràmetres dinàmics del target estan influenciats per les condicions de la mar, produint en algunes situacions greus alteracions en la formació de la imatge. Aquests aspectes dificulten l'anàlisi de la detecció de les embarcacions, requerint models teòrics i simulacions numèriques. Aquest Projecte Final de Carrera investiga les tècniques MTI disponibles, aplicant-les sobre les imatges marítimes generades per un simulador SAR. Els resultats són la generació dels productes MTI en format imatge i el càlcul de la probabilitat asimptòtica de detecció per a cada target

    Ground moving target indication with synthetic aperture radars for maritime surveillance

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    The explosive growth of shipping traffic all over the World, with around three quarters of the total trade goods and crude oil transported by sea, has raised newly emerging concerns (economical, ecological, social and geopolitical). Geo-information (location and speed) of ocean-going vessels is crucial in the maritime framework, playing a key role in the related environmental monitoring, fisheries management and maritime/coastal security. In this scenario space-based synthetic aperture radar (SAR) remote sensing is a potential tool for globally monitoring the oceans and seas, providing two-dimensional high-resolution imaging capabilities in all-day and all-weather conditions. The combination of ground moving target indication (GMTI) modes with multichannel spaceborne SAR systems represents a powerful apparatus for surveillance of maritime activities. The level of readiness of such a technology for road traffic monitoring is still low, and for the marine scenario is even less mature. Some of the current space-based SAR missions include an experimental GMTI mode with reduced detection capabilities, especially for small and slow moving targets. In this framework, this doctoral dissertation focuses on the study and analysis of the GMTI limitations of current state-of-the-art SAR missions when operating over maritime scenarios and the proposal of novel and optimal multichannel SAR-GMTI architectures, providing subclutter visibility of small (reduced reflectivity) slow moving vessels. This doctoral activity carries out a transversal analysis embracing system-architecture proposal and optimization, processing strategies assessment, performance evaluation, sea/ocean clutter characterization and adequate calibration methodologies suggestion. Firstly, the scarce availability of multichannel SAR-GMTI raw data and the related restrictions to access it have raised the need to implement flexible simulation tools for SAR-GMTI performance evaluation and mission. These simulation tools allow the comparative study and evaluation of the SAR-GMTI mode operated with current SAR missions, showing the reduced ability of these missions to detect small and slow boats in subclutter visibility. Improved performance is achieved with the new multichannel architecture based on non-uniformly distributed receivers (with external deployable antennas), setting the ground for future SAR-GMTI mission development. Some experimental multichannel SAR-GMTI data sets over the sea and acquired with two instruments, airborne F-SAR and spaceborne TerraSAR-X (TSX) platforms, have been processed to evaluate their detection capabilities as well as the adequate processing strategies (including channel balancing). This doctoral activity presents also a preliminary characterization of the sea clutter returns imaged by the spaceborne TSX instrument in a three-level basis, i.e., radiometric, statistical and polarimetric descriptions using experimental polarimetric data. This study has shown that the system-dependent limitations, such as thermal noise and temporal decorrelation, play a key role in the appropriate interpretation of the data and so should be properly included in the physical backscattering models of the sea. Current and most of the upcoming SAR missions are based on active phase array antennas (APAA) technology for the operation of multiple modes of acquisitions. The related calibration is a complex procedure due to the high number of different beams to be operated. Alternative internal calibration methodologies have been proposed and analyzed in the frame of this doctoral thesis. These approaches improved the radiometric calibration performance compared to the conventional ones. The presented formulation of the system errors as well as the proposed alternative strategies set the path to extrapolate the analysis for multichannel SAR systems.L'increment continu del tràfic marítim arreu del món, amb gairebé tres quartes parts del total de mercaderies i cru transportats per mar, porta associats uns impactes canviants a nivell econòmic, ambiental, social i geopolític. La geo-informació (localització i velocitat) dels vaixells té un paper fonamental en el monitoratge ambiental, la gestió de la pesca i la seguretat marítima/costanera. Els radars d'obertura sintètica (SAR, sigles en anglès) embarcats en satèl·lits són una eina molt potent per al monitoratge global dels oceans i dels mars, gràcies a la seva capacitat de generar imatges d'alta resolució amb independència de les condicions meteorològiques i de la llum solar. La detecció de blancs mòbils terrestres (GMTI, sigles en anglès) combinada amb sistemes multicanal SAR és fonamental per a la vigilància de les activitats marítimes. El nivell de maduresa d'aquesta tecnologia per monitorar tràfic rodat és baix, però per al cas marítim encara ho és més. Algunes missions SAR orbitals inclouen el mode GMTI, però amb unes capacitats de detecció reduïdes, especialment per a blancs petits i lents. En aquest marc, la tesi doctoral es centra en l'estudi i anàlisi de les limitacions GMTI dels actuals sistemes SAR operant en entorns marítims, proposant noves configuracions SAR-GMTI multicanal optimitzades per a la detecció de vaixells petits (emmascarats pels retrons radar del mar) i que es mouen lentament. La present dissertació doctoral du a terme un estudi transversal que abasta des de la proposta i optimització de sistemes/configuracions, passant per l'avaluació de les tècniques de processat, fins a l'estudi del rendiment de la missió, caracterització del mar i la valoració de noves metodologies de calibratge. En primer terme, diverses eines de simulació flexibles s'han implementat per poder avaluar les capacitats GMTI de diferents missions tenint en compte la poca disponibilitat de dades multicanal SAR-GMTI. Aquests simuladors permeten l'estudi comparatiu de les capacitats GMTI de les missions SAR orbitals actuals, demostrant les seves reduïdes opcions per identificar vaixells emmascarats pels retorns del mar. En el marc de l'activitat de recerca s'han processat dades experimentals SAR-GMTI multicanal de sistemes aeris (F-SAR) i orbitals (TerraSAR-X), per tal d'avaluar les seves capacitats de detecció de blancs mòbils sobre entorns marítims, proposant les estratègies de processat i calibratge més adients. Com a part de l'activitat de recerca doctoral, s'ha portat a terme una caracterització preliminar dels retorns radar del mar adquirits amb el sensor orbital TerraSAR-X, amb tres nivells d'anàlisi (radiomètric, estadístic i polarimètric). Aquest estudi demostra que aspectes com el soroll tèrmic i la decorrelació temporal, dependents del propi sensor i de l'entorn dinàmic del mar, poden limitar la correcta interpretació de les dades, i per tant, s'han d'incloure en els models físics dels mecanismes de dispersió del mar. Les missions SAR tant actuals com futures es basen en l'explotació de la tecnologia de les agrupacions d'antenes de fase activa (APAA) per operar diferents modes d'adquisició. El procés de calibratge associat és molt complex atès el gran nombre de feixos que es poden utilitzar. En el marc de la tesi doctoral s'han proposat i avaluat metodologies alternatives de calibratge intern per aquests sistemes, amb un millor rendiment en comparació amb les tècniques convencionals. Aquestes estratègies de calibratge, juntament amb la corresponent formulació dels errors de sistema, estableixen les bases per a l'estudi i avaluació en sistemes multicanal SA
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