11 research outputs found

    A moving target velocity estimation method based on the MC-MASA SAR mode

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    Imaging position shift based on the multiple azimuth squint angles (MASA) mode is effective for target azimuth velocity estimation, whereas accuracy is low when target range velocity is high. In this paper, the estimation problem for both target azimuth and range velocities is considered based on the multi-channels MASA (MC-MASA) mode. Firstly, the acquisition geometry of MC-MASA mode and Doppler characteristics of a moving target are analyzed in detail, especially in squint mode. Then, for better moving target estimation, the stationary background clutter is removed using the displacement phase center antenna (DPCA) technique, and the failure in range velocity estimation with sequential SAR images is also discussed. Furthermore, a modified along-track interferometry (ATI) is proposed to preliminarily reconstruct the azimuth-and-range velocity map based on the MC-MASA mode. Since the velocity estimation accuracy is dependent on squint angle and signal-to-clutter ratio (SCR), the circumstances are divided into three cases with different iteration estimation strategies, which could expand the scene application scope of velocity estimation and achieve a high estimation accuracy along both azimuth and range directions. Finally, the performance of the proposed method is demonstrated by experimental results

    GNSS-based passive radar techniques for maritime surveillance

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    The improvement of maritime traffic safety and security is a subject of growing interest, since the traffic is constantly increasing. In fact, a large number of human activities take place in maritime domain, varying from cruise and trading ships up to vessels involved in nefarious activities such as piracy, human smuggling or terrorist actions. The systems based on Automatic Identification System (AIS) transponder cannot cope with non-cooperative or non-equipped vessels that instead can be detected, tracked and identified by means of radar system. In particular, passive bistatic radar (PBR) systems can perform these tasks without a dedicated transmitter, since they exploit illuminators of opportunity as transmitters. The lack of a dedicated transmitter makes such systems low cost and suitable to be employed in areas where active sensors cannot be placed such as, for example, marine protected areas. Innovative solutions based on terrestrial transmitters have been considered in order to increase maritime safety and security, but these kinds of sources cannot guarantee a global coverage, such as in open sea. To overcome this problem, the exploitation of global navigation satellites system (GNSS) as transmitters of opportunity is a prospective solution. The global, reliable and persistent nature of these sources makes them potentially able to guarantee the permanent monitoring of both coastal and open sea areas. To this aim, this thesis addresses the exploitation of Global Navigation Satellite Systems (GNSS) as transmitters of opportunity in passive bistatic radar (PBR) systems for maritime surveillance. The main limitation of this technology is the restricted power budget provided by navigation satellites, which makes it necessary to define innovative moving target detection techniques specifically tailored for the system under consideration. For this reason, this thesis puts forward long integration time techniques able to collect the signal energy over long time intervals (tens of seconds), allowing the retrieval of suitable levels of signal-to-disturbance ratios for detection purposes. The feasibility of this novel application is firstly investigated in a bistatic system configuration. A long integration time moving target detection technique working in bistatic range&Doppler plane is proposed and its effectiveness is proved against synthetic and experimental datasets. Subsequently the exploitation of multiple transmitters for the joint detection and localization of vessels at sea is also investigated. A single-stage approach to jointly detect and localize the ship targets by making use of long integration times (tens of seconds) and properly exploiting the spatial diversity offered by such a configuration is proposed. Furthermore, the potential of the system to extract information concerning the detected target characteristics for further target classification is assessed

     Ocean Remote Sensing with Synthetic Aperture Radar

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    The ocean covers approximately 71% of the Earth’s surface, 90% of the biosphere and contains 97% of Earth’s water. The Synthetic Aperture Radar (SAR) can image the ocean surface in all weather conditions and day or night. SAR remote sensing on ocean and coastal monitoring has become a research hotspot in geoscience and remote sensing. This book—Progress in SAR Oceanography—provides an update of the current state of the science on ocean remote sensing with SAR. Overall, the book presents a variety of marine applications, such as, oceanic surface and internal waves, wind, bathymetry, oil spill, coastline and intertidal zone classification, ship and other man-made objects’ detection, as well as remotely sensed data assimilation. The book is aimed at a wide audience, ranging from graduate students, university teachers and working scientists to policy makers and managers. Efforts have been made to highlight general principles as well as the state-of-the-art technologies in the field of SAR Oceanography

    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

    The Adaptive City

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