Synthetic aperture radar is an important tool in a wide range of civilian and military imaging applications. This is primarily due to its ability to image in all weather conditions, during both the day and the night, unlike optical imaging systems. A synthetic aperture radar system contains a step which is not present in an optical imaging system, this is image formation. This is required because the acquired data from the radar sensor does not directly correspond to the image. Instead, to form an image, the system must solve an inverse problem. In conventional scenarios, this inverse problem is relatively straight forward and a matched lter based algorithm produces an image of suitable image quality. However, there are a number of interesting scenarios where this is not the case. Scenarios where standard image formation algorithms are unsuitable include systems with data undersampling, errors in the system observation model and data that is corrupted by radio frequency interference. Image formation in these scenarios will form the topics of this thesis and a number of iterative algorithms are proposed to achieve image formation. The motivation for these proposed algorithms is primarily from the eld of compressed sensing, which considers the recovery of signals with a low-dimensional structure. The rst contribution of this thesis is the development of fast algorithms for the system observation model and its adjoint. These algorithms are required by large-scale gradient based iterative algorithms for image formation. The proposed algorithms are based on existing fast back-projection algorithms, however, a new decimation strategy is proposed which is more suitable for some applications. The second contribution is the development of a framework for iterative near- eld image formation, which uses the proposed fast algorithms. It is shown that the framework can be used, in some scenarios, to improve the visual quality of images formed from fully sampled data and undersampled data, when compared to images formed using matched lter based algorithms. The third contribution concerns errors in the system observation model. Algorithms that correct these errors are commonly referred to as autofocus algorithms. It is shown that conventional autofocus algorithms, which work as a post-processor on the formed image, are unsuitable for undersampled data. Instead an autofocus algorithm is proposed which corrects errors within the iterative image formation procedure. The proposed algorithm is provably stable and convergent with a faster convergence rate than previous approaches. The nal contribution is an algorithm for ultra-wideband synthetic aperture radar image formation. Due to the large spectrum over which the ultra-wideband signal is transmitted, there is likely to be many other users operating within the same spectrum. These users can produce signi cant radio frequency interference which will corrupt the received data. The proposed algorithm uses knowledge of the RFI spectrum to minimise the e ect of the RFI on the formed image.

International Telemetering Conference Proceedings / October 26-29, 1987 / Town and Country Hotel, San Diego, California / The Very Large Array (VLA) radio telescope, located in west-central New Mexico, obtains high-resolution radio images of astronomical objects by using Fourier aperture synthesis with 27 antennas. With the addition of X-band to its receiving capabilities by 1989, and when arrayed with the Goldstone Deep Space Communications Complex (GDSCC), the VLA will double the Deep Space Network (DSN) receiving aperture in the U. S. longitude for signals from Voyager 2 at Neptune. This paper describes the VLA and the installation of the X-band system, its operation and performance for Voyager data reception, and its capabilities for other science at X-band.

International Telemetering Conference Proceedings / October 22-25, 2001 / Riviera Hotel and Convention Center, Las Vegas, Nevada / Synthetic-aperture microwave imaging with ground penetrating radar systems has become a research topic of great importance for the potential applications in sensing and profiling of civil and geophysical structures. It allows us to visualize subsurface structures for nondestructive evaluation with microwave tomographic images. This paper provides an overview of the research program, ranging from the formation of the concepts, physical and mathematical modeling, formulation and development of the image reconstruction algorithms, laboratory experiments, and full-scale field tests.

Synthetic aperture sonar (SAS) is a wide-beam sonar technique commonly used for mapping the seafloor at high resolution. The Acoustics Research Group at the University of Canterbury operates a towed SAS system known as KiwiSAS-IV. This is currently being redesigned with the aim of reducing the weight, size and power requirements of the system. The long term goal is to make it capable of being mounted on an autonomous underwater vehicle (AUV) so that mapping of remote and/or dangerous waters can be accomplished without human interaction. This thesis presents the design of the front-end electronics used to drive the 36 transducers to produce the acoustic beam and receive the returning signals after they have reflected off a target. To achieve sufficient range, the transducers are driven with a 200 Vₚ₋ₚ signal with a maximum frequency of 110 kHz. This design uses class D switching amplifiers to generate these waveforms. The AD9271 integrated circuit, which can handle eight transducers simultaneously, is used to amplify the incoming signals and sample them at up to 50 MHz. This high sampling rate multiplied by all 36 transducers results in an amount of data which is too great for a conventional microprocessor-based system to handle. Instead, an FPGA is used to receive this data, decimate it using multiplier-free cascaded integrator-comb (CIC) filters, and then pass it to the back-end system for further processing and storage. A prototype circuit was created to test the theory developed in this thesis. This showed that the system is capable of generating the necessary waveforms and amplifying, capturing, and decimating the returning signals. However, further refinement is required before it is able to be used in the sonar system.

The UK has an abundant offshore wind resource with offshore wind farming set to grow rapidly over the coming years. Optimisation of energy production is of the utmost importance and accurate estimates of wind speed distributions are critical for the planning process. Synthetic aperture radar (SAR) data can provide synoptic, wide area wind field estimates at resolutions of a few kilometres and has great potential for wind resource assessment. This thesis addresses the key challenges for the operational implementation of SAR in this context; namely the accuracy of SAR wind retrievals and the ability of SAR to characterise the mean wind speed and wind power density. We consider the main stages of SAR wind retrieval; the retrieval algorithm; sources of a priori information; the optimal configuration of the retrieval system; and the challenges for and accuracy of SAR wind resource estimation. This study was conducted for the eastern Irish Sea in the UK, a region undergoing significant offshore wind energy development. A new wind retrieval algorithm was developed that implements a maximum a posterior probability (MAP) method drawn from Bayesian statistics. MAP was demonstrated to be less sensitive to input errors than the standard direction-based wind speed algorithm (DWSA) and provides a simple retrieval quality check via the error reduction ratio. Retrieval accuracy is strongly influenced by the quality of a priori information. The accuracy of two operationally viable a priori sources, mesoscale numerical weather prediction (NWP) data and WISAR image directions, was evaluated by comparison against in-situ wind observations and WERA coastal data. Results show that NWP wind speeds produce good wind speed and direction estimates with standard deviations of ¬±2 ms-1 and ±16o respectively. WISAR directions were less accurate producing standard deviations ranging from ±20o to ±29o, but were preferable when strong differences between NWP timesteps were observed. The accuracy of SAR wind retrievals was evaluated by comparison against in-situ wind observations. The MAP algorithm was found to provide modest improvements in retrieval accuracy over DWSA. Highest quality retrievals achieved using the CMOD5 forward model, producing wind speeds with a RMSE of 1.83 ms-1. Regarding the ability of SAR to estimate offshore wind resources, dataset density was found to be a controlling parameter. With 103 scenes available mean wind speeds were well characterised by comparison against in-situ observations and Wind Atlas results, while wind power density showed considerable errors. The accuracy of wind speed maps was further improved by accounting for wind direction and fetch effects upon the SAR wind distribution. A key strength of the SAR wind fields is their ability to identify the effect of mesoscale structures upon the surface wind field with atmospheric gravity waves observed in 30% of the images. These structures are shown to introduce wind speed fluctuations of up to ±2 ms-1 at scales of 5 to 10 km and may have significant implications for wind power prediction. These findings show that SAR may provide an important source of wide area wind speed observations as a complement to existing wind resource estimation techniques. SAR may be of particular use in coastal areas where complex wind fields are observed.

Optimization algorithms were developed for use with the Adaptive Joint Time-Frequency (AJFT) algorithm to reduce Inverse Synthetic Aperture Radar (ISAR) image blurring caused by higher-order target motion. A specific optimization was then applied to 3D motion detection. Evolutionary search methods based on the Genetic Algorithm (GA) and the Particle Swarm Optimization (PSO) algorithm were designed to rapidly traverse the solution space in order to find the parameters that would bring the ISAR image into focus in the cross-range. 3D motion detection was achieved by using the AJTF PSO to extract the phases of 3 different point scatterers in the target data and measuring their linearity when compared to an ideal phase for the imaging interval under investigation. The algorithms were tested against both simulated and real ISAR data sets.

<p>In this thesis, we develop methods for addressing the deficiencies of array processing with linear thinned arrays. Our methods are designed for array systems mounted on moving platforms and exploit synthetic aperture processing techniques. In particular, we use array motion to decrease the sidelobe levels and increase the degrees of freedom available from thinned array systems. In this work, we consider two application areas 1) passive SONAR and 2) ultrasound imaging. </p><p>Synthetic aperture processing is a methodology for exploiting array motion and has been successfully used in practice to increase array resolution. By spatially sampling along the path of the array virtual sensors can be realized and coherently fused to the existing array. The novel contribution of this work is our application of synthetic aperture processing. Here our goal is not to increase array resolution, instead we propose to use the synthetic aperture process to expand the spatial covariance and spatial frequency sensing capabilities of thinned array system.</p><p> </p><p>In the passive sensing case, we use a class of thinned arrays know as co-prime linear sensor arrays for source localization. The class of co-prime arrays provides roughly half the aperture worth of spatial covariances and with modest array motion can be extended to the full aperture of the array. The amount of motion required to produce a full set of spatial covariances is shown to be a function of the co-prime array parameters and is only a fraction of the total aperture of the array. The full set of spatial covariances can be used to form a spatial covariance matrix with dimension equal to that of a uniform array. With a spatial covariance matrix in hand one can perform signal processing tasks as if the array were fully populated. Three methods for spatial covariance matrix estimation are compared in different source localization scenarios. In the work presented here, we demonstrate the benefits of our approach for achieving reduced sidelobe levels and extending the source localization capabilities above the limits of the static co-prime array. </p><p>In the active sensing case, we develop a framework for incorporating motion using thinned arrays for ultrasound imaging. In this setting, array motion is used to augment the spatial frequency sensing capabilities of the thinned array system. Here we develop an augmentation strategy based on using quarter-wavelength array translations to fill-in missing spatial frequencies not measured by the static thinned array. The quarter-wavelength translation enables the thinned array system to sample missing spatial frequencies and increase the redundancy of other spatial frequencies sampled by the array. We compare the level of redundancy in sampling the spatial frequencies achieved by the thinned arrays post translation to different levels of sample redundancy derived from pruning the transmit/receive events of a uniform array. In this manner, we are able to examine how the level of spatial frequency redundancy afforded by different thinned arrays compare over the full redundancy range of the uniform array. While artificially pruning the uniform array does not necessarily create realizable arrays, it provides the means to compare image quality at different spatial frequency redundancy levels. In this work, we are able to conclude that images formed from thinned arrays using the translated synthetic aperture process are capable of approximating images formed from the corresponding uniform array. In particular, the systems considered in this work have approximately one-third of the active sensors when compared to the uniform array. </p><p>In both application areas, the use of thinned arrays offers a reduction in the cost to deploy and maintain a given array system. The feature that makes it possible to overcome the spatial sampling deficiencies of thinned array systems is motion and it is at the core of the performance gains in these applications.</p> / Dissertation

Synthetic Aperture Radar (SAR) has been identified as a good candidate to provide high-resolution soil moisture information over extended areas. SAR data could be used as observations within a global Data Assimilation (DA) approach to benefit applications such as hydrology and agriculture. Prior to developing an operational DA system, one must tackle the following challenges of soil moisture estimation with SAR: (1) the dependency of the measured radar signal on both soil moisture and soil surface roughness which leads to an ill-conditioned inverse problem, and (2) the difficulty in characterizing spatially/temporally surface roughness of natural soils and its scattering contribution. The objectives of this project are (1) to develop a roughness measurement method to improve the spatial/temporal characterization of soil surface roughness, and (2) to investigate to what extent the inverse problem can be solved by combining multipolarization, multi-incidence, and/or multi-frequency radar measurements. The first objective is achieved with a measurement method based on Structure from Motion (SfM). It is tailored to monitor natural surface roughness changes which have often been assumed negligible although without evidence. The measurement method is flexible, a.ordable, straightforward and generates Digital Elevation Models (DEMs) for a SAR-pixel-size plot with mm accuracy. A new processing method based on band-filtering of the DEM and its 2D Power Spectral Density (PSD) is proposed to compute the classical roughness parameters. Time series of DEMs show that non-negligible changes in surface roughness can happen within two months at scales relevant for microwave scattering. The second objective is achieved using maximum likelihood fitting of the Oh backscattering model to (1) full-polarimetric Radarsat-2 data and (2) simulated multi-polarization / multi-incidence / multi-frequency radar data. Model fitting with the Radarsat-2 images leads to poor soil moisture retrieval which is related to inaccuracy of the Oh model. Model fitting with the simulated data quantifies the amount of multilooking for di.erent combinations of measurements needed to mitigate the critical e.ect of speckle on soil moisture uncertainty. Results also suggest that dual-polarization measurements at L- and C-bands are a promising combination to achieve the observation requirements of soil moisture. In conclusion, the SfM method along with the recommended processing techniques are good candidates to improve the characterization of surface roughness. A combination of multi-polarization and multi-frequency radar measurements appears to be a robust basis for a future Data Assimilation system for global soil moisture monitoring.

Approved for public release; distribution in unlimited. / Synthetic aperture sonar beamforming and signal processing relies on properly steering and focusing the aperture beam pattern in order to co-phase all the received signals. Due to the effects of motion in the synthetic aperture sonar problem, the propagation path between the transmitter, discrete point scatterer, and the receiver is time varying. Traditionally, simple approximations are used to determine these propagation ranges and angles of incidence and scatter. Methods to determine these ranges and angles exactly may significantly improve array gain and, therefore, target detection. This thesis investigates improvements to SAS signal processing algorithms using exact methods for the calculation of the time-varying ranges between transmitter and discrete point scatter, and between discrete point scatter and receiver, and the phase angle of the scattered acoustic signal incident upon the receiver. Using computer simulations, exact range and angle calculations were performed for different scenarios and compared to ranges and angles determined using standard approximations. The exact ranges were then used to determine incident phase, and were again compared to the approximate methods. Comparison of the exact and approximate methods was based on range estimation error and percentage error. Improvements in synthetic aperture array gain using exact phase weights based on exact, time-varying range solutions are proposed. / http://hdl.handle.net/10945/1142 / Lieutenant, United States Navy

Les radars à synthèse d'ouverture (SAR) spatioportés ont fait la preuve de leur valeur inestimable dans l'observation des vents et des vagues océaniques mondiaux. Les images SAR acquises par plusieurs capteurs sont utilisées, notamment Sentinel-1 (S-1), Envisat/ASAR, Gaofen-3 et Radarsat-2. Cette thèse passe en revue les paramètres SAR couramment utilisés dans la première partie. Une série d'étapes d'étalonnage sont nécessaires pour obtenir un NRCS approprié et une évaluation du NRCS est effectuée pour le mode d'onde S-1 (WV). Il s'avère que WV est mal calibré et est donc recalibré pour obtenir un NRCS précis. Il a été démontré que la coupure de l'azimut est complémentaire du NRCS et peut expliquer l'impact de l'état de la mer sur l'extraction du vent. D'après les produits SAR entièrement polarimétriques disponibles, la coupure de l'azimut varie considérablement en fonction des polarisations. La transformation actuelle de la cartographie SAR est suffisante pour interpréter la coupure azimutale copolarisée, mais pas pour la polarisation croisée. Compte tenu des limites de l'imagerie SAR, un nouveau paramètre est proposé et défini en fonction du spectre croisé de l'image SAR, appelé MACS. La partie imaginaire de MACS est une quantité signée par rapport à la direction du vent. Compte tenu de cette dépendance, on s'attend à ce qu'un algorithme indépendant de récupération du vent en bénéficie. L'ampleur du MACS peut aider à estimer la fonction de modulation de la cartographie SAR. De plus, la MACS donne également des résultats prometteurs en ce qui concerne les études globales sur les vagues. Les signatures globales du MACS à différentes longueurs d'onde sont bien représentatives de la distribution spatiale et saisonnière des vents. Les MACS des vagues longues montrent des valeurs plus élevées sur les trajectoires des tempêtes alors que les vagues plus courtes sont principalement dans les vents des trader. Ces résultats devraient aider à évaluer les résultats du modèle et compléter les études ultérieures sur le climat spectral global des vagues. / Spaceborne synthetic aperture radar (SAR) has been demonstrated invaluable in observing the global ocean winds and waves. SAR images acquired by multiple sensors are employed, including Sentinel-1(S-1), Envisat/ASAR, Gaofen-3 and Radarsat-2. This thesis reviews the commonly used SAR parameters (NRCS and azimuth cutoff) in the first part. A series of calibration steps are required to obtain a proper NRCS and assessment of NRCS is carried out for S-1wave mode (WV). It turns out that WV is poorly calibrated and is thus re-calibrated to obtain accurate NRCS. Azimuth cut off is demonstrated to be complementary to NRCS and can account for the sea state impact on the wind retrieval. Based on the available fully polarimetric SAR products, azimuth cut off is found to vary greatly with polarizations. The present SAR mapping transformation is sufficient to interpret the co-polarized azimuth cut off, while not for the cross-polarization. With the limitations of SAR imaging in mind, a new parameter is proposed and defined based on the SAR image cross-spectra, termed as MACS. The imaginary part of MACS is found to be a signed quantity relative to the wind direction. Given this dependence, an independent wind retrieval algorithm is expected to benefit. The magnitude of MACS is able to aid for estimate of modulation function of SAR mapping. In addition, MACS also gives promising results regarding the global wave studies. The global signatures of MACS at various wave lengths are well representative of the winds distributions, spatially and seasonally. MACS of long waves shows greater values over the storm tracks while the shorter waves are mostly within the trader winds. These results are expected to help evaluate the model outputs and complement further studies of the global wave spectral climate. Data continuity in the coming 10 years shall extend the study towards longer duration.