Dissertations / Theses: 'Radar techniques'

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Frankford, Mark Thomas. "EXPLORATION OF MIMO RADAR TECHNIQUES WITH A SOFTWARE-DEFINED RADAR." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1306526246.

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Ravichandran, Kulasegaram. "Radar imaging using two-dimensional synthetic aperture radar (SAR) techniques /." abstract and full text PDF (UNR users only), 2007. http://0-gateway.proquest.com.innopac.library.unr.edu/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:1446797.

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Thesis (M.S.)--University of Nevada, Reno, 2007.
Library also has microfilm. Ann Arbor, Mich. : ProQuest Information and Learning Company, [2008]. 1 microfilm reel ; 35 mm. Online version available on the World Wide Web.

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Chen, Hung-Ruei. "FMCW radar jamming techniques and analysis." Thesis, Monterey California. Naval Postgraduate School, 2013. http://hdl.handle.net/10945/37597.

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Frequency-Modulated Continuous-Wave (FMCW) radar is a type of Low Probability of Intercept radar system that is being heavily investigated in the military. Not only is its transmission difficult to be detected by enemy intercept receivers, but FMCW radar has the inherent capability of increasing coherent signal power while suppressing noise power during its receive signal processing. This thesis investigates the jamming effectiveness of selected jamming waveforms by injecting the interfering signals into the Lab-Volt Radar Training System (LVRTS). The jamming effect is evaluated based on the change in beat frequency due to the jamming. Due to the hardware limitations of the LVRTS, a MATLAB simulation model is also constructed for advanced electronic attack testing. The MATLAB model emulates the FMCW emitter digital signal processing response to coherent and non-coherent jamming signals under an anti-ship capable missile scenario. The simulation output is the target range and range rate, whose error measures quantify the jamming effectiveness. From the standpoint of electronic warfare, related subjects such as electronic warfare support measures and FMCW electronic protection are also discussed.

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Sexton, G. "Ground probing radar signal processing techniques." Thesis, University of Newcastle Upon Tyne, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.354404.

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Panzner, Berthold [Verfasser]. "Synthetic Aperture Radar Focusing Techniques for Subsurface Radar Imaging / Berthold Panzner." München : Verlag Dr. Hut, 2013. http://d-nb.info/1031844910/34.

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Rossetti, Gaia. "Mathematical optimization techniques for cognitive radar networks." Thesis, Loughborough University, 2018. https://dspace.lboro.ac.uk/2134/33419.

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This thesis discusses mathematical optimization techniques for waveform design in cognitive radars. These techniques have been designed with an increasing level of sophistication, starting from a bistatic model (i.e. two transmitters and a single receiver) and ending with a cognitive network (i.e. multiple transmitting and multiple receiving radars). The environment under investigation always features strong signal-dependent clutter and noise. All algorithms are based on an iterative waveform-filter optimization. The waveform optimization is based on convex optimization techniques and the exploitation of initial radar waveforms characterized by desired auto and cross-correlation properties. Finally, robust optimization techniques are introduced to account for the assumptions made by cognitive radars on certain second order statistics such as the covariance matrix of the clutter. More specifically, initial optimization techniques were proposed for the case of bistatic radars. By maximizing the signal to interference and noise ratio (SINR) under certain constraints on the transmitted signals, it was possible to iteratively optimize both the orthogonal transmission waveforms and the receiver filter. Subsequently, the above work was extended to a convex optimization framework for a waveform design technique for bistatic radars where both radars transmit and receive to detect targets. The method exploited prior knowledge of the environment to maximize the accumulated target return signal power while keeping the disturbance power to unity at both radar receivers. The thesis further proposes convex optimization based waveform designs for multiple input multiple output (MIMO) based cognitive radars. All radars within the system are able to both transmit and receive signals for detecting targets. The proposed model investigated two complementary optimization techniques. The first one aims at optimizing the signal to interference and noise ratio (SINR) of a specific radar while keeping the SINR of the remaining radars at desired levels. The second approach optimizes the SINR of all radars using a max-min optimization criterion. To account for possible mismatches between actual parameters and estimated ones, this thesis includes robust optimization techniques. Initially, the multistatic, signal-dependent model was tested against existing worst-case and probabilistic methods. These methods appeared to be over conservative and generic for the considered signal-dependent clutter scenario. Therefore a new approach was derived where uncertainty was assumed directly on the radar cross-section and Doppler parameters of the clutters. Approximations based on Taylor series were invoked to make the optimization problem convex and {subsequently} determine robust waveforms with specific SINR outage constraints. Finally, this thesis introduces robust optimization techniques for through-the-wall radars. These are also cognitive but rely on different optimization techniques than the ones previously discussed. By noticing the similarities between the minimum variance distortionless response (MVDR) problem and the matched-illumination one, this thesis introduces robust optimization techniques that consider uncertainty on environment-related parameters. Various performance analyses demonstrate the effectiveness of all the above algorithms in providing a significant increase in SINR in an environment affected by very strong clutter and noise.

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Nanding, N. "Hydrological applications of radar-raingauge rainfall merging techniques." Thesis, University of Bristol, 2016. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.715769.

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French, A. "Target recognition techniques for multifunction phased array radar." Thesis, University College London (University of London), 2010. http://discovery.ucl.ac.uk/19675/.

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This thesis, submitted for the degree of Doctor of Philosophy at University College London, is a discussion and analysis of combined stepped-frequency and pulse-Doppler target recognition methods which enable a multifunction phased array radar designed for automatic surveillance and multi-target tracking to offer a Non Cooperative Target Recognition (NCTR) capability. The primary challenge is to investigate the feasibility of NCTR via the use of high range resolution profiles. Given stepped frequency waveforms effectively trade time for enhanced bandwidth, and thus resolution, attention is paid to the design of a compromise between resolution and dwell time. A secondary challenge is to investigate the additional benefits to overall target classification when the number of coherent pulses within an NCTR wavefrom is expanded to enable the extraction of spectral features which can help to differentiate particular classes of target. As with increased range resolution, the price for this extra information is a further increase in dwell time. The response to the primary and secondary challenges described above has involved the development of a number of novel techniques, which are summarized below: • Design and execution of a series of experiments to further the understanding of multifunction phased array Radar NCTR techniques • Development of a ‘Hybrid’ stepped frequency technique which enables a significant extension of range profiles without the proportional trade in resolution as experienced with ‘Classical’ techniques • Development of an ‘end to end’ NCTR processing and visualization pipeline • Use of ‘Doppler fraction’ spectral features to enable aircraft target classification via propulsion mechanism. Combination of Doppler fraction and physical length features to enable broad aircraft type classification. • Optimization of NCTR method classification performance as a function of feature and waveform parameters. • Generic waveform design tools to enable delivery of time costly NCTR waveforms within operational constraints. The thesis is largely based upon an analysis of experimental results obtained using the multifunction phased array radar MESAR2, based at BAE Systems on the Isle of Wight. The NCTR mode of MESAR2 consists of the transmission and reception of successive multi-pulse coherent bursts upon each target being tracked. Each burst is stepped in frequency resulting in an overall bandwidth sufficient to provide sub-metre range resolution. A sequence of experiments, (static trials, moving point target trials and full aircraft trials) are described and an analysis of the robustness of target length and Doppler spectra feature measurements from NCTR mode data recordings is presented. A recorded data archive of 1498 NCTR looks upon 17 different trials aircraft using five different varieties of stepped frequency waveform is used to determine classification performance as a function of various signal processing parameters and extent (numbers of pulses) of the data used. From analysis of the trials data, recommendations are made with regards to the design of an NCTR mode for an operational system that uses stepped frequency techniques by design choice.

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Pennington, Jason R. "Radar Signal Characteristic Extraction with FFT-Based Techniques." Miami University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=miami1306201663.

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Lellouch, Gabriel. "Waveform design and processing techniques in OFDM radar." Doctoral thesis, University of Cape Town, 2015. http://hdl.handle.net/11427/16678.

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With the advent of powerful digital hardware, software defined radio and radar have become an active area of research and development. This in turn has given rise to many new research directions in the radar community, which were previously not comprehensible. One such direction is the recently investigated OFDM radar, which uses OFDM waveforms instead of the classic linear frequency mod- ulated waveforms. Being a wideband signal, the OFDM symbol offers spectral efficiency along with improved range resolution, two enticing characteristics for radar. Historically a communication signal, OFDM is a special form of multi- carrier modulation, where a single data stream is transmitted over a number of lower rate carriers. The information is conveyed via sets of complex phase codes modulating the phase of the carriers. At the receiver, a demodulation stage estimates the transmitted phase codes and the information in the form of binary words is finally retrieved. In radar, the primary goal is to detect the presence of targets and possibly estimate some of their features through measurable quantities, e.g. range, Doppler, etc. Yet, being a young waveform in radar, more understanding is required to turn it into a standard radar waveform. Our goal, with this thesis, is to mature our comprehension of OFDM for radar and contribute to the realm of OFDM radar. First, we develop two processing alternatives for the case of a train of wideband OFDM pulses. In this, our first so-called time domain solution consists in applying a matched filter to compress the received echoes in the fast time before applying a fast Fourier transform in the slow time to form the range Doppler image. We motivate this approach after demonstrating that short OFDM pulses are Doppler tolerant. The merit of this approach is to conserve existing radar architectures while operating OFDM waveforms. The second so-called frequency domain solution that we propose is inspired from communication engineering research since the received echoes are tumbled in the frequency domain. After several manipulations, the range Doppler image is formed. We explain how this approach allows to retrieve an estimate of the unambiguous radial velocity, and propose two methods for that. The first method requires the use of identical sequence (IS) for the phase codes and is, as such, binding, while the other method works irrespective of the phase codes. Like the previous technique, this processing solution accommodates high Doppler frequencies and the degradation in the range Doppler image is negligible provided that the spacing between consecutive subcarriers is sufficient. Unfortunately, it suffers from the issue of intersymbol interference (ISI). After observing that both solutions provide the same processing gain, we clarify the constraints that shall apply to the OFDM signals in either of these solutions. In the first solution, special care has been employed to design OFDM pulses with low peak-to-mean power ratio (PMEPR) and low sidelobe level in the autocorrelation function. In the second solution, on the other hand, only the constraint of low PMEPR applies since the sidelobes of the scatterer characteristic function in the range Doppler image are Fourier based. Then, we develop a waveform-processing concept for OFDM based stepped frequency waveforms. This approach is intended for high resolution radar with improved low probability of detection (LPD) characteristics, as we propose to employ a frequency hopping scheme from pulse to pulse other than the conventional linear one. In the same way we treated our second alternative earlier, we derive our high range resolution processing in matrix terms and assess the degradation caused by high Doppler on the range profile. We propose using a bank of range migration filters to retrieve the radial velocity of the scatterer and realise that the issue of classical ambiguity in Doppler can be alleviated provided that the relative bandwidth, i.e. the total bandwidth covered by the train of pulses divided by the carrier frequency, is chosen carefully. After discussing a deterministic artefact caused by frequency hopping and the means to reduce it at the waveform design or processing level, we discuss the benefit offered by our concept in comparison to other standard wideband methods and emphasize on its LPD characteristics at the waveform and pulse level. In our subsequent analysis, we investigate genetic algorithm (GA) based techniques to finetune OFDM pulses in terms of radar requirements viz., low PMEPR only or low PMEPR and low sidelobe level together, as evoked earlier. To motivate the use of genetic algorithms, we establish that existing techniques are not exible in terms of the OFDM structure (the assumption that all carriers are present is always made). Besides, the use of advanced objective functions suited to particular configurations (e.g. low sidelobe level in proximity of the main autocorrelation peak) as well as the combination of multiple objective functions can be done elegantly with GA based techniques. To justify that solely phase codes are used for our optimisation(s), we stress that the weights applied to the carriers composing the OFDM signal can be spared to cope with other radar related challenges and we give an example with a case of enhanced detection. Next, we develop a technique where we exploit the instantaneous wideband trans- mission to characterise the type of the canonical scatterers that compose a target. Our idea is based on the well-established results from the geometrical theory of diffraction (GTD), where the scattered energy varies with frequency. We present the problem related to ISI, stress the need to design the transmitted pulse so as to reduce this risk and suggest having prior knowledge over the scatterers relative positions. Subsequently, we develop a performance analysis to assess the behaviour of our technique in the presence of additive white Gaussian noise (AWGN). Then, we demonstrate the merit of integrating over several pulses to improve the characterisation rate of the scatterers. Because the scattering centres of a target resonate variably at different frequencies, frequency diversity is another enticing property which can be used to enhance the sensing performance. Here, we exploit this element of diversity to improve the classification function. We develop a technique where the classification takes place at the waveform design when few targets are present. In our case study, we have three simple targets. Each is composed of perfectly electrically conducting spheres for which we have exact models of the scattered field. We develop a GA based search to find optimal OFDM symbols that best discriminate one target against any other. Thereafter, the OFDM pulse used for probing the target in the scene is constructed by stacking the resulting symbols in time. After discussing the problem of finding the best frequency window to sense the target, we develop a performance analysis where our figure of merit is the overall probability of correct classification. Again, we prove the merit of integrating over several pulses to reach classification rates above 95%. In turn, this study opens onto new challenges in the realm of OFDM radar. We leave for future research the demonstration of the practical applicability of our novel concepts and mention manifold research axes, viz., a signal processing axis that would include methods to cope with inter symbol interference, range migration issues, methods to raise the ambiguity in Doppler when several echoes from distinct scatterers overlap in the case of our frequency domain processing solutions; an algorithmic axis that would concern the heuristic techniques employed in the design of our OFDM pulses. We foresee that further tuning might help speeding up our GA based algorithms and we expect that constrained multi- objective optimisation GA (MOO-GA) based techniques shall benefit the OFDM pulse design problem in radar. A system design axis that would account for the hardware components' behaviours, when possible, directly at the waveform design stage and would include implementation of the OFDM radar system.

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Jerome, Richard Carleton University Dissertation Engineering Electrical. "Performance analysis of space-based radar tracking techniques." Ottawa, 1990.

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Sandys-Renton, Jane Belinda Elizabeth. "Segmentation techniques for SAR imagery." Thesis, University of Liverpool, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.317224.

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Quelle, Hans-Christoph. "Segmentation bayesienne non supervisee en imagerie radar." Rennes 1, 1993. http://www.theses.fr/1993REN10012.

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Segmentation bayesienne non supervisee en imagerie radar. La these est consacree a la segmentation statistique non supervisee en imagerie radar. L'accent a ete mis sur les methodes locales, qui au contraire des methodes globales ne necessitent pas l'hypothese d'independance des donnees observees conditionnellement a une realisation du terrain. Dans une premiere partie l'influence du contexte spatial sur l'estimation des parametres utilises par le modele d'image hierarchique et sur la segmentation bayesienne des images d'intensites mono-vue et multi-vues a ete etudie. Ensuite nous avons propose une methode d'estimation adaptative de parametres (asem) base sur l'estimateur sem, permettant la segmentation bayesienne des scenes homogenes, non-stationnaires. Les tests effectues sur des images de synthese et reelles ont montre la superiorite de la segmentation bayesienne utilisant les parametres estimes avec l'asem par rapport a la segmentation utilisant les parametres estimes avec le sem, mais aussi, sous certaines conditions, sur des images de synthese stationnaire. Dans une derniere partie l'idee d'une generalisation du modele d'image hierarchique de kelly et derin est proposee permettant l'adaptation de la probabilite marginale de chaque composant du melange aux differentes regions de l'image

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Hwang, Seung-Hyeon. "Adaptive antenna techniques for smart antennas and radar systems." Related electronic resource: Current Research at SU : database of SU dissertations, recent titles available full text, 2005. http://wwwlib.umi.com/cr/syr/main.

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Pisipati, Udaynag. "Techniques for improving landmine detection using ground penetrating radar." Diss., Columbia, Mo. : University of Missouri-Columbia, 2006. http://hdl.handle.net/10355/4604.

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Thesis (M.S.)--University of Missouri-Columbia, 2006.
The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file viewed on (February 23, 2007) Includes bibliographical references.

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Akhanli, Deniz. "Radar Range-doppler Imaging Using Joint Time-frequency Techniques." Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/12608325/index.pdf.

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Inverse Synthetic Aperture Radar coherently processes the return signal from the target in order to construct the image of the target. The conventional methodology used for obtaining the image is the Fourier transform which is not capable of suppressing the Doppler change in the return signal. As a result, Range-Doppler image is degraded. A proper time-frequency transform suppresses the degradation due to time varying Doppler shift. In this thesis, high resolution joint-time frequency transformations that can be used in place of the conventional method are evaluated. Wigner-Ville Distribution, Adaptive Gabor Representation with Coarse-to-Fine search algorithm, and Time-Frequency Distribution Series are examined for the target imaging system. The techniques applied to sample signals compared with each other. The computational and memorial complexity of the methods are evaluated and compared to each other and possible improvements are discussed. The application of these techniques in the target imaging system is also performed and resulting images compared to each other.

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Armstrong, Brian Clement. "Processing techniques for improved radar detection in spiky clutter." Thesis, University College London (University of London), 1992. http://discovery.ucl.ac.uk/1317536/.

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The problem of improved radar detection of targets embedded in spiky clutter is addressed. Two main areas where improvements may be possible are investigated, namely improved clutter suppression by doppler filtering, and improved Constant False Alarm Rate (CFAR) processing. The clutter suppression performance of several doppler processors is quantified under a wide range of conditions. It is shown that in spatially homogeneous clutter ideal optimal (Hsiao) filters offer 2 to 3 dB higher improvement factor than conventional techniques. Adaptive Hsiao filters are evaluated under conditions of spatially heterogeneous clutter, and it is shown that practical losses due to filter adaptivity and spectral heterogeneity will outweigh the superior performance of ideal Hsiao filters in homogeneous clutter. It is concluded that improved doppler filtering offers little scope for improving detection performance in spiky clutter, and that more significant benefits are to be gained through improved CFAR processing. The performance of three current generation CFAR processors is evaluated in spatially uncorrelated K-distributed clutter to quantify detection losses. It is shown that losses of in excess of 10 dB can be expected in spiky clutter. Reducing the loss by exploitation of any spatial correlation of the underlying clutter power is investigated. To this end a mathematically rigorous model for spatially correlated K-distributed clutter is derived. An improved CFAR processor based on optimal weighting of reference cells is formulated and evaluated. It is shown that in highly correlated clutter CFAR loss can be reduced by 2 to 5 dB compared to Cell Averaging CFAR processors. An alternative "RDT-CFAR" processor is formulated to eliminate reliance on spatial correlation, and this is shown to reduce CFAR loss by more than 10 dB in spectrally homogeneous spiky clutter. However, an increase in false alarm rate in clutter without constant spectrum is demonstrated. The RDT-CFAR processor has been modified to eliminate dependence on surrounding range bins. The resulting "δ-CFAR" processor reduces CFAR loss by more than 10 dB in even moderately spiky clutter. It is also immune to extraneous targets and clutter edges, and its false alarm performance is insensitive to clutter spikiness.

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Tucker, Dewey S. (Dewey Stanton). "Wavelet denoising techniques with applications to high-resolution radar." Thesis, Massachusetts Institute of Technology, 1997. http://hdl.handle.net/1721.1/10466.

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Curry, Mark A. "Techniques for radar imaging using a wideband adaptive array /." Thesis, Connect to this title online; UW restricted, 2001. http://hdl.handle.net/1773/5841.

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Leeson, Michael J. "The application of quasi-optical techniques to millimetre wave radar." Thesis, University of St Andrews, 1993. http://hdl.handle.net/10023/2774.

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The application of Quasi Optical techniques has been of great benefit to the field of instrumentation for frequencies between 750Hz and several hundred OHz. The application of Quasi Optical techniques to millimetre wave radar, described in this thesis, has produced an FMCW Doppler radar capable of operation at 940Hz and 1400Hz. Total polarization agility and a capability to operate over a very wide bandwidth is demonstrated. Quasi Optical circuits are proposed as solutions for many of the system requirements, and these are fully analyzed. Significant benefits of these techniques are demonstrated, and future improvements are suggested. A new design tool, in the form of a program, for Quasi Optical circuit analysis is presented and is used for the analysis of all the optical circuits in this thesis. The program has speeded up the design process for optical circuits. A new type of feedhorn is described and characterized. Its performance compares well with existing feedhorns, and it provides a low cost alternative to existing antenna requirements.

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Jones, William John. "Direct frequency synthesis using combined digital and analogue techniques." Thesis, University of Bradford, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.336118.

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Totir, Félix. "Caractérisation multidimensionnelle à très large bande des réflecteurs électromagnétiques en environnement radar non-gaussien." Brest, 2006. http://www.theses.fr/2006BRES2010.

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La thèse est structurée autour de la problématique de la caractérisation des cibles navales vues par un radar de surveillance côtière à large bande. Deux aspects essentiels de cette problématique sont abordés : la modélisation des échos radar des cibles navales dans leur environnement (problème direct) et la représentation/identification des cibles présentes dans le cadre d’un scénario naval à partir des échos radar enregistrés (problème inverse). Pour chaque représentation de la cible, son écho électromagnétique est calculé à partir d’un modèle de type Ensemble de Points Brillants (EPB), extrait en utilisant la technique CLEAN. Pour l’ensemble d’orientations possibles de la cible, les modèles EPB sont réunis à travers une Représentation Unifiée (EPB-RU). La dynamique de la cible est simulée à partir de modèles de réalité virtuelle correspondant à de petits objets flottant sur la surface de la mer. Le masquage introduit par les vagues ainsi que le fouillis de mer sont également prise en compte. L’identification des cibles est effectuée à partir des images ISAR 2D et 3D, reconstruites en utilisant un signal émis à large bande et la méthode d’imagerie superrésolution. Plusieurs ensembles d’attributs sont extraits à partir des images reconstruites en utilisant essentiellement les Contours Actifs Déformables. Différents classifieurs (KNN, PMC, SART ou SVM) sont ensuite mis en œuvre afin d’identifier la cible observée. L’application des outils de simulation développés est illustrée à la fin de la thèse au travers de la modélisation / représentation de plusieurs cibles radar dans un scénario naval simplifié
The thesis is devoted to the problem of the naval target characterization when seen by a broadband, surveillance costal radar. Two essential aspects of this problematic are considered: the realistic modeling of naval targets radar echo in marine environment (direct problem) and the representation/identification of the targets in a naval scenario using echoed radar signal (inverse problem). For each target orientation, the electromagnetic echo is computed using a Scattering Center Model (SCM), extracting using CLEAN technique For all target orientations, SCMs are combined in a Global SCM model. Target dynamics is simulated using virtual reality models of small-sized objects floating on the sea surface. Wave-introduced target masking and sea clutter are also accounted for. Target identification is performed using 2D and 3D ISAR images, constructed using broadband scanning signals and superresolution methods. Different kinds of descriptive targets features are issued from ISAR images essentially using Active Deformable Contours. KNN, MLP, SART or SVM classifiers are used to identify scanned targets. Finally, the joint application of all developed simulation tools illustrates modeling and representation of a few radar targets in a simplified naval scenario

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Wilson, Damian R. "Advanced polarization and Doppler radar techniques to study precipitation microphysics." Thesis, University of Reading, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.284066.

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Martínez, Vázquez Alberto. "Snow cover monitoring techniques with gb-SAR." Doctoral thesis, Universitat Politècnica de Catalunya, 2008. http://hdl.handle.net/10803/6922.

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Los radares de apertura sintética basados en tierra (GB-SAR) son instrumentos que, aun siendo relativamente jóvenes, se utilizan con éxito para monitorizar operacionalmente deslizamientos de tierra. Por otra parte, el manto nivoso se ha estudiado tradicionalmente a nivel local con sensores invasivos o con radares de onda continua. El trabajo presentado en esta tesis contribuye a la conjunción de ambos campos: el uso de sensores GB-SAR para la monitorización del manto nivoso. En los capítulos 5, 6 y 7 se muestran las tres técnicas desarrolladas: cálculo de la altura del manto nivoso, cálculo del volumen de nieve desplazado en una avalancha, y detección y clasificación de avalanchas.
La altura del manto nivoso se calcula a partir de la fase interferométrica diferencial de dos adquisiciones SAR consecutivas bajo la hipótesis de nieve seca y asumiendo un modelo de nieve de una capa. El volumen desplazado en una avalancha se obtiene mediante la resta de dos modelos del terreno digitales (DTM) generados justo antes y después del fenómeno avalancha. Los DTMs se obtienen con el modo topográfico del instrumento: dos antenas separadas una cierta distancia reciben simultáneamente los ecos de una tercera antena que transmite. La tercera técnica de monitorización, detección y clasificación de avalanchas, se realiza mediante la magnitud de la coherencia compleja entre dos imágenes SAR consecutivas. Las avalanchas de nieve presentan valores de coherencia muy bajos en el área afectada, que puede ser identificada mediante un modelo basado en características morfológicas y estadísticas. En la presente tesis se presenta un innovador algoritmo para la detección y clasificación de avalanchas.
El GB-SAR del Joint Research Centre, una vez mejorado para permitir su uso continuado 24h al día y 7 días a la semana (capítulo 3), ha sido utilizado para desarrollar y verificar las técnicas mencionadas anteriormente. Se han realizado medidas durante seis inviernos, que han proporcionado más de 120000 imágenes SAR a una frecuencia aproximada de 12 minutos por imagen. Se han estudiado dos emplazamientos, cada uno con características diferentes con el fin de verificar el uso operativo de las técnicas bajo condiciones reales. Los resultados muestran que la obtención de la altura del manto nivoso es posible pero su aplicación está limitada al campo experimental ya que su uso está condicionado por fuertes restricciones. Un estudio de viabilidad posteriormente confirmado con medidas muestra, en cambio, las limitaciones de precisión de los instrumentos GB-SAR para obtener una estima del volumen de nieve desplazado en una avalancha. Finalmente, la técnica más prometedora es la de detección y clasificación de avalanchas, la cuál se demuestra factible y robusta desde un punto de vista operativo y práctica desde una perspectiva de usuario final.
Ground-based synthetic aperture radars (GB-SAR) are instruments that, although relatively young, are operationally used to monitor landslides with sub-millimetre accuracy. There are however other application fields that deserve some attention.
Monitoring of the snow cover and, in particular, of those processes associated with the snow avalanches are a clear example of this. To date, monitoring of the snow cover has been traditionally carried out at local scale either with invasive sensors or with continuous wave (CW) radars, while at wider scales air- or satellite-borne sensors have been employed. The work presented in this PhD thesis is a first attempt to study the potential use of GB-SAR sensors to monitor the snow cover. Three techniques for monitoring snow cover with GB-SAR are presented through Chapters 5, 6 and 7: snow height retrieval, snow avalanche volume retrieval and avalanche events detection and classification.
Snow height is retrieved by using the differential interferometric phase of two consecutive SAR acquisitions under the assumption of single layer model and dry snow conditions. The volume displaced in a snow avalanche is computed by subtracting two digital terrain models (DTM) generated immediately before and after the avalanche event.
DTMs are obtained with the topographic interferometric mode of the instrument: a spatial base line separates two antennas that simultaneously receive the echoes of a third transmitting antenna. The third monitoring technique, avalanche detection and classification, is achieved identifying low-coherence anomalies in the coherence image between two successive SAR acquisitions. Snow avalanches present a low-coherence signature that can be identified by a morphological and statistical parameter model. A novel detection and classification scheme for snow avalanches is proposed.
The Joint Research Centre's GB-SAR sensor, upgraded to allow continuou operation 24 hours a day 7 days a week, also as part of the work of this thesis (Chapter 3), was used to develop and assess the before mentioned techniques. Measurements were carried out during six winters, providing more than 120000 SAR images at a rate of one image every 12 minutes approximately. Two test sites were studied, each with different characteristics in order to assess under real conditions the operational use of the monitoring techniques. Results show that snow height retrieval is achievable but remains, for the moment, an on-going research topic due to strong constraints limiting its use. A feasibility study is presented showing the accuracy limitations of GB-SAR to compute the snow volume involved in an avalanche. Finally, the most promising technique is snow avalanche detection and classification, which is demonstrated to be feasible and robust from an operational point of view and practical from an end user perspective.

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Middleton, Robert. "Techniques for homodyne dechirp-on-receive linearly frequency modulated radar." Thesis, University of St Andrews, 2011. http://hdl.handle.net/10023/1843.

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This thesis presents work done to extend and improve the operation of homodyne dechirp-on-receive linearly frequency modulated radars. First, an investigation of the effect of common phase errors on the point response function of the radar is described. The dependence on the window function of the degradation due to phase errors is investigated, and a simple, precise, and general approach for calculating the degraded Point Spread Function (PSF) is described and demonstrated. This method is shown to be particularly useful when investigating the effect of chirp nonlinearity on the PSF. Next, a method for focussing range profiles that are degraded by chirp nonlinearity is described. This method is based on two established methods, the Phase Gradient Algorithm (PGA) and a time-domain re-sampling technique. The technique is entirely hardware independent, allowing any homodyne dechirp-on-receive linearly frequency modulated radar to be focussed. Where suitable archive signal data exists, focussed imagery can even be produced from radars that no longer exist. The complete algorithm and details of the implementation are described, and the technique is demonstrated on three representative radar cases: extreme chirp nonlinearity, typical chirp nonlinearity, and a retrospective case. In all of the cases, it was shown that the PSF was dramatically improved. A technique based on down conversion by aliasing for reducing the required sampling rate is described, and a simple technique for calculating suitable sampling rates is presented. This method is demonstrated for a typical application in which sampling rate reduction might be required, namely Moving Target Indication (MTI). The MTI application is described and quantified, including a simple technique for choosing suitable radar operation parameters. The MTI technique with subsampling was demonstrated in software simulations and in a simple radar experiment. A Synthetic Aperture Radar (SAR) test bench for researching component performance and scatterer properties in the context of SAR was developed. An appropriate image formation processing algorithm was found and modified to better suit the task of a short data collection baseline and drifting centre frequencies, both of which are present in the test bench situation. Software was written to collect data, to control the hardware, and to process the signals into SAR images. A data simulator was written to test the image formation algorithm implementation; it also served as a useful tool for investigating the effect of signal errors on the quality of the resultant SAR imagery. A suitable oscillator was chosen for the task, based on phase noise and centre frequency stability considerations, both of which are quantified and discussed. Preliminary SAR imagery was produced, indicating that the system operates correctly and in agreement with comparable systems.

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Kirkpantur-cadallli, Atiye Asli. "An Investigation Of Jamming Techniques Through A Radar Receiver Simulation." Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/12609079/index.pdf.

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In this study, various jamming techniques and their effects on detection and tracking performance have been investigated through a radar receiver simulation that models a search radar for target acquisition and single-target tracking radar during track operation. The radar is modeled as looking at airborne targets, and hence clutter is not considered. Customized algorithms have been developed for the detection of target azimuth angle, range and Doppler velocity within the modeled geometry and chosen radar parameters. The effects of varying parameters like jamming-to-signal ratio (JSR) and jamming signal`s Doppler shift have been examined in the analysis of jamming effectiveness.

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Purseyyed, Behruz. "The application of aperture synthesis techniques to satellite radar altimetry." Thesis, University College London (University of London), 1990. http://discovery.ucl.ac.uk/10047468/.

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Radar altimetry over the ocean is now a well established discipline of satellite remote sensing, providing measurements of mean height, significant waveheight and surface wind speed. In contrast, radar altimetry over non-ocean surfaces, to obtain topography of land and polar ice sheets, is still a new idea. The difference between these two situations is that the ocean surface is essentially flat with a very small vertical extent, so a broad-beam pulse-limited mode radar altimeter having a relatively small antenna is sufficient to give very accurate measurements of the ocean mean height. However for topographic surfaces, variations in the elevation can be much higher, and using a conventional altimeter causes serious problems, such as interpretation error and misregistration of a measured range, which cannot be normally corrected. To avoid these problems, a considerably narrower beam antenna has to be used to localise the surface under observation. This requires very large antenna structures, which would be both complex and costly. This thesis investigates the application of aperture synthesis techniques to narrow-beam altimetry as an alternative to physically large antennas, to achieve high along-track resolution. It considers the analysis of the involved factors and design parameters, errors, data handling and signal processing requirements and methods for fixing the antenna beam accurately with the ultimate goal of providing a dynamic global altimetric database. In the second half of the thesis, an experimental aircraft-borne altimeter is examined. Details of the design, construction and evaluation of a prototype system are described. This radar includes several novel features, such as aperture synthesis with full-deramp range processing, digital chirp generation, bistatic FMCW operation and off-line digital signal processing. Also a series of experiments are arranged for this radar to examine its performance to process the signature of corner reflector targets, and consideration is given to the extension of these ideas to a satellite-borne instrument.

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Pacheco, Joe 1978. "Finite difference techniques for body of revolution radar cross section." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/8121.

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Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2000.
Includes bibliographical references (p. 267-272).
Although a number of radar cross section prediction techniques have been developed which exploit body of revolution symmetry, the use of finite-difference techniques with these geometries has not been throughly explored. This thesis investigates several finite-difference approaches which vary both in the approximations they introduce as well as the computational resources they require. These techniques include body of revolution finite-difference time-domain methods with both staircase and conformal grids, a hybrid FD-TD/geometrical optics method, and a body of revolution parabolic wave equation method. In addition, the use of the monostatic-bistatic equivalence principle is explored in approximating monostatic RCS at multiple angles from a single FD-TD simulation. Both canonical and more realistic BOR targets are modeled. The results from these techniques are compared, with each other and with method of moment predictions, physical theory of diffraction predictions, and analytic results. From these comparisons the tradeoffs possible between accuracy and computation with this collection of finite-difference tools is determined.
by Joe Pacheco, Jr.
M.Eng.

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Borrion, H. "Study of processing techniques for radar non-cooperative target recognition." Thesis, University College London (University of London), 2007. http://discovery.ucl.ac.uk/1444030/.

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Radar is a powerful tool for detecting and tracking airborne targets such as aircraft and missiles by day and night. Nowadays, it is seen as a genuine solution to the problem of target recognition. Recent events showed that cooperative means of identification such as the IFF transponders carried by most aircraft are not entirely reliable and can be switched off by terrorists. For this reason, it is important that target identification be obtained through measurements and reconnaissance based on non-cooperative techniques. In practice, recognition is achieved by comparing the electromagnetic sig nature of a target to a set of others previously collected and stored in a library. Such signatures generally represent the targets reflectivity as a function of space. A common representation is known as one-dimensional high-resolution range-profile (HRRP) and can be described as the projection of the reflectivity along the direction of propagation of the wave. When the measured signature matches a template, the target is identified. The main drawback of this technique is that signatures greatly vary with aspect-angle so that measurements must be made for many angles and in three dimensions. This implies a potentially large cost as large datasets must be created, stored and processed. Besides, any modification of the target structure may yield incorrect classification results. Instead, other processing techniques exist that rely on recent mathematical algorithms. These techniques can be used to extract target features directly from the radar data. Because of the direct relation with target geometry, these feature-based methods seem to be suitable candidates for reducing the need of large databases. However, their performances and their domains of validity are not known. This is especially true when it comes to real targets for at least three reasons. First, the performance of the methods varies with the signal-to-noise ratio. Second, man-made targets arc often more complex than just a set of independent theoretical point-like scatterers. Third, these targets are made up of a large number of scattering elements so that mathematical assumptions are not met. In conclusion, the physical correctness of the computational models are questionable. This thesis investigates the processing techniques that can be used for non-cooperative target recognition. It demonstrates that the scattering-centre extraction is not suitable for the model-based approach. In contrast, it shows that the technique can be used with the feature-based approach. In particular, it investigates the recognition when achieved directly in the z-domain and proposes a novel algorithm that exploits the information al ready in the database for identifying the signal features that corresponds to physical scatterers on the target. Experiments involving real targets show that the technique can enhance the classification performance and therefore could be used for non-cooperative target recognition.

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Belloni, Carole. "Deep learning and featured-based classification techniques for radar imagery." Thesis, Ecole nationale supérieure Mines-Télécom Atlantique Bretagne Pays de la Loire, 2019. http://www.theses.fr/2019IMTA0164.

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Une plateforme autonome en mouvement dotée d'un système radar peut générer des images Radar à Synthèse d'Ouverture (RSO ou SAR). Ces images fournissent des informations stratégiques pour des applications civiles et militaires. Elles peuvent être acquises de jour commede nuit dans des conditions météorologiques variées. Des algorithmes visant à la Reconnaissance Automatique de Cible (RAC ou ATR) sont alors utiles pour assister voire automatiser la prise dedécision. En effet, l’interprétation de ces images peut être complexe, y compris pour un opérateur expérimenté. La classification d'images du domaine visible génère un intérêt important des chercheurs, en partie grâce à la profusion des données. Par conséquent, des méthodes robustes de classification par descripteurs et deep learning ont été développées pour les images visibles. A l’inverse, une problématique essentielle rencontrée lors du développement d'algorithmes pour la RAC RSO est la rareté des données accessibles au public. Une difficulté supplémentaire est la variabilité des phénomènes physiques lors de l’acquisition radar. Les méthodes de classification des images optiques pourraient être adaptées pour les images RSO. Une nouvelle base de données d'images RSO Inverse (RSOI ou ISAR) est proposée dans cette thèse. Elle contient des images d'entraînement et de test obtenues dans des configurations variées. Une technique visant à générer des images artificielles supplémentaires est aussi développée. L’objectif est d’améliorer l’efficacité de l’apprentissage des algorithmes de classification nécessitant de nombreuses images d'entraînement, tels que les réseaux de neurones. Cette technique consiste à simuler un bruit SAR réaliste sur les images initiales. Une segmentation basée sur des Modèles de Mélange de Gaussiennes (MMG ou GMM) est adaptée à des images RSO à polarisation simple. Des descripteurs conçus pour caractériser des images optiques sont utilisés dans le domaine RSO afin de classifier des cibles après segmentation et leurs performances respectives sont comparées. Une nouvelle architecture de réseau de neurones, appelée pose-informed, est développée. Elle prend en compte les effets de l’orientation de la cible sur son apparence dans les images RSO. Les résultats présentés montrent que cette architecture permet une amélioration significative de la classification par rapport à une architecture standard. Au-delà des performances, un enjeu cléréside dans l’explicativité des méthodes issues du deep learning. Un ensemble d’outils analytiques sont présentés afin faciliter la compréhension du processus de décision du réseau de neurones. Ils permettent, entre autres, l’identification des zones vues comme essentielles à la classification par le réseau de neurones
Autonomous moving platforms carrying radar systems can synthesise long antenna apertures and generate Synthetic Aperture Radar (SAR) images. SAR images provide strategic information for military and civilian applications and they can be acquired day and night under a wide range of weather conditions. Because the interpretation of SAR images is a common challenge, Automatic Target Recognition (ATR) algorithms can help assist with decision-making when the operator is in the loop or when the platforms are fully autonomous. One of the main limitations of developing SAR ATR algorithms is the lack of suitable and publicly available data. Optical images classification, instead, has recently attracted significantly more research interest because of the number of potential applications and the profusion of data. As a result, robust feature-based and deep learning classification methods have been developed for optical imaging that could be applied to the SAR domain. In this thesis, a new Inverse SAR (ISAR) dataset consisting of test and training images acquired under a range of geometrical conditions is presented. In addition, a method is proposed to generate extra synthetic images, by simulating realistic SAR noise on the original images, and increase the training efficiency of classification algorithms that require a wealth of data, such as deep neural networks. A Gaussian Mixture Model (GMM) segmentation approach is adapted to segment single-polarised SAR images of targets. Features proposed to characterise optical images are transferred to the SAR domain to carry out target classification after segmentation and their respective performanceis compared. A new pose-informed deep learning network architecture, that takes into account the effects of target orientation on target appearance in a SAR image, is proposed. The results presented in this thesis show that the use of this architecture provides a significant performance improvement for almost all datasets used in this work over a baseline network. Understanding the decision-making process of deep networks is another key challenge of deep learning. To address this issue, a new set of analytical tools is proposed that enables the identification, amongst other things, of the location of the algorithm focus points that lead to high level classification performance

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Frantz, Xavier. "Software packages performance evaluation of basic radar signal processing techniques." Master's thesis, Faculty of Engineering and the Built Environment, 2019. http://hdl.handle.net/11427/30160.

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This dissertation presents a radar signal processing infrastructure implemented on scripting language platforms. The main goal is to determine if any open source scripted packages are appropriate for radar signal processing and if it is worthwhile purchasing the more expensive MATLAB, commonly used in industry. Some of the most common radar signal processing techniques were considered, such as pulse compression, Doppler processing and adaptive filtering for interference suppression. The scripting languages investigated were the proprietary MATLAB, as well as open source alternatives such as Octave, Scilab, Python and Julia. While the experiments were conducted, it was decided that the implementations should have algorithmic fairness across the various software packages. The first experiment was loop based pulse compression and Doppler processing algorithms, where Julia and Python outperformed the rest. A further analysis was completed by using vectors to index matrices instead of loops, where possible. This saw a significant improvement in all of the languages for Doppler processing implementations. Although Julia performed extremely well in terms of speed, it utilized the most memory for the processing techniques. This was due to its garbage collector not automatically clearing the memory heap when required. The adaptive LMS (least mean squares) filter designs were a different form of analysis, as a vector of data was required instead of a matrix of data. When processing a vector or one dimensional array of data, Julia outperformed the rest of the software packages significantly, approximately a 10 times speed improvement. The experiments indicated that Python performed satisfactorily in terms of speed and memory utilization. Physical RAM of computer systems is, however, constantly improving, which will mitigate the memory issue for Julia. Overall, Julia is the best open source software package to use, as its syntax is similar to MATLAB compared with Python, and it is improving rapidly as Julia developers are constantly updating it. Other disadvantage of Python is that the mathematical signal processing is an add-on realized by modules such as NumPy.

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Damtie, B. (Baylie). "New incoherent scatter radar measurement techniques and data analysis methods." Doctoral thesis, Oulun yliopisto, 2004. http://urn.fi/urn:isbn:9514273125.

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Abstract This dissertation presents new incoherent scatter radar measurement techniques and data analysis methods. The measurements used in the study were collected by connecting a computer-based receiver to the EISCAT (European Incoherent SCATter) radar on Svalbard. This hardware consists of a spectrum analyzer, a PCI-bus-based programmable digital I/O card and a desktop computer with a large-capacity hard disk. It takes in the 70-MHz signal from the ESR (Eiscat Svalbard Radar) signal path and carries out down-conversion, AD conversion, quadrature detection, and finally stores the output samples effective sampling rate is 1 MHz, large enough to span all the frequency channels used in the experiment. Hence the total multichannel signal was stored instead of separate lagged products for each frequency channel, which is the procedure in the standard hardware. This solution has some benefits including elimination of ground clutter with only a small loss in statistical accuracy. The capability of our hardware in storing the incoherent scatter radar signals directly allows us to use very flexible and versatile signal processing methods, which include clutter suppression, filtering, decoding, lag prole calculation, inversion and optimal height integration. The performance of these incoherent scatter radar measurement techniques and data analysis methods are demonstrated by employing an incoherent scatter experiment that applies a new binary phase code. Each bit of this code has been further coded by a 5-bit Barker code. In the analysis, stochastic inversion has been used for the first time in decoding Barker-coded incoherent scatter measurements, and this method takes care of the ambiguity problems associated with the measurements. Finally, we present new binary phase codes with corresponding sidelobe-free decoding filters that maximize the signal-to-noise ratio (SNR) and at the same time eliminate unwanted sidelobes completely
Original papers The original papers are not included in the electronic version of the dissertation. Lehtinen, M., Markkanen, J., Väänänen, A., Huuskonen, A., Damtie, B., Nygrén, T., & Rahkola, J. (2002). A new incoherent scatter technique in the EISCAT Svalbard Radar. Radio Science, 37(4), 3-1-3–14. https://doi.org/10.1029/2001rs002518 Damtie, B., Nygrén, T., Lehtinen, M. S., & Huuskonen, A. (2002). High resolution observations of sporadic-E layers within the polar cap ionosphere using a new incoherent scatter radar experiment. Annales Geophysicae, 20(9), 1429–1438. https://doi.org/10.5194/angeo-20-1429-2002 Damtie, B., Lehtinen, M. S., & Nygrén, T. (2004). Decoding of Barker-coded incoherent scatter measurements by means of mathematical inversion. Annales Geophysicae, 22(1), 3–13. https://doi.org/10.5194/angeo-22-3-2004 Lehtinen, M. S., Damtie, B., & Nygrén, T. (2004). Optimal binary phase codes and sidelobe-free decoding filters with application to incoherent scatter radar. Annales Geophysicae, 22(5), 1623–1632. https://doi.org/10.5194/angeo-22-1623-2004

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Mestre-Quereda, Alejandro. "Advanced Processing Techniques and Applications of Synthetic Aperture Radar Interferometry." Doctoral thesis, Universidad de Alicante, 2019. http://hdl.handle.net/10045/101167.

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Synthetic Aperture Radar interferometry (InSAR) is a powerful and established technique, which is based on exploiting the phase difference between pairs of SAR images, and which aims to measure changes in the Earth’s surface. The quality of the interferometric phase is therefore the most crucial factor for deriving reliable products by means of this technique. Unfortunately, the quality of the phase is often degraded due to multiple decorrelation factors, such as the geometrical or temporal decorrelation. Accordingly, central to this PhD thesis is the development of advanced processing techniques and algorithms to extensively reduce such disturbing effects caused by decorrelation. These new techniques include an improved range spectral filter which fully utilizes an external Digital Elevation Model (DEM) to reduce geometrical decorrelation between pairs of SAR images, especially in areas strongly influenced by topography where conventional methods are limited; an improved filter for the final interferometric phase the goal of which is to remove any remaining noise (for instance, noise caused by temporal decorrelation) while, simultaneously, phase details are appropriately preserved; and polarimetric optimization algorithms which also try to enhance the quality of the phase by exploring all the polarization diversity. Moreover, the exploitation of InSAR data for crop type mapping has also been evaluated in this thesis. Specifically, we have tested if the multitemporal interferometric coherence is a valuable feature which can be used as input to a machine learning algorithm to generate thematic maps of crop types. We have shown that InSAR data are sensitive to the temporal evolution of crops, and, hence, they constitute an alternative or a complement to conventional radiometric, SAR-based, classifications.

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Chini, Marco <1973&gt. "Radar and optical remote sensing techniques for earthquake damage mapping." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2008. http://amsdottorato.unibo.it/863/1/Tesi_Chini_Marco.pdf.

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Chini, Marco <1973&gt. "Radar and optical remote sensing techniques for earthquake damage mapping." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2008. http://amsdottorato.unibo.it/863/.

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Charlton, Matthew. "Ground penetrating radar techniques for the determination of subsurface moisture variability." Thesis, King's College London (University of London), 2002. https://kclpure.kcl.ac.uk/portal/en/theses/ground-penetrating-radar-techniques-for-the-determination-of-subsurface-moisture-variability(51fdd61c-75d5-429b-a592-e1cb4b4ef816).html.

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Chan, Tsz K. "Experimental studies on microwave detection and imaging of targets in clutter using correlation techniques /." Thesis, Connect to this title online; UW restricted, 1998. http://hdl.handle.net/1773/6011.

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Chang, Paul Chinling. "Near zone radar imaging and feature capture of building interiors." Columbus, Ohio : Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1197399599.

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Brown, Sarah Caroline Mellows. "High resolution polarimetric imaging of biophysical objects using synthetic aperture radar." Thesis, University of Sheffield, 1998. http://etheses.whiterose.ac.uk/10223/.

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A synthetic aperture microwave near-field system is used to image biophysical objects in order to investigate the nature of radar-target interaction. Two different imaging algorithms for focusing data collected over a two-dimensional planar aperture are investigated. The first of these is the single frequency backward propagation technique which is mathematically simple to implement and provides a high degree of resolution. Secondly, a multifrequency development of the backward propagation algorithm is presented and derived from two separate perspectives. This latter algorithm, known as the auto-focusing algorithm, requires no information about the range of the target from the aperture. Full characterisation by simulation of both algorithms is carried out and different filtering techniques are investigated. The backward propagation algorithm is applied to the polarimetric imaging of three different leafless trees and a sugar beet plant at the X-band frequency of 10GHz. The images so produced demonstrate that the backscattered signal is dependent on the orientation of individual tree elements with respect to the polarisation. Furthermore, multiple scattering terms can be identified within the structure of the tree. The auto-focusing algorithm is applied to the polarimetric imaging of two trees at 10GHz and repeat measurements are made over several months. As with the single frequency measurements, the backscattered signal is dependent on the orientation of individual tree elements relative to the polarisation. The relative contributions from the leaves and branches of the trees to the backscattered signal are assessed and found to be seasonally dependent. Measurements are also carried out to investigate the variation of backscatter from a beech tree with varying incidence angle. It is demonstrated that at small angles of incidence, the leaves are the dominant source of backscatter but at large incidence angles, the branches and trunk of the tree have the greatest contrbution.

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Suvarna, Sushil Sheena. "Reconstruction of Ground Penetrating Radar Images using techniques based on Optimization." NCSU, 2004. http://www.lib.ncsu.edu/theses/available/etd-01282004-143415/.

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Ground Penetrating Radar (GPR) is an instrument used in semi-automated construction systems. In principal, images of subsurface objects such as pipes and mines may be detected and potentially measured. The detection of utilities is complicated by a combination of the complexity involved in the data collection technique of the GPR and the irregularities present beneath the surface. This thesis provides the initial results in the development of an algorithm to invert the effects of these corruptions and return images, which are exact in the placement and conformation of subterranean objects. The technique employed is a deconvolution-like method that utilizes a maximum a posteriori (MAP) based optimization method to estimate the best reconstruction. Mean field annealing (MFA) using gradient descent is the optimization method used. Using this technique, single objects in the field of observation were reconstructed to within an acceptable percentage of their original shape. Further work would involve reconstructing multiple objects in the field of observation as well as considering features other than hyperbolae that correspond to objects.

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Barrett, Brian Edward. "Ground penetrating radar techniques for quantifying water distribution in glacial ice." Thesis, University of Leeds, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.441173.

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Wilkinson, Andrew John. "Techniques for 3-D surface reconstruction using synthetic aperture radar interferometry." Thesis, University College London (University of London), 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.299243.

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Akerson, Jerome Jeffrey 1961. "Numerical techniques for electromagnetic applications in microelectronic and radar imaging systems." Thesis, Massachusetts Institute of Technology, 1998. http://hdl.handle.net/1721.1/46116.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1998.
Includes bibliographical references (p. 227-242).
by Jerome J. Akerson.
Ph.D.

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Sekak, Fatima. "Microwave radar techniques and dedicated signal processing for Vital Signs measurement." Thesis, Université de Lille (2018-2021), 2021. https://pepite-depot.univ-lille.fr/LIBRE/EDENGSYS/2021/2021LILUN033.pdf.

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Dans le contexte de la sécurisation des systèmes de transport, la surveillance à courte distance de l’activité des personnes, en particulier du conducteur dans un véhicule, constitue un enjeu majeur dans l’amélioration du système d’aide à la conduite. L’application visée dans ce travail concerne principalement le domaine du ferroviaire.Les fréquences respiratoire et cardiaque du conducteur sont des indicateurs clés pour l’évaluation de l’état physiologique. Les méthodes de mesure conventionnelles de ces signes vitaux reposent sur des capteurs opérant en contact direct avec la peau. Par conséquent, le caractère intrusif de ces solutions ne s’avère pas adapté au domaine du transport, en particulier du fait de la gêne induite. Dans le cadre de ces travaux, une solution radar hyperfréquence opérant à faible puissance est proposée pour la mesure en continue des signaux d’activités respiratoire et cardiaque. En particulier, les signaux physiologiques (battements du cœur, mouvement mécanique de la cage thoracique) sont des indicateurs de l’activité humaine qui peuvent être détectés à distance (jusqu’à une dizaine de mètres) au moyen d’ondes électromagnétiques hyperfréquences rayonnées.Bien que la littérature montre un engouement grandissant pour le développement de techniques radars dédiés à la surveillance des personnes, il n’existe pas, à ce jour, de dispositif commercial robuste, sensible et précis. Une analyse fine des paramètres électriques et géométriques de la technique radar est proposée dans ce travail afin d’identifier les sources d’incertitudes, de définir les paramètres optimaux, de valider expérimentalement la solution proposée. Un traitement de signal original, basé sur l’approche cyclostationnaire, est mis en œuvre afin d’extraire les paramètres d’intérêt dans des environnements de mesure de référence ou perturbés. Les solutions matérielles proposées associées à un traitement de signal optimal permettent d’entrevoir des architectures de radar adaptées aux contingences hors laboratoire
In the context of securing transportation systems, short-range monitoring of people's activity, in particular the driver's activity in a vehicle, is a major issue in the improvement of the driver assistance system. The application targeted in this work concerns mainly the railway domain.Respiratory and heart rates of the driver are key indicators for the evaluation of the physiological state. Conventional methods of measuring these vital signs rely on sensors operating in direct contact with the skin. Therefore, the intrusive character of these solutions is not suited for the transportation domain, especially because of the induced discomfort. In this work, a microwave radar solution operating at low power is proposed for the continuous measurement of respiratory and cardiac activity signals. In particular, physiological signals (heartbeat, mechanical movement of the rib cage) are indicators of human activity that can be detected at a distance (up to ten meters) using radiated microwave electromagnetic waves.Although the literature shows a growing interest in the development of radar techniques dedicated to the surveillance of people, there is no robust, sensitive and accurate commercial device available to date. A detailed analysis of the electrical and geometrical parameters of the radar technique is proposed in this work in order to identify the sources of uncertainties, to define the optimal parameters, to validate experimentally the proposed solution. An original signal processing, based on the cyclostationary approach, is implemented in order to extract the parameters of interest in reference or disturbed measurement environments. The proposed hardware solutions associated with an optimal signal processing allow to foresee radar architectures adapted to non-laboratory contingencies

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Ma, Zhenhua. "Advanced feature based techniques for landmine detection using ground penetrating radar." Diss., Columbia, Mo. : University of Missouri-Columbia, 2007. http://hdl.handle.net/10355/4971.

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Thesis (M.S.)--University of Missouri-Columbia, 2007.
The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on November 11, 2008) Includes bibliographical references.

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Williams, Mary Moulton. "Radar cross-section data encoding based on parametric spectral estimation techniques." Thesis, This resource online, 1994. http://scholar.lib.vt.edu/theses/available/etd-06162009-063346/.

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Wang, Yuanxun. "Radar signature prediction and feature extraction using advanced signal processing techniques /." Digital version accessible at:, 1999. http://wwwlib.umi.com/cr/utexas/main.

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Ali, Mohammed Hussain. "The design and implementation of radar clutter modelling and adaptive target detection techniques." Thesis, Cranfield University, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.276334.

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Shakya, Indu Lal. "High capacity CDMA and collaborative techniques." Thesis, University of Sussex, 2008. http://sro.sussex.ac.uk/id/eprint/7619/.

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The thesis investigates new approaches to increase the user capacity and improve the error performance of Code Division Multiple Access (CDMA) by employing adaptive interference cancellation and collaborative spreading and space diversity techniques. Collaborative Coding Multiple Access (CCMA) is also investigated as a separate technique and combined with CDMA. The advantages and shortcomings of CDMA and CCMA are analysed and new techniques for both the uplink and downlink are proposed and evaluated. Multiple access interference (MAI) problem in the uplink of CDMA is investigated first. The practical issues of multiuser detection (MUD) techniques are reviewed and a novel blind adaptive approach to interference cancellation (IC) is proposed. It exploits the constant modulus (CM) property of digital signals to blindly suppress interference during the despreading process and obtain amplitude estimation with minimum mean squared error for use in cancellation stages. Two new blind adaptive receiver designs employing successive and parallel interference cancellation architectures using the CM algorithm (CMA) referred to as ‘CMA-SIC' and ‘BA-PIC', respectively, are presented. These techniques have shown to offer near single user performance for large number of users. It is shown to increase the user capacity by approximately two fold compared with conventional IC receivers. The spectral efficiency analysis of the techniques based on output signal-to interference-and-noise ratio (SINR) also shows significant gain in data rate. Furthermore, an effective and low complexity blind adaptive subcarrier combining (BASC) technique using a simple gradient descent based algorithm is proposed for Multicarrier-CDMA. It suppresses MAI without any knowledge of channel amplitudes and allows large number of users compared with equal gain and maximum ratio combining techniques normally used in practice. New user collaborative schemes are proposed and analysed theoretically and by simulations in different channel conditions to achieve spatial diversity for uplink of CCMA and CDMA. First, a simple transmitter diversity and its equivalent user collaborative diversity techniques for CCMA are designed and analysed. Next, a new user collaborative scheme with successive interference cancellation for uplink of CDMA referred to as collaborative SIC (C-SIC) is investigated to reduce MAI and achieve improved diversity. To further improve the performance of C-SIC under high system loading conditions, Collaborative Blind Adaptive SIC (C-BASIC) scheme is proposed. It is shown to minimize the residual MAI, leading to improved user capacity and a more robust system. It is known that collaborative diversity schemes incur loss in throughput due to the need of orthogonal time/frequency slots for relaying source's data. To address this problem, finally a novel near-unity-rate scheme also referred to as bandwidth efficient collaborative diversity (BECD) is proposed and evaluated for CDMA. Under this scheme, pairs of users share a single spreading sequence to exchange and forward their data employing a simple superposition or space-time encoding methods. At the receiver collaborative joint detection is performed to separate each paired users' data. It is shown that the scheme can achieve full diversity gain at no extra bandwidth as inter-user channel SNR becomes high. A novel approach of ‘User Collaboration' is introduced to increase the user capacity of CDMA for both the downlink and uplink. First, collaborative group spreading technique for the downlink of overloaded CDMA system is introduced. It allows the sharing of the same single spreading sequence for more than one user belonging to the same group. This technique is referred to as Collaborative Spreading CDMA downlink (CS-CDMA-DL). In this technique T-user collaborative coding is used for each group to form a composite codeword signal of the users and then a single orthogonal sequence is used for the group. At each user's receiver, decoding of composite codeword is carried out to extract the user's own information while maintaining a high SINR performance. To improve the bit error performance of CS-CDMA-DL in Rayleigh fading conditions, Collaborative Space-time Spreading (C-STS) technique is proposed by combining the collaborative coding multiple access and space-time coding principles. A new scheme for uplink of CDMA using the ‘User Collaboration' approach, referred to as CS-CDMA-UL is presented next. When users' channels are independent (uncorrelated), significantly higher user capacity can be achieved by grouping multiple users to share the same spreading sequence and performing MUD on per group basis followed by a low complexity ML decoding at the receiver. This approach has shown to support much higher number of users than the available sequences while also maintaining the low receiver complexity. For improved performance under highly correlated channel conditions, T-user collaborative coding is also investigated within the CS-CDMA-UL system.

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Rogron, Bertrand. "Qualité et performances de l'image radar dans le domaine complexe." Toulouse 3, 1995. http://www.theses.fr/1995TOU30070.

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Ce document porte sur l'utilisation de l'amplitude et de la phase des images radar a travers deux themes: le premier concerne la qualite de l'image. La scene radar contient des cibles ponctuelles qui permettent d'obtenir la reponse impulsionnelle du systeme avec une precision generalement suffisante. La methode de recherche est entierement automatique et permet d'isoler les ambiguites en azimut. Le niveau de bruit sur l'image est estime en exploitant le caractere blanc de son spectre. Le principe de la mesure repose sur le calcul des premiers termes de la fonction d'autocorrelation du signal complexe en distance, effectue en des regions de l'image de puissances differentes. Le deuxieme concerne l'interferometrie par radar. Dans le domaine de la classification de surfaces agricoles, on utilise generalement les informations de puissance qui sont donnees par le radar a des dates successives. A partir d'un couple d'images du satellite ers1, il est montre que l'interferometrie apporte des informations complementaires, liees aux evolutions des surfaces a petite et a grande echelle. Chaque pixel peut se decomposer en deux parties, coherente et incoherente, ce qui permet de dissocier la puissance des elements stables, de celle des elements instables. Lorsque les elements du sol sont suffisamment stables, il est possible d'utiliser un couple d'images pour ameliorer la resolution en distance jusqu'a un facteur deux. Grace a une modelisation de la prise de vue, on peut connaitre de maniere precise les parametres permettant de construire l'image super-resolue. La technique et les algorithmes sont valides par l'analyse de cibles ponctuelles sur un couple d'images du satellite ers1

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Dissertations / Theses on the topic 'Radar techniques'

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