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abstract: Peptide microarrays have been used in molecular biology to profile immune responses and develop diagnostic tools. When the microarrays are printed with random peptide sequences, they can be used to identify antigen antibody binding patterns or immunosignatures. In this thesis, an advanced signal processing method is proposed to estimate epitope antigen subsequences as well as identify mimotope antigen subsequences that mimic the structure of epitopes from random-sequence peptide microarrays. The method first maps peptide sequences to linear expansions of highly-localized one-dimensional (1-D) time-varying signals and uses a time-frequency processing technique to detect recurring patterns in subsequences. This technique is matched to the aforementioned mapping scheme, and it allows for an inherent analysis on how substitutions in the subsequences can affect antibody binding strength. The performance of the proposed method is demonstrated by estimating epitopes and identifying potential mimotopes for eight monoclonal antibody samples. The proposed mapping is generalized to express information on a protein's sequence location, structure and function onto a highly localized three-dimensional (3-D) Gaussian waveform. In particular, as analysis of protein homology has shown that incorporating different kinds of information into an alignment process can yield more robust alignment results, a pairwise protein structure alignment method is proposed based on a joint similarity measure of multiple mapped protein attributes. The 3-D mapping allocates protein properties into distinct regions in the time-frequency plane in order to simplify the alignment process by including all relevant information into a single, highly customizable waveform. Simulations demonstrate the improved performance of the joint alignment approach to infer relationships between proteins, and they provide information on mutations that cause changes to both the sequence and structure of a protein. In addition to the biology-based signal processing methods, a statistical method is considered that uses a physics-based model to improve processing performance. In particular, an externally developed physics-based model for sea clutter is examined when detecting a low radar cross-section target in heavy sea clutter. This novel model includes a process that generates random dynamic sea clutter based on the governing physics of water gravity and capillary waves and a finite-difference time-domain electromagnetics simulation process based on Maxwell's equations propagating the radar signal. A subspace clutter suppression detector is applied to remove dominant clutter eigenmodes, and its improved performance over matched filtering is demonstrated using simulations. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2014

Maritime surveillance radars are critical in commerce, transportation, navigation, and defense. However, the sea environment is perhaps the most challenging of natural radar backdrops because maritime radars must contend with electromagnetic backscatter from the sea surface, or sea clutter. Sea clutter poses unique challenges in very low grazing angle geometries, where typical statistical assumptions regarding sea clutter backscatter do not hold. As a result, traditional constant false alarm rate (CFAR) detection schemes may yield a large number of false alarms while objects of interest may be challenging to detect. Solutions posed in the literature to date have been either computationally impractical or lacked robustness. This dissertation explores whether fully polarimetric radar offers a means of enhancing detection performance in low grazing angle sea clutter. To this end, MIT Lincoln Laboratory funded an experimental data collection using a fully polarimetric X-band radar assembled largely from commercial off-the-shelf components. The Point de Chene Dataset, collected on the Atlantic coast of Massachusetts’ Cape Ann in October 2015, comprises multiple sea states, bandwidths, and various objects of opportunity. The dataset also comprises three different polarimetric transmit schemes. In addition to discussing the radar, the dataset, and associated post-processing, this dissertation presents a derivation showing that an established multiple input, multiple output radar technique provides a novel means of simultaneous polarimetric scattering matrix measurement. A novel scheme for polarimetric radar calibration using a single active calibration target is also presented. Subsequent research leveraged this dataset to develop Polarimetric Co-location Layering (PCL), a practical algorithm for mitigation of low grazing angle sea clutter, which is the most significant contribution of this dissertation. PCL routinely achieves a significant reduction in the standard CFAR false alarm rate while maintaining detections on objects of interest. Moreover, PCL is elegant: It exploits fundamental characteristics of both sea clutter and object returns to determine which CFAR detections are due to sea clutter. We demonstrate that PCL is robust across a range of bandwidths, pulse repetition frequencies, and object types. Finally, we show that PCL integrates in parallel into the standard radar signal processing chain without incurring a computational time penalty.

abstract: A critical problem for airborne, ship board, and land based radars operating in maritime or littoral environments is the detection, identification and tracking of targets against backscattering caused by the roughness of the sea surface. Statistical models, such as the compound K-distribution (CKD), were shown to accurately describe two separate structures of the sea clutter intensity fluctuations. The first structure is the texture that is associated with long sea waves and exhibits long temporal decorrelation period. The second structure is the speckle that accounts for reflections from multiple scatters and exhibits a short temporal decorrelation period from pulse to pulse. Existing methods for estimating the CKD model parameters do not include the thermal noise power, which is critical for real sea clutter processing. Estimation methods that include the noise power are either computationally intensive or require very large data records. This work proposes two new approaches for accurately estimating all three CKD model parameters, including noise power. The first method integrates, in an iterative fashion, the noise power estimation, using one-dimensional nonlinear curve fitting, with the estimation of the shape and scale parameters, using closed-form solutions in terms of the CKD intensity moments. The second method is similar to the first except it replaces integer-based intensity moments with fractional moments which have been shown to achieve more accurate estimates of the shape parameter. These new methods can be implemented in real time without requiring large data records. They can also achieve accurate estimation performance as demonstrated with simulated and real sea clutter observation datasets. The work also investigates the numerically computed Cram\'er-Rao lower bound (CRLB) of the variance of the shape parameter estimate using intensity observations in thermal noise with unknown power. Using the CRLB, the asymptotic estimation performance behavior of the new estimators is studied and compared to that of other estimators. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2019

Conventional fixed threshold detectors set a fixed threshold based on the overall statistical characteristics of the spatially uniform clutter over all ranges to give a specific probability of false alarm and detection. However, in radar applications clutter statistics are not known a priori. Constant False Alarm Rate (CFAR) techniques provide an adaptive threshold to estimate the clutter statistics and to distinguish targets from clutter. In Cell Averaging CFAR (CA-CFAR) the threshold is controlled by averaging the fixed size CFAR cells surrounding the cell under test. In this thesis, radar detection of targets in sea clutter modelled by compound Kdistribution is examined from a statistical detection viewpoint by Monte Carlo simulations. The performance of CA-CFAR processors is analysed under varying conditions of sea clutter spatial correlation and spikiness for several cases of false alarm probability, the length of cell size used in the CFAR processor and the number of pulses integrated prior to CA-CFAR processor. v The detection performance of CA-CFAR is compared with the performance of fixed threshold detection. The performance evaluations are quantified by CFAR loss. CFAR loss is defined as the increase in average signal to clutter ratio compared to that of fixed threshold, required to achieve a given probability of detection and probability of false alarm. Curves for CFAR loss to the spikiness and spatial correlation of clutter, number of pulses integrated and the length of cell size are presented.

abstract: Tracking a time-varying number of targets is a challenging dynamic state estimation problem whose complexity is intensified under low signal-to-noise ratio (SNR) or high clutter conditions. This is important, for example, when tracking multiple, closely spaced targets moving in the same direction such as a convoy of low observable vehicles moving through a forest or multiple targets moving in a crisscross pattern. The SNR in these applications is usually low as the reflected signals from the targets are weak or the noise level is very high. An effective approach for detecting and tracking a single target under low SNR conditions is the track-before-detect filter (TBDF) that uses unthresholded measurements. However, the TBDF has only been used to track a small fixed number of targets at low SNR. This work proposes a new multiple target TBDF approach to track a dynamically varying number of targets under the recursive Bayesian framework. For a given maximum number of targets, the state estimates are obtained by estimating the joint multiple target posterior probability density function under all possible target existence combinations. The estimation of the corresponding target existence combination probabilities and the target existence probabilities are also derived. A feasible sequential Monte Carlo (SMC) based implementation algorithm is proposed. The approximation accuracy of the SMC method with a reduced number of particles is improved by an efficient proposal density function that partitions the multiple target space into a single target space. The proposed multiple target TBDF method is extended to track targets in sea clutter using highly time-varying radar measurements. A generalized likelihood function for closely spaced multiple targets in compound Gaussian sea clutter is derived together with the maximum likelihood estimate of the model parameters using an iterative fixed point algorithm. The TBDF performance is improved by proposing a computationally feasible method to estimate the space-time covariance matrix of rapidly-varying sea clutter. The method applies the Kronecker product approximation to the covariance matrix and uses particle filtering to solve the resulting dynamic state space model formulation. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2015

L’incidence rasante est un problème spécifique, qui apparaît notamment lorsqu'une antenne est placée sur un mât (télécommunications, défense…) ou sur la côte (surveillance environnementale ou militaire de l'espace maritime). Elle rend la modélisation du problème de diffraction difficile, de par le faible niveau de rétrodiffusion et l’importance de phénomènes complexes comme la diffusion multiple. La question reste importante même si l’écho est très faible, puisqu’il est potentiellement suffisant pour perturber le bon fonctionnement de systèmes antennaires microondes sur un navire. Il porte de plus des informations intéressantes sur l’état de la mer, comme cela a été démontré aux bandes HF et VHF. Un modèle rigoureux de diffraction tridimensionnelle précédemment développé est étendu au calcul des quatre polarisations fondamentales (polarisations Horizontale et Verticale des ondes incidente et réfléchie). Il permet désormais de prendre en compte la conductivité finie de la surface, point crucial dans le cas d'une polarisation incidente Verticale. L’opérateur hyper-singulier impliqué dans l’équation intégrale discrétisée par la méthode des moments est étudié pour évaluer la précision des calculs numériques.Les méthodes approchées de diffraction permettent des calculs numériques beaucoup plus rapides, et sont donc en pratique incontournables. Le modèle rigoureux est donc utilisé, en conjonction avec des données expérimentales, pour servir de référence permettant d’étudier la précision, en incidence rasante et dans le cas de la surface de la mer, de ces méthodes approchées. Nous étudions en particulier la méthode à deux échelles GOSSA, et proposons une correction à son comportement aux angles rasants.Le mouvement de la surface de la mer crée un décalage de fréquence radar dans l’onde rétrodiffusée (effet Doppler), décalage mesuré expérimentalement et que l’algorithme de méthode des moments permet de simuler. Nous étudions par des simulations bidimensionnelles l’évolution du décalage Doppler micro onde avec l’incidence, et l’influence des nonlinéarités de la surface de la mer. Le comportement limite en incidence rasante est précisé, et les contributions respectives des phénomènes électromagnétiques et hydrodynamiques discutées. / The grazing incidence is a specific problem, which appears especially when an antenna is placed on a mast (telecommunications, defence...) or on the coast (environmental or military maritime spatial monitoring). The modelization of the scattering process in such a configuration is difficult, due to low backscattering and to the importance of complex phenomena such as multiple scattering. The issue remains important even if the echo is very low, because it is potentially sufficient to disturb the proper functioning of microwave antenna systems on a ship. Moreover, it carries interesting informations about the sea state, as was demonstrated in HF and VHF bands.A rigorous model of the three-dimensional scattering process, previously developed, is extended to the computation of the scattered fiel in the four fundamental polarizations (Horizontal and Vertical polarization of incident and reflected waves). It is now possible to take into account the finite conductivity of the surface, a crucial point when the incident field is vertically polarized. The hyper- singular operator involved in the integral equation discretized by the method of moments is studied to evaluate the accuracy of numerical calculations.The approximate methods of diffraction allow much faster numerical calculations, and are therefore essential. The rigorous model is used in conjunction with experimental data, as a reference to study the accuracy of such approximate methods, in the case of the sea surface at grazing incidence. We study in particular the two-scale method GOSSA and propose a correction to its behaviour at grazing angles. The motion of the sea surface creates a frequency shift in the radar backscattered wave (Doppler effect). This offset can be measured experimentally, our algorithm allows us to simulate it. We proceed to two-dimensional simulations showing the evolution of the Doppler shift with respect to the grazing angle, and show the influence of the nonlinearities in the sea model. The limit of the mean Doppler shift at very low grazing angles is studied, and the respective contributions of electromagnetic and hydrodynamic phenomena are discussed.

Radar signal processing techniques aim to suppress clutter to enable target detection. Many clutter suppression techniques have been developed to improve the detection performance in literature. Among these methods, the most widely known is MTI plus coherent integrator, which gives sufficient radar performance in various scenarios. However, when the correlation coefficient of clutter is small or the spectral separation between the target and clutter is small, classical approaches to clutter suppression fall short. In this study, we consider the ARMA spectral estimation performance in sea clutter modelled by compound K-distribution through Monte Carlo simulations. The method is applied for varying conditions of clutter spikiness and auto correlation sequences (ACS) depending on the radar operation. The performance of clutter suppression using ARMA spectral estimator, which will be called ARMA-CS in this work, is analyzed under varying ARMA model orders. To compare the clutter suppression of ARMA-CS with that of conventional methods, we use improvement factor (IF) which is the ratio between the output Signal to Interference Ratio (SIR) and input SIR as performance measure. In all cases, the performance of ARMA-CS method is better than conventional clutter suppression methods when the correlation among clutter samples is small or the spectral separation between target and clutter is small.

Game engines are well known for their use in the gaming industry but are starting to have an impact in other areas as well. Architecture, automotive, and the defence industry are today using these engines to visualise and, to some extent, test their products. In this thesis, we have examined how the game engine Unity could be used for simulating a radar with the purpose of detecting and measuring sea clutter. Following a pre-study examining different implementation approaches, it was decided to use ray tracing. The radar itself is simulated by using the camera to emit rays and having a plane object directly behind it act as a receiver. Rays are then individually traced for each pixel, propagating throughout the scene and saving information such as hit coordinates, distance travelled, and direction. By using the total travel distance of each ray that returned to the receiver, the phase of each ray is calculated. This is then used to compute the total amplitude, which represents the returned signal strength. Using a compute shader, most of the computations are done in parallel on the GPU, enabling millions of rays to be traced. As measuring sea clutter was an objective of the study, tests measuring the ocean were carried out. These used ocean surfaces with two different sea states, using the Phillips spectrum to generate realistic waves. A ship object was then tested in free space and on two different ocean surfaces. The calculated amplitude and the number of rays returned were used to determine the signal strength returned and the RCS of the object. The purpose of this was to compare with other results of sea clutter studied, observed both in the real world and in simulated scenarios, and determine if our approach could be a valid choice for the industry. Some results matched the findings of a similar study that used a professional radar simulation tool called OKTAL. Other results of sea clutter were found to not be realistic due to certain limitations. The current main limitation of our implementation is not being able to trace a large enough ocean surface with the finer details needed for realistic results. However, this could be solved by creating a better implementation. These findings suggest that simulating radar and sea clutter in Unity is a feasible approach worth continuing to explore. / Spelmotorer är välkända för sin användning inom spelindustrin men har också fått genomslag inom andra områden. Arkitektur, fordonsindustrin och försvarsindustrin använder idag dessa verktyg för att visualisera och till viss mån, även testa sina produkter. I detta examensarbete har vi undersökt hur spelmotorn Unity kan användas för att simulera en radar i syfte att detektera och mäta sjöklotter. Efter en förstudie där olika implementeringsmetoder undersöktes, beslutades det att använda strålspårning (eng. ray tracing). Själva radarn simuleras genom att använda kameraobjektet i Unity för att sända ut strålar. Bakom kameran finns ett planobjekt som fungerar som mottagare. Strålar spåras sedan individuellt för varje pixel och sprider sig genom en given scen. Samtidigt sparas information såsom träffkoordinater, den totala färdsträckan samt riktning. Genom att använda det totala färdavståndet för varje stråle som återvänt till mottagaren kan fasen för varje stråle beräknas. Detta kan sedan användas för att beräkna den totala returnerade amplituden, vilket motsvarar den returnerade signalstyrkan. Med hjälp av en "compute shader" kan databeräkningarna göras parallellt av GPU:n vilket underlättar när så många strålar ska spåras. Eftersom syftet med uppsatsen var mätning av simulerat sjöklotter, genomfördes tester för att mäta på ett simulerat hav. Havsytorna hade två olika sjöstadier, vilka genererades med Phillips-spektrumet för att få realistiska vågor. Ett fartygsobjekt testades sedan i frirymd och sedan även i de två olika havsytorna. Amplituden och mängden strålar som returnerades användes för att bestämma den totala returnerade signalstyrkan och "Radar Cross Section" (RCS) för objektet. Syftet med detta var att kunna jämföra med andra studier gällande sjöklotter, både simulerade som verklighetsbaserade och avgöra om vårt tillvägagångssätt kunde resultera i ett användbart verktyg för branschen. De olika amplituder och antalet strålar som vi fick tillbaka varierade beroende på vilka vinklar och havsytor som användes.Vissa resultat var inte realistiska jämfört med verkliga mätningar av sjöklotter. Det beror främst på våra nuvarande begränsningar i att inte kunna spåra en tillräckligt stor och tillräckligt detaljerad havsyta, vilket behövs för att mätningarna ska vara mer realistiska. Däremot matchade vi några resultat med de från en liknande studie, där verktyget OKTAL, som är ett professionellt radarsimuleringsverktyg, användes. Detta i kombination med möjligheterna för en förbättrad implementation tyder på att användningen av en spelmotor som Unity är ett intressant verktyg värd att vidareutforska radarsimuleringar med.

Le travail réalisé dans le cadre de cette thèse a pour but de caractériser des signaux aléatoires, rencontrés dans le domaine aérien et sous-marin, en s’appuyant sur une approche statistique. En traitement du signal, l'analyse statistique a longtemps été fondée sous l'hypothèse de Gaussianité des données. Cependant, ce modèle n'est plus valide dès lors que la densité de probabilité des données se caractérise par des phénomènes de queues lourdes et d'asymétrie. Une famille de lois est particulièrement adaptée pour représenter de tels phénomènes : les distributions α-stables. Dans un premier temps, les distributions α-stables ont été présentées et utilisées pour estimer des données synthétiques et réelles, issues d'un sondeur monofaisceau, dans une stratégie de classification de fonds marins. La classification est réalisée à partir de la théorie des fonctions de croyance, permettant ainsi de prendre en compte l'imprécision et l'incertitude liées aux données et à l'estimation de celles-ci. Les résultats obtenus ont été comparés à un classifieur Bayésien. Dans un second temps, dans le contexte de la surveillance maritime, une approche statistique à partir des distributions α-stables a été réalisée afin de caractériser les échos indésirables réfléchis par la surface maritime, appelés aussi fouillis de mer, où la surface est observée en configuration bistatique. La surface maritime a d'abord été générée à partir du spectre d'Elfouhaily puis la Surface Équivalente Radar (SER) de celle-ci a été déterminée à partir de l'Optique Physique (OP). Les distributions de Weibull et ont été utilisées et comparées au modèle α-stable. La validité de chaque modèle a été étudiée à partir d'un test de Kolmogorov-Smirnov. / The purpose of this thesis is to characterize random signals, observed in air and underwater context, by using a statistical approach. In signal processing, the hypothesis of Gaussian model is often used for a statistical study. However, the Gaussian model is not valid when the probability density function of data are characterized by heavy-tailed and skewness phenomena. A family of laws can fit these phenomena: the α-stable distributions. Firstly, the α-stable distribution have been used to estimate generated and real data, extracted from a mono-beam echo-sounder, for seabed sediments classification. The classification is made by using the theory of belief functions, which can take into account the imprecision and uncertainty of data and theirs estimations. The results have been compared to a Bayesian approach. Secondly, in a context a marine surveillance, a statistical study from the α-stable distribution has been made to characterize undesirable echo reflected by a sea surface, called sea clutter, where the sea surface is considered in a bistatic configuration. The sea surface has been firstly generated by the Elfouhaily sea spectrum and the Radar Cross Section (RCS) of the sea surface has been computed by the Physical Optics (PO). The Weibull and distributions have been used and the results compared to the α-stable model. The validity of each model has been evaluated by a Kolmogorov-Smirnov test.