Orientador: Francisco Sekiguchi de Carvalho e Buchmann / Resumo: Estuários são ambientes heterogêneos, altamente complexos, e condicionados por diversos fatores ambientais. Nenhum estuário é igual a outro, e é esta diversidade que os torna tão importantes do ponto de vista da conservação. A grande quantidade de recursos naturais disponíveis nesses ambientes favorece o desenvolvimento de assentamentos urbanos nas suas margens, podendo comprometer o equilíbrio natural. A partir do conhecimento detalhado dos sistemas estuarinos é possível traçar metas assertivas para a conservação e gestão destes ambientes tão singulares. O presente estudo visa a caracterização e comparação dos estuários dos rios Itaguaré e Guaratuba (Bertioga, SP) quanto aos seus parâmetros geo-físico-químicos. A área de estudo está localizada na planície costeira da Bacia Hidrográfica da Baixada Santista e inserida no Parque Estadual Restinga de Bertioga. Foram realizados levantamentos semestrais de batimetria e imageamento com sonar de varredura lateral, com o intuito de conhecer as profundidades e feições de fundo dos estuários, avaliando a dinâmica de processos erosivos e deposicionais. Medições mensais de salinidade, temperatura e turbidez foram realizadas ao longo de um ano, visando avaliar o comportamento sazonal da intrusão salina e da zona de máxima turbidez. Para verificar variações na granulometria, foram coletadas amostras de sedimentos nos mesmos pontos de medição das variáveis físico-químicas da água. Os resultados foram avaliados de forma integrada, utilizando... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Estuaries are highly complex heterogeneous environments, conditioned by different environmental factors. Every estuary has particular characteristics, and this diversity makes them so important for conservation. The great amount of available natural resources in these environments contributes to urban settlement developments on their surroundings, which may compromise their natural balance. Detailed knowledge of estuarine systems helps establish assertive goals for the conservation and management of these unique environments. This study aims to characterize and compare Itaguaré and Guaratuba estuaries (Bertioga, SP) regarding their geophysical-chemical characteristics. The study area is located on the Baixada Santista Basin’s coastal plain, and inserted in the Restinga of Bertioga State Park. Biannual bathymetry and side scan sonar surveys were carried in order to evaluate erosive and depositional processes affecting depths and bottom features of the estuaries. Salinity, temperature and turbidity measurements were carried out monthly over a period of one year to evaluate seasonal behavior of saline intrusion and the estuarine turbidity maximum. Sediment samples were collected in order to verify granulometry variations. Results were evaluated in an integrated manner, using geoprocessing and spatial analysis techniques, coupled with secondary data of mareography and precipitation, analyzing the influence of meteoceanographic factors in the water column and the background config... (Complete abstract click electronic access below) / Mestre

Le sujet porte sur l'étude de systèmes SAS (Synthetic Aperture Sonar) multistatiques. Ces systèmes permettent d'obtenir des images de cibles mieux résolues qu'avec un sonar classique à partir d'ondes acoustiques. Le SAS est largement exploité en configuration monostatique mais il existe très peu d'études à ce jour en SAS multistatique. Le travail consiste donc à évaluer les performances en configuration bistatique et multistatique et à les comparer à celles connues en configuration monostatique. Une méthode de calcul utilisée en radar a donc été mise en oeuvre en sonar de façon à expliciter la résolution en configuration bistatique, ce qui est un résultat original de ce travail. L'algorithme classiquement utilisé pour reconstruire des images repose sur l'hypothèse que la cible est une somme de points brillants. Cette hypothèse n'est pas bien adaptée en acoustique sous-marine. Un nouvel algorithme a donc été développé dans le but de se rapprocher des phénomènes de diffraction présents à l'interface entre l'eau et la cible. Le modèle de champ diffracté est obtenu par la combinaison d'équations intégrales de frontière avec l'approximation de Kirchhoff. Une méthode de reconstruction d'images par transformée de Fourier 2D de ce modèle a été implémentée et testée sur des données simulées, puis sur des données obtenues lors d'essais en cuve. Le nouvel algorithme montre une meilleure précision de la reconstruction et la capacité de pouvoir extraire de l'information quantitative de la cible. L'intérêt des configurations multistatiques pour la reconnaissance de cibles a également été démontré dans ces travaux de thèse. / This study deals with multistatic SAS (Synthetic Aperture Sonar) systems. SAS are high resolution imaging systems compared to classical sonar ones. The SAS technique is largly exploited in the monostatic configuration but few studies already exist in multistatic SAS. Thus, the work consists in evaluating resolution and detection performances in bistatic and multistatic configurations. Then, the objective is to compare these performances to monostatic ones. A radar method has been adapted to sonar to compute bistatic performances and this is an original result of this work.The classical algorithm to reconstruct images from acoustical waves lies on the hypothesis that the target is a sum of point scatterers. This hypothesis is not really well adapted to underwater acoustics that is why a new algogorithm has been developped in this study. The new algorithm would be better adapted to scattering diffraction phenomena at the interface between water and target than the classical one. The scattered field model of the target is obtained by combinating boundary integral equations and the Kirchhoff Approximation. An imaging reconstruction method by 2D Fourier Transform of this model has been implemented and tested on numerical and experimental datas. The new algorithm allow a better reconstruction accurency and is able to give quantitative information on targets. The interest of multistatic configurations for target identification has also been demonstrated in this PhD work.

Autonomous underwater vehicle (AUV) navigation has been a challenging problem for a long time. Navigation is challenging due to the drift present in underwater environments and the lack of precise localisation systems such as GPS. Therefore, the uncertainty of the vehicle’s pose grows with the mission’s duration. This research investigates methods to form constraints on the vehicle’s pose throughout typical surveys. Current underwater navigation relies on acoustic sensors. Side Scan Sonar (SSS) is cheaper than Multibeam echosounder (MBES) but can generate 2D intensity images of wide sections of the seafloor instead of 3D representations. The methodology consists in extracting information from pairs of side-scan sonar images representing overlapping portions of the seafloor and computing the sensor pose transformation between the two reference frames of the image to generate constraints on the pose. The chosen approach relies on optimisation methods within a Simultaneous Localisation and Mapping (SLAM) framework to directly correct the trajectory and provide the best estimate of the AUV pose. I tested the optimisation system on simulated data to evaluate the proof of concept. Lastly, as an experiment trial, I tested the implementation on an annotated dataset containing overlapping side-scan sonar images provided by SMaRC. The simulated results indicate that AUV pose error can be reduced by optimisation, even with various noise levels in the measurements. / Navigering av autonoma undervattensfordon (AUV) har länge varit ett utmanande problem. Navigering är en utmaning på grund av den drift som förekommer i undervattensmiljöer och bristen på exakta lokaliseringssystem som GPS. Därför ökar osäkerheten i fråga om fordonets position med uppdragets längd. I denna forskning undersöks metoder för att skapa begränsningar för fordonets position under typiska undersökningar. Nuvarande undervattensnavigering bygger på akustiska sensorer. Side Scan Sonar (SSS) är billigare än Multibeam echosounder (MBES) men kan generera 2D-intensitetsbilder av stora delar av havsbotten i stället för 3D-bilder. Metoden består i att extrahera information från par av side-scan sonarbilder som representerar överlappande delar av havsbotten och beräkna sensorns posetransformation mellan bildens två referensramar för att generera begränsningar för poset. Det valda tillvägagångssättet bygger på optimeringsmetoder inom en SLAM-ram (Simultaneous Localisation and Mapping) för att direkt korrigera banan och ge den bästa uppskattningen av AUV:s position. Jag testade optimeringssystemet på simulerade data för att utvärdera konceptet. Slutligen testade jag genomförandet på ett annoterat dataset med överlappande side-scan sonarbilder från SMaRC. De simulerade resultaten visar att AUV:s poseringsfel kan minskas genom optimering, även med olika brusnivåer i mätningarna.

This thesis addresses the issues of data sparsity in the sonar domain. A data pipeline is set up to generate and enhance sonar data. The possibilities and limitations of using cycleGAN as a tool to enhance simulated sonar images for the purpose of training neural networks for detection and classification is studied. A neural network is trained on the enhanced simulated sonar images and tested on real sonar images to evaluate the quality of these images.The novelty of this work lies in extending previous methods to a more general framework and showing that GAN enhanced simulations work for complex tasks on field data.Using real sonar images to enhance the simulated images, resulted in improved classification compared to a classifier trained on solely simulated images. / Denna rapport ämnar undersöka problemet med gles data för djupinlärning i sonardomänen. Ett dataflöde för att generera och höja kvalitén hos simulerad sonardata sätts upp i syfte att skapa en stor uppsättning data för att träna ett neuralt nätverk. Möjligheterna och begränsningarna med att använda cycleGAN för att höja kvalitén hos simulerad sonardata studeras och diskuteras. Ett neuralt nätverk för att upptäcka och klassificera objekt i sonarbilder tränas i syfte att evaluera den förbättrade simulerade sonardatan.Denna rapport bygger vidare på tidigare metoder genom att generalisera dessa och visa att metoden har potential även för komplexa uppgifter baserad på icke trivial data.Genom att träna ett nätverk för klassificering och detektion på simulerade sonarbilder som använder cycleGAN för att höja kvalitén, ökade klassificeringsresultaten markant jämfört med att träna på enbart simulerade bilder.

Approved for public release, distribution unlimited / The Anti-Submarine Warfare screen design simulation is a program that provides a model for operations in anti-submarine warfare (ASW). The purpose of the program is to aid ASW commanders, allowing them to configure an ASW screen, including the sonar policy, convoy speed, and the number of ships, to gain insight into how these and other factors beyond their control, such as water conditions, impact ASW effectiveness. It is also designed to be used as a training tool for ASW officers. The program is implemented in Java programming language, using the Multi Agent System (MAS) technique. The simulation interface is a Horizontal Display Center (HDC) which is very similar to a MEKO200 class Frigate Combat Information Center's (CIC) HDC. The program uses Extensible Markup Language (XML) files for reading data for program scenarios; parameters are initialized before each run time begins. The simulation also provides all the output data at the end of run time for analysis purposes. The program user's goal, and the purpose of the program, is to decrease the number of successful attacks against surface vessels by changing the configuration parameters of the ASW screen, to reflect sonar policy, convoy speed or number of ships in the simulation. Ongoing use of the program can provide data needed to anticipate required operational needs in future ASW situations. / Lieutenant Junior Grade, Turkish Navy

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.

This manuscript describes a methodology to combine environmental models, acoustic signal predictions, statistical detection models and operations research to form a framework for calculating and communicating performance. This methodology has been applied to undersea target detection systems and has come to be known as Performance Surface modeling. The term Performance Surface refers to a geo-spatial representation of the predicted performance of one or more sensors constrained by all-source forecasts for a geophysical area of operations. Recent improvements in ocean, atmospheric and underwater acoustic models, along with advances in parallel computing provide an opportunity to forecast the effects of a complex and dynamic acoustic environment on undersea target detection system performance. This manuscript describes a new process that calculates performance in a straight-forward "sonar-equation" manner utilizing spatially complex and temporally dynamic environmental models. This performance model is constructed by joining environmental acoustic signal predictions with a detection model to form a probabilistic prediction which is then combined with probabilities of target location to produce conditional, joint and marginal probabilities. These joint and marginal probabilities become the scalar estimates of system performance. This manuscript contains two invited articles recently accepted for publication. The first article describes the Performance Surface model development with sections on current applications and future extensions to a more stochastic model. The second article is written from the operational perspective of a Naval commanding officer with co-authors from the active force. Performance Surface tools have been demonstrated at the Naval Oceanographic Office (NAVOCEANO) and the Naval Oceanographic Anti-Submarine Warfare (ASW) Center (NOAC) in support of recent naval exercises. The model also has recently been a major representation for the "performance" layer of the Naval Meteorological and Oceanographic Command (NAVMETOCCOM) in its Battlespace on Demand strategy for supporting the Fleet with oceanographic products.

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Este trabalho descreve os aperfeiçoamentos realizados na plataforma robótica móvel ROMEO III, dando origem ao robô ROMEO III.v2, onde os três principais desafios da navegação de robôs móveis são atacados: a localização, o mapeamento e o planejamento da trajetória. Esta nova configuração herda as soluções utilizadas em suas versões anteriores: o algoritmo A* para realizar o planejamento da trajetória e a utilização de encoders unido à detecção de marcos artificiais para a localização. Assim, para atacar o problema do mapeamento, o ROMEO III.v2 utiliza: 1) a metodologia Occupancy Grid para caracterizar o ambiente, 2) um arranjo de sonares com dois receptores e um transmissor para adquirir os dados do espaço em volta da plataforma (permitindo identificar o ângulo de recepção da onda ultra-sônica, além de estimar possíveis erros de leitura) e 3) uma bússola eletrônica é utilizada para identificar a orientação inicial da plataforma. Diversos testes são apresentados neste trabalho e mostram que o robô ROMEO III.v2 alcançou a sua finalidade dentro das limitações impostas pelo sonar: navegar autonomamente em um ambiente estático, estruturado e desconhecido.

A classificação de sinais acústicos é de importância fundamental para as unidades navais e aeronavais, tanto navios e essencialmente submarinos, quanto para aeronaves com capacidade antissubmarino (P-3AM, da FAB). Neste contexto, empregou-se o método de Support Vector Machine (SVM) para realizar a classificação dos navios, com base na análise de tons característicos produzidos pelos seus sinais acústicos. Comparando os resultados decorrentes do uso de Redes Neurais Artificiais aos obtidos com uso do SVM, concluiu-se que este segundo método gerou um aumento de performance no classificador em função das características extraídas dos tons. Contudo os tempos computacionais foram considerados elevados, razão porque há a necessidade de maiores investigações para adequar o emprego do SVM em um ambiente operacional.