In synthetic aperture radar (SAR) and inverse synthetic aperture radar (ISAR), an imaging radar emits electromagnetic waves of varying frequencies towards a target and the backscattered waves are collected. By either moving the radar antenna or rotating the target and combining the collected waves, a much longer synthetic aperture can be created. These radar measurements can be used to determine the radar cross-section (RCS) of the target and to reconstruct an estimate of the target. However, the reconstructed images will suffer from spectral leakage effects and are limited in resolution. Many methods of enhancing the images exist and some are based on deep learning. Most commonly the deep learning methods rely on high-resolution ground truth data of the scene to train a neural network to enhance the radar images. In this thesis, a method that does not rely on any high-resolution ground truth data is applied to train a convolutional neural network to enhance radar images. The network takes a conventional ISAR image subject to spectral leakage effects as input and outputs an enhanced ISAR image which contains much more defined features. New RCS measurements are created from the enhanced ISAR image and the network is trained to minimise the difference between the original RCS measurements and the new RCS measurements. A sparsity constraint is added to ensure that the proposed enhanced ISAR image is sparse. The synthetic training data consists of scenes containing point scatterers that are either individual or grouped together to form shapes. The scenes are used to create synthetic radar measurements which are then used to reconstruct ISAR images of the scenes. The network is tested using both synthetic data and measurement data from a cylinder and two aeroplane models. The network manages to minimise spectral leakage and increase the resolution of the ISAR images created from both synthetic and measured RCSs, especially on measured data from target models which have similar features to the synthetic training data.  The contributions of this thesis work are firstly a convolutional neural network that enhances ISAR images affected by spectral leakage. The neural network handles complex-valued signals as a single channel and does not perform any rescaling of the input. Secondly, it is shown that it is sufficient to calculate the new RCS for much fewer frequency samples and angular positions and compare those measurements to the corresponding frequency samples and angular positions in the original RCS to train the neural network.

Additive tillverkning (AM) är en tillverkningsteknik som har använts i stor utsträckning i industrier de senaste åren. Electron beam melting (EBM) är en innovativ teknik för tillverkning inom ortopediska implantat- och flygindustrin för att EBM erbjuder hög produktivitet och lägre kostnad per del. Jämfört med traditionella tillverkningsmetoder kan EBM tillverka delar med betydande mekaniska egenskaper, men det finns några vanliga brister som hindrar EBMs förmåga att bli en vanligare bearbetningsmetod vid tillverkning. I detta arbete, som tar an formen av en State of the Art Rapport, introduceras EBM-metoden på teknisk nivå och jämförs med andra AM-metoder och konventionella tillverkningsmetoder. / Additive manufacturing (AM) is a manufacturing technology that has been widely used in industries in recent years. Electron beam melting (EBM) is an innovative technology for manufacturing of the orthopedic implant and aerospace industry because EBM offers high productivity and lower cost per part. Compared to traditional manufacturing methods, EBM can produce parts with significant mechanical properties, but there is some common shortcoming that prevent EBM's ability to become a more common processing method in manufacturing. This work, which takes the form of a State of the Art Report, introduces the EBM method at the technical level and compares with other AM methods and conventional manufacturing methods.

<p>Basic radar systems use electromagnetic wave reflections from targets to determine the motion characteristics of these targets. Synthetic Aperture Radar (SAR) systems use the reflections to produce target images as well. SAR is an imaging radar system that produces high resolution images of a scene or target by using radar motion to synthesize the antenna aperture. A SAR model to handle extended targets and point targets in faster time is presented, as are some simulated results. This thesis explains synthetic aperture concepts, the model used and a simulation of a SAR system. It runs through modelling point targets as well as extended targets by using the resolution cells of the radar, creating the raw signal data from the target information and then the signal processing that converts the raw data to a SAR image. The simulation was done for better understanding of synthetic aperture parameters and it was done in C++ programming language for improved processing speed. In comparison to previous simulations obtained from literature review, there is an increase in speed of more than 2.5 times as the number of targets increases, producing higher resolution images in less time. A model to handle extended targets was presented while also showing the imperfections due to the model assumptions. These assumptions are then explained as the best option in the absence of extra geographic information on the target scene.</p> / Master of Applied Science (MASc)

La rétrodiffusion associée aux effets de géométrie de surface à des angles d’incidence élevés (62°—76°) et pour quatres angles azimutaux (Q0, 3Q0, 60° et 90°) a été étudiée pour des champs de maïs du Québec (Canada) à l’aide de 3 images du ROS-C du Centre canadien de télédétection. Selon les conditions de drainage des champs, le couvert végétal apporte une plus ou moins grande contribution à la rétrodiffusion. L’effet de géométrie de surface est nettement plus prononcé (amplitude 3,2 dB) pour les champs de maïs sans drainage souterrain que ceux ayant un drainage souterrain (1,5 dB). Le contraste entre ces deux types de champ est rattaché aux différences de pente du couvert végétal ainsi qu’aux variations de biomasse.

International Telemetering Conference Proceedings / October 20-23, 2003 / Riviera Hotel and Convention Center, Las Vegas, Nevada / In this paper, we discuss a Block Adaptive Vector Quantization(BAVQ) Algorithm for Synthetic Aperture Radar(SAR). And we discuss a realization method of BAVQ algorithm for SAR raw data compressing in digital signal processor. Using the algorithm and the digital signal processor, we have compressed the SIR_C/X_SAR data.

In remote areas without conventional cellular service, satellite communication is often the only viable option. Handheld devices for use with satellite communication networks require a high transmit power to obtain a reliable signal. The need for a high transmit power makes it difficult for the device to meet specific absorption rate (SAR) restrictions. An adaptive beam forming technique for shaping radiation away from the user’s head is proposed. This technique uses a back-to-back patch antenna design with an impedance monitoring based system capable of adaptively controlling the pattern of the antenna. The adaptive antenna system was designed, simulated, fabricated, and measured. The system could detect a head phantom within 3 cm of the antenna. SAR levels were verified to be within safety restrictions at 3 cm through simulation. By turning off the patch facing the user’s head when the phone is transmitting, and the user’s head is within 3 cm, it was shown that SAR levels could be reduced to safe levels. / February 2017

Anteriormente, foi identificada a atividade esquistossomicida da piplartina, um alcalóide-amida isolado em nossos estudos de bioprospecção em plantas da família Piperaceae. Neste trabalho, foi analisada a estrutura e as propriedades de uma série de análogos da piplartina para avaliar a relação estrutura-atividade. A atividade de análogos sintéticos da piplartina foi avaliada in vitro em vermes adultos de S. mansoni. Primeiro, os análogos foram testados a 50 e 100 &mu;g/mL. Os compostos ativos foram selecionados para a determinação dos valores de IC50. Ao todo, 36 análogos com modificações em três regiões da piplartina foram avaliados. Todas as modificações tiveram uma influência negativa na atividade biológica; no entanto, uma seletividade específica entre os gêneros foi observada. Seis análogos tiveram os valores de IC50 determinados, variando entre 72,33 a 216,86 &mu;M. As diferenças na atividade esquistossomicida entre a piplartina e seus análogos podem ser atribuídas a alterações na forma, equilíbrio hidrofílico-lipofílico e distribuição de carga eletrostática. / Previously, the schistosomicidal activity of piplartine, an alkaloid-amide isolated in our bioprospection studies with plants from Piperaceae species, was identified. In this work, we analyzed the structure and properties of a series of piplartine derivatives to propose a structure-activity relationship model. In vitro activity was evaluated in S. mansoni adult worms exposed in vitro to piplartine synthetic analogs. First, analogs were screened at 50 and 100 &mu;g/mL. Active compounds were selected to the determination of IC50 values. A total of 36 synthetic piplartine analogs with modifications in three regions of the piplartine molecule were evaluated. All the modifications had a negative influence in the biological activity; nevertheless, a gender specific selectivity was observed. Of all the analogs, 6 had the IC50 values determined, ranging from 72.33 a 216.86 &mu;M. Differences in the schistosomicidal activity between piplartine and its analogs could be attributed to changes in shape, hydrophilic-lipophilic equilibrium and electrostatic charge distribution.

The growth of digital systems underscores the need to convert analog information to the digital domain at high speeds and with great accuracy. Analog-to-Digital Converter (ADC) calibration is often a limiting factor, requiring longer calibration times to achieve higher accuracy. The goal of this dissertation is to perform a fully digital background calibration using an arbitrary input signal for A/D converters. The work presented here adapts the cyclic "Split-ADC" calibration method to the time interleaved (TI) and successive approximation register (SAR) architectures. The TI architecture has three types of linear mismatch errors: offset, gain and aperture time delay. By correcting all three mismatch errors in the digital domain, each converter is capable of operating at the fastest speed allowed by the process technology. The total number of correction parameters required for calibration is dependent on the interleaving ratio, M. To adapt the "Split-ADC" method to a TI system, 2M+1 half-sized converters are required to estimate 3(2M+1) correction parameters. This thesis presents a 4:1 "Split-TI" converter that achieves full convergence in less than 400,000 samples. The SAR architecture employs a binary weight capacitor array to convert analog inputs into digital output codes. Mismatch in the capacitor weights results in non-linear distortion error. By adding redundant bits and dividing the array into individual unit capacitors, the "Split-SAR" method can estimate the mismatch and correct the digital output code. The results from this work show a reduction in the non-linear distortion with the ability to converge in less than 750,000 samples.

This thesis works through the design of a radar-based system for imaging snowpacks remotely and over large areas to assist in avalanche prediction. The key to such a system is the ability to image volumes of snow at shallow, spatially-varying angles of incidence. To achieve this prerequisite, the design calls for a ground-based Synthetic Aperture Radar (SAR) capable of generating three-dimensional, ultra-high-resolution images of a snowpack. To arrive at design parameters for this SAR, the thesis works through relevant principles in avalanche mechanics, alpine-snowpack geophysics, and electromagnetic scattering theory. The thesis also works through principles of radar, SAR, antenna, and image processing theory to this end. A preliminary system is implemented to test the feasibility of the overall design. The preliminary system demonstrates ultra-high-resolution, three-dimensional imaging capabilities and the ability to image the volume of multiple alpine snowpacks. Images of these snowpacks display the structural patterns indicative of different layers in the snowpacks. Possible attributions of the patterns to physical properties in the snowpack are explored, but conclusions are not arrived at. Finally, lessons from the implementation of this preliminary system are discussed in terms of opportunities to be capitalized upon and problems to be overcome in future systems that more faithfully realize the complete design set forth in the thesis.

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