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Coherent optical signal processing systems typically require dynamic, low-loss phase changes of an optical signal. Waveform generation employing phase modulation is an important application area. In particular, laser radar systems have been shown to perform better with non-linear frequency chirps. This work shows how dynamically tunable integrated optical ring resonators are able to produce such phase changes to a signal in an effective manner and offer new possibilities for the detection of phase-modulated optical signals. When designing and fabricating dynamically tunable integrated optical ring resonators for any application, system level requirements must be taken into account. For frequency chirped laser radar systems, the primary system level requirements are good long range performance and fine range resolution. These mainly depend on the first sidelobe level and mainlobe width of the autocorrelation of the chirp. Through simulation, the sidelobe level and mainlobe width of the autocorrelation of the non-linear frequency modulated chirp generated by a series of integrated optical ring resonators is shown to be significantly lower than the well-known tangent-FM chirp. Proof-of-concept experimentation is also important to verify simulation assumptions. A proof-of-concept experiment employing thermally tunable Silicon-Nitride integrated optical ring resonators is shown to generate non-linear frequency modulated chirp waveforms with peak instantaneous frequencies of 28 kHz. Besides laser radar waveform generation, three other system level applications of dynamically tunable integrated optical ring resonators are explored in this work. A series of dynamically tunable integrated optical ring resonators is shown to produce constant dispersion which can then help extract complex spectral information. Broadband photonic RF phase shifting for beam steering of a phased array antenna is also shown using dynamically tunable integrated optical ring resonators. Finally all-optical pulse compression for laser radar using dynamically tunable integrated optical ring resonators is shown through simulation and proof-of-concept experimentation.

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Le suivi des espaces urbanisés et de leurs dynamiques spatio-temporelles représente un enjeu important pour la population urbaine, autant sur le plan environnemental, économique et social. Avec le lancement des satellites portant des radars à synthèse d’ouverture de la nouvelle génération (TerraSAR-X, COSMO-SkyMed, ALOS, RADARSAT-2,Sentinel-1, Constellation RADARSAT), il est possible d’obtenir des séries temporelles d’images avec des résolutions spatiales et temporelles fines. Ces données multitemporelles aident à mieux analyser et décrire les structures urbaines et leurs variations dans l’espace et dans le temps. L’interférométrie par satellite est effectuée en comparant les phases des images RSO prises à différents passages du satellite au-dessus du même territoire. En optant pour des positions du satellite séparées d’une longue ligne de base, l’InSAR mène à la création des modèles numériques d’altitude (MNA). Si cette ligne de base est courte et à la limite nulle, nous avons le cas de l’interférométrie différentielle (DInSAR) qui mène à l’estimation du mouvement possible du terrain entre les deux acquisitions. Pour toutes les deux applications de l’InSAR, deux opérations sont importantes qui garantissent la génération des interférogrammes de qualité. La première est le filtrage du bruit omniprésent dans les phases interférométriques et la deuxième est le déroulement des phases. Ces deux opérations deviennent particulièrement complexes en milieu urbain où au bruit des phases s’ajoutent des fréquents sauts et discontinuités des phases dus à la présence des bâtiments et d’autres structures surélevées. L’objectif de cette recherche est le développement des nouveaux algorithmes de filtrage et de déroulement de phase qui puissent mieux performer que les algorithmes considérés comme référence dans ce domaine. Le but est d’arriver à générer des produits InSAR de qualité en milieu urbain. Concernant le filtrage, nous avons établi un algorithme qui est une nouvelle formulation du filtre Gaussien anisotrope adaptatif. Quant à l’algorithme de déroulement de phase, il est fondé sur la minimisation de l’énergie par un algorithme génétique ayant recours à une modélisation contextuelle du champ de phase. Différents tests ont été effectués avec des images RSO simulées et réelles qui démontrent le potentiel de nos algorithmes qui dépasse à maints égards celui des algorithmes standard. Enfin, pour atteindre le but de notre recherche, nous avons intégré nos algorithmes dans l’environnement du logiciel SNAP et appliqué l’ensemble de la procédure pour générer un MNA avec des images RADARSAT-2 de haute résolution d’un secteur de la Ville de Montréal (Canada) ainsi que des cartes des mouvements du terrain dans la région de la Ville de Mexico (Mexique) avec des images de Sentinel-1 de résolution plutôt moyenne. La comparaison des résultats obtenus avec des données provenant des sources externes de qualité a aussi démontré le fort potentiel de nos algorithmes. / The monitoring of urban areas and their spatiotemporal dynamics is an important issue for the urban population, at the environmental, economic, as well as social level. With the launch of satellites carrying next-generation synthetic aperture radars (TerraSAR-X, COSMO-SkyMed, ALOS, RADARSAT-2, Sentinel-1, Constellation RADARSAT), it is possible to obtain time series of images with fine temporal and spatial resolutions. These multitemporal data help to better analyze and describe urban structures, and their variations in space and time. Satellite interferometry is performed by comparing the phases of SAR images taken at different satellite passes over the same territory. By opt-ing for satellite positions separated by a long baseline, InSAR leads to the creation of digital elevation models (DEM). If this baseline is short and, at the limit zero, we have the case of differential interferometry (DInSAR) which leads to the estimation of the possible movement of the land between the two acquisitions. In both InSAR applica-tions, two operations are important that ensure the generation of quality interferograms. The first is the filtering of ubiquitous noise in the interferometric phases and the second is the unwrapping of the phases. These two operations become particularly complex in urban areas where the phase noise is added to the frequent jumps and discontinuities of phases due to the presence of buildings and other raised structures. The objective of this research is the development of new filtering and phase unwrap-ping algorithms that can perform better than algorithms considered as reference in this field. The goal is to generate quality InSAR products in urban areas. Regarding filtering, we have established an algorithm that is a new formulation of the adaptive anisotropic Gaussian filter. As for the phase unwrapping algorithm, it is based on the minimization of energy by a genetic algorithm using contextual modelling of the phase field. Various tests have been carried out with simulated and real SAR images that demonstrated the potential of our algorithms that in many respects exceeds that of standard algorithms. Finally, to achieve the goal of our research, we integrated our algorithms into the SNAP software environment and applied the entire procedure to generate a DEM with high-resolution RADARSAT-2 images from an area of the City of Montreal (Canada) as well as maps of land movement in the Mexico City region (Mexico) with relatively medium-resolution Sentinel-1 images. Comparison of the results with data from external quality sources also demonstrated the strong potential of our algorithms.

<div>Electrical nerve stimulation (ENS) is an emerging therapy for many neurological disorders. Compared with conventional one-way stimulations, closed-loop ENS approaches increase the stimulation efficacy and minimize patient's discomfort by constantly adjusting the stimulation parameters according to the feedback biomarkers from patients. Wireless neurostimulation devices capable of both stimulation and telemetry of recorded physiological signals are welcome for closed-loop ENS systems to improve the quality and reduce the costs of treatments, and real-time digital signal processing (DSP) engines processing and extracting features from recorded signals can reduce the data transmission rate and the resulting power consumption of wireless devices. Electrically-evoked compound action potential (ECAP) is an objective measure of nerve activity and has been used as the feedback biomarker in closed-loop ENS systems including neural response telemetry (NRT) systems and a newly proposed autonomous nerve control (ANC) platform. It's desirable to design a DSP engine for real-time processing of ECAP in closed-loop ENS systems. </div><div><br></div><div>This thesis focuses on developing the DSP architecture for real-time processing of ECAP, including stimulus artifact rejection (SAR), denoising, and extraction of nerve fiber responses as biomedical features, and its VLSI implementation for optimal hardware costs. The first part presents the DSP architecture for real-time SAR and denoising of ECAP in NRT systems. A bidirectional-filtered coherent averaging (BFCA) method is proposed, which enables the configurable linear-phase filter to be realized hardware efficiently for distortion-free filtering of ECAPs and can be easily combined with the alternating-polarity (AP) stimulation method for SAR. Design techniques including folded-IIR filter and division-free averaging are incorporated to reduce the computation cost. The second part presents the fiber-response extraction engine (FREE), a dedicated DSP engine for nerve activation control in the ANC platform. FREE employs the DSP architecture of the BFCA method combined with the AP stimulation, and the architecture of computationally efficient peak detection and classification algorithms for fiber response extraction from ECAP. FREE is mapped onto a custom-made and battery-powered wearable wireless device incorporating a low-power FPGA, a Bluetooth transceiver, a stimulation and recording analog front-end and a power-management unit. In comparison with previous software-based signal processing, FREE not only reduces the data rate of wireless devices but also improves the precision of fiber response classification in noisy environments, which contributes to the construction of high-accuracy nerve activation profile in the ANC platform. An application-specific integrated circuit (ASIC) version of FREE is implemented in 180-nm CMOS technology, with total chip area and core power consumption of 19.98 mm² and 1.95 mW, respectively. </div><div><br></div>