Phase calibration of the EISCAT Svalbard Radar interferometer using optical satellite signatures

The link between natural ion-line enhancements in radar spectra and auroral activity has been the subject of recent studies but conclusions have been limited by the spatial and temporal resolution previously available. The next challenge is to use shorter sub-second integration times in combination with interferometric programmes to resolve spatial structure within the main radar beam, and so relate enhanced filaments to individual auroral rays. This paper presents initial studies of a technique, using optical and spectral satellite signatures, to calibrate the received phase of a signal with the position of the scattering source along the interferometric baseline of the EISCAT Svalbard Radar. It is shown that a consistent relationship can be found only if the satellite passage through the phase fringes is adjusted from the passage predicted by optical tracking. This required adjustment is interpreted as being due to the vector between the theoretical focusing points of the two antennae, i.e. the true radar baseline, differing from the baseline obtained by survey between the antenna foot points. A method to obtain a measurement of the true interferometric baseline using multiple satellite passes is outlined.

Mutual occlusion between real and virtual elements in Augmented Reality based on fiducial markers

Augmented Reality (AR) systems which use optical tracking with fiducial marker for registration have had an important role in popularizing this technology, since only a personal computer with a conventional webcam is required. However, in most these applications, the virtual elements are shown only in the foreground a real element does not occlude a virtual one. The method presented enables AR environments based on fiducial markers to support mutual occlusion between a real element and many virtual ones, according to the elements position (depth) in the environment. © 2012 IEEE.

Multimodal augmented reality system for surgical microscopy

Image-guided, computer-assisted neurosurgery has emerged to improve localization and targeting, to provide a better anatomic definition of the surgical field, and to decrease invasiveness. Usually, in image-guided surgery, a computer displays the surgical field in a CT/MR environment, using axial, coronal or sagittal views, or even a 3D representation of the patient. Such a system forces the surgeon to look away from the surgical scene to the computer screen. Moreover, this kind of information, being pre-operative imaging, can not be modified during the operation, so it remains valid for guidance in the first stage of the surgical procedure, and mainly for rigid structures like bones. In order to solve the two constraints mentioned before, we are developing an ultrasoundguided surgical microscope. Such a system takes the advantage that surgical microscopy and ultrasound systems are already used in neurosurgery, so it does not add more complexity to the surgical procedure. We have integrated an optical tracking device in the microscope and an augmented reality overlay system with which we avoid the need to look away from the scene, providing correctly aligned surgical images with sub-millimeter accuracy. In addition to the standard CT and 3D views, we are able to track an ultrasound probe, and using a previous calibration and registration of the imaging, the image obtained is correctly projected to the overlay system, so the surgeon can always localize the target and verify the effects of the intervention. Several tests of the system have been already performed to evaluate the accuracy, and clinical experiments are currently in progress in order to validate the clinical usefulness of the system.

Application of Time-Delay Estimation to Mixed Reality Multisensor Tracking

Spatial tracking is one of the most challenging and important parts of Mixed Reality environments. Many applications, especially in the domain of Augmented Reality, rely on the fusion of several tracking systems in order to optimize the overall performance. While the topic of spatial tracking sensor fusion has already seen considerable interest, most results only deal with the integration of carefully arranged setups as opposed to dynamic sensor fusion setups. A crucial prerequisite for correct sensor fusion is the temporal alignment of the tracking data from several sensors. Tracking sensors are typically encountered in Mixed Reality applications, are generally not synchronized. We present a general method to calibrate the temporal offset between different sensors by the Time Delay Estimation method which can be used to perform on-line temporal calibration. By applying Time Delay Estimation on the tracking data, we show that the temporal offset between generic Mixed Reality spatial tracking sensors can be calibrated. To show the correctness and the feasibility of this approach, we have examined different variations of our method and evaluated various combinations of tracking sensors. We furthermore integrated this time synchronization method into our UBITRACK Mixed Reality tracking framework to provide facilities for calibration and real-time data alignment.

Augmented environments for the targeting of hepatic lesions during image-guided robotic liver surgery

BACKGROUND Stereotactic navigation technology can enhance guidance during surgery and enable the precise reproduction of planned surgical strategies. Currently, specific systems (such as the CAS-One system) are available for instrument guidance in open liver surgery. This study aims to evaluate the implementation of such a system for the targeting of hepatic tumors during robotic liver surgery. MATERIAL AND METHODS Optical tracking references were attached to one of the robotic instruments and to the robotic endoscopic camera. After instrument and video calibration and patient-to-image registration, a virtual model of the tracked instrument and the available three-dimensional images of the liver were displayed directly within the robotic console, superimposed onto the endoscopic video image. An additional superimposed targeting viewer allowed for the visualization of the target tumor, relative to the tip of the instrument, for an assessment of the distance between the tumor and the tool for the realization of safe resection margins. RESULTS Two cirrhotic patients underwent robotic navigated atypical hepatic resections for hepatocellular carcinoma. The augmented endoscopic view allowed for the definition of an accurate resection margin around the tumor. The overlay of reconstructed three-dimensional models was also used during parenchymal transection for the identification of vascular and biliary structures. Operative times were 240 min in the first case and 300 min in the second. There were no intraoperative complications. CONCLUSIONS The da Vinci Surgical System provided an excellent platform for image-guided liver surgery with a stable optic and instrumentation. Robotic image guidance might improve the surgeon's orientation during the operation and increase accuracy in tumor resection. Further developments of this technological combination are needed to deal with organ deformation during surgery.

Simultaneous 3D object tracking and camera parameter estimation by Bayesian methods and transdimensional MCMC sampling

Multi-camera 3D tracking systems with overlapping cameras represent a powerful mean for scene analysis, as they potentially allow greater robustness than monocular systems and provide useful 3D information about object location and movement. However, their performance relies on accurately calibrated camera networks, which is not a realistic assumption in real surveillance environments. Here, we introduce a multi-camera system for tracking the 3D position of a varying number of objects and simultaneously refin-ing the calibration of the network of overlapping cameras. Therefore, we introduce a Bayesian framework that combines Particle Filtering for tracking with recursive Bayesian estimation methods by means of adapted transdimensional MCMC sampling. Addi-tionally, the system has been designed to work on simple motion detection masks, making it suitable for camera networks with low transmission capabilities. Tests show that our approach allows a successful performance even when starting from clearly inaccurate camera calibrations, which would ruin conventional approaches.

Optical signal processing with electrooptic modulators and dispersion

A review of the main techniques that have been proposed for temporal processing of optical pulses that are the counterpart of the well-known spatial arrangements will be presented. They are translated to the temporal domain via the space-time duality and implemented with electrooptical phase and amplitude modulators and dispersive devices. We will introduce new variations of the conventional approaches and we will focus on their application to optical communications systems

Comparative study of two laparoscopic instrument tracker designs for motion analysis and image-guided surgery: a technical evaluation

Laparoscopic instrument tracking systems are a key element in image-guided interventions, which requires high accuracy to be used in a real surgical scenario. In addition, these systems are a suitable option for objective assessment of laparoscopic technical skills based on instrument motion analysis. This study presents a new approach that improves the accuracy of a previously presented system, which applies an optical pose tracking system to laparoscopic practice. A design enhancement of the artificial markers placed on the laparoscopic instrument as well as an improvement of the calibration process are presented as a means to achieve more accurate results. A technical evaluation has been performed in order to compare the accuracy between the previous design and the new approach. Results show a remarkable improvement in the fluctuation error throughout the measurement platform. Moreover, the accumulated distance error and the inclination error have been improved. The tilt range covered by the system is the same for both approaches, from 90º to 7.5º. The relative position error is better for the new approach mainly at close distances to the camera system

A method to obtain the thermal parameters and the photothermal transduction efficiency in an optical hyperthermia device based on laser irradiation of gold nanoparticles

Optical hyperthermia systems based on the laser irradiation of gold nanorods seem to be a promising tool in the development of therapies against cancer. After a proof of concept in which the authors demonstrated the efficiency of this kind of systems, a modeling process based on an equivalent thermal-electric circuit has been carried out to determine the thermal parameters of the system and an energy balance obtained from the time-dependent heating and cooling temperature curves of the irradiated samples in order to obtain the photothermal transduction efficiency. By knowing this parameter, it is possible to increase the effectiveness of the treatments, thanks to the possibility of predicting the response of the device depending on the working configuration. As an example, the thermal behavior of two different kinds of nanoparticles is compared. The results show that, under identical conditions, the use of PEGylated gold nanorods allows for a more efficient heating compared with bare nanorods, and therefore, it results in a more effective therapy.

Bayesian scene analysis for multi-camera 3D tracking and camera positioning

Los sistemas de seguimiento mono-cámara han demostrado su notable capacidad para el análisis de trajectorias de objectos móviles y para monitorización de escenas de interés; sin embargo, tanto su robustez como sus posibilidades en cuanto a comprensión semántica de la escena están fuertemente limitadas por su naturaleza local y monocular, lo que los hace insuficientes para aplicaciones realistas de videovigilancia. El objetivo de esta tesis es la extensión de las posibilidades de los sistemas de seguimiento de objetos móviles para lograr un mayor grado de robustez y comprensión de la escena. La extensión propuesta se divide en dos direcciones separadas. La primera puede considerarse local, ya que está orientada a la mejora y enriquecimiento de las posiciones estimadas para los objetos móviles observados directamente por las cámaras del sistema; dicha extensión se logra mediante el desarrollo de un sistema multi-cámara de seguimiento 3D, capaz de proporcionar consistentemente las posiciones 3D de múltiples objetos a partir de las observaciones capturadas por un conjunto de sensores calibrados y con campos de visión solapados. La segunda extensión puede considerarse global, dado que su objetivo consiste en proporcionar un contexto global para relacionar las observaciones locales realizadas por una cámara con una escena de mucho mayor tamaño; para ello se propone un sistema automático de localización de cámaras basado en las trayectorias observadas de varios objetos móviles y en un mapa esquemático de la escena global monitorizada. Ambas líneas de investigación se tratan utilizando, como marco común, técnicas de estimación bayesiana: esta elección está justificada por la versatilidad y flexibilidad proporcionada por dicho marco estadístico, que permite la combinación natural de múltiples fuentes de información sobre los parámetros a estimar, así como un tratamiento riguroso de la incertidumbre asociada a las mismas mediante la inclusión de modelos de observación específicamente diseñados. Además, el marco seleccionado abre grandes posibilidades operacionales, puesto que permite la creación de diferentes métodos numéricos adaptados a las necesidades y características específicas de distintos problemas tratados. El sistema de seguimiento 3D con múltiples cámaras propuesto está específicamente diseñado para permitir descripciones esquemáticas de las medidas realizadas individualmente por cada una de las cámaras del sistema: esta elección de diseño, por tanto, no asume ningún algoritmo específico de detección o seguimiento 2D en ninguno de los sensores de la red, y hace que el sistema propuesto sea aplicable a redes reales de vigilancia con capacidades limitadas tanto en términos de procesamiento como de transmision. La combinación robusta de las observaciones capturadas individualmente por las cámaras, ruidosas, incompletas y probablemente contaminadas por falsas detecciones, se basa en un metodo de asociación bayesiana basado en geometría y color: los resultados de dicha asociación permiten el seguimiento 3D de los objetos de la escena mediante el uso de un filtro de partículas. El sistema de fusión de observaciones propuesto tiene, como principales características, una gran precisión en términos de localización 3D de objetos, y una destacable capacidad de recuperación tras eventuales errores debidos a un número insuficiente de datos de entrada. El sistema automático de localización de cámaras se basa en la observación de múltiples objetos móviles y un mapa esquemático de las áreas transitables del entorno monitorizado para inferir la posición absoluta de dicho sensor. Para este propósito, se propone un novedoso marco bayesiano que combina modelos dinámicos inducidos por el mapa en los objetos móviles presentes en la escena con las trayectorias observadas por la cámara, lo que representa un enfoque nunca utilizado en la literatura existente. El sistema de localización se divide en dos sub-tareas diferenciadas, debido a que cada una de estas tareas requiere del diseño de algoritmos específicos de muestreo para explotar en profundidad las características del marco desarrollado: por un lado, análisis de la ambigüedad del caso específicamente tratado y estimación aproximada de la localización de la cámara, y por otro, refinado de la localización de la cámara. El sistema completo, diseñado y probado para el caso específico de localización de cámaras en entornos de tráfico urbano, podría tener aplicación también en otros entornos y sensores de diferentes modalidades tras ciertas adaptaciones. ABSTRACT Mono-camera tracking systems have proved their capabilities for moving object trajectory analysis and scene monitoring, but their robustness and semantic possibilities are strongly limited by their local and monocular nature and are often insufficient for realistic surveillance applications. This thesis is aimed at extending the possibilities of moving object tracking systems to a higher level of scene understanding. The proposed extension comprises two separate directions. The first one is local, since is aimed at enriching the inferred positions of the moving objects within the area of the monitored scene directly covered by the cameras of the system; this task is achieved through the development of a multi-camera system for robust 3D tracking, able to provide 3D tracking information of multiple simultaneous moving objects from the observations reported by a set of calibrated cameras with semi-overlapping fields of view. The second extension is global, as is aimed at providing local observations performed within the field of view of one camera with a global context relating them to a much larger scene; to this end, an automatic camera positioning system relying only on observed object trajectories and a scene map is designed. The two lines of research in this thesis are addressed using Bayesian estimation as a general unifying framework. Its suitability for these two applications is justified by the flexibility and versatility of that stochastic framework, which allows the combination of multiple sources of information about the parameters to estimate in a natural and elegant way, addressing at the same time the uncertainty associated to those sources through the inclusion of models designed to this end. In addition, it opens multiple possibilities for the creation of different numerical methods for achieving satisfactory and efficient practical solutions to each addressed application. The proposed multi-camera 3D tracking method is specifically designed to work on schematic descriptions of the observations performed by each camera of the system: this choice allows the use of unspecific off-the-shelf 2D detection and/or tracking subsystems running independently at each sensor, and makes the proposal suitable for real surveillance networks with moderate computational and transmission capabilities. The robust combination of such noisy, incomplete and possibly unreliable schematic descriptors relies on a Bayesian association method, based on geometry and color, whose results allow the tracking of the targets in the scene with a particle filter. The main features exhibited by the proposal are, first, a remarkable accuracy in terms of target 3D positioning, and second, a great recovery ability after tracking losses due to insufficient input data. The proposed system for visual-based camera self-positioning uses the observations of moving objects and a schematic map of the passable areas of the environment to infer the absolute sensor position. To this end, a new Bayesian framework combining trajectory observations and map-induced dynamic models for moving objects is designed, which represents an approach to camera positioning never addressed before in the literature. This task is divided into two different sub-tasks, setting ambiguity analysis and approximate position estimation, on the one hand, and position refining, on the other, since they require the design of specific sampling algorithms to correctly exploit the discriminative features of the developed framework. This system, designed for camera positioning and demonstrated in urban traffic environments, can also be applied to different environments and sensors of other modalities after certain required adaptations.

Bayesian scene analysis for multi-camera 3D tracking and camera positioning

Los sistemas de seguimiento mono-cámara han demostrado su notable capacidad para el análisis de trajectorias de objectos móviles y para monitorización de escenas de interés; sin embargo, tanto su robustez como sus posibilidades en cuanto a comprensión semántica de la escena están fuertemente limitadas por su naturaleza local y monocular, lo que los hace insuficientes para aplicaciones realistas de videovigilancia. El objetivo de esta tesis es la extensión de las posibilidades de los sistemas de seguimiento de objetos móviles para lograr un mayor grado de robustez y comprensión de la escena. La extensión propuesta se divide en dos direcciones separadas. La primera puede considerarse local, ya que está orientada a la mejora y enriquecimiento de las posiciones estimadas para los objetos móviles observados directamente por las cámaras del sistema; dicha extensión se logra mediante el desarrollo de un sistema multi-cámara de seguimiento 3D, capaz de proporcionar consistentemente las posiciones 3D de múltiples objetos a partir de las observaciones capturadas por un conjunto de sensores calibrados y con campos de visión solapados. La segunda extensión puede considerarse global, dado que su objetivo consiste en proporcionar un contexto global para relacionar las observaciones locales realizadas por una cámara con una escena de mucho mayor tamaño; para ello se propone un sistema automático de localización de cámaras basado en las trayectorias observadas de varios objetos móviles y en un mapa esquemático de la escena global monitorizada. Ambas líneas de investigación se tratan utilizando, como marco común, técnicas de estimación bayesiana: esta elección está justificada por la versatilidad y flexibilidad proporcionada por dicho marco estadístico, que permite la combinación natural de múltiples fuentes de información sobre los parámetros a estimar, así como un tratamiento riguroso de la incertidumbre asociada a las mismas mediante la inclusión de modelos de observación específicamente diseñados. Además, el marco seleccionado abre grandes posibilidades operacionales, puesto que permite la creación de diferentes métodos numéricos adaptados a las necesidades y características específicas de distintos problemas tratados. El sistema de seguimiento 3D con múltiples cámaras propuesto está específicamente diseñado para permitir descripciones esquemáticas de las medidas realizadas individualmente por cada una de las cámaras del sistema: esta elección de diseño, por tanto, no asume ningún algoritmo específico de detección o seguimiento 2D en ninguno de los sensores de la red, y hace que el sistema propuesto sea aplicable a redes reales de vigilancia con capacidades limitadas tanto en términos de procesamiento como de transmision. La combinación robusta de las observaciones capturadas individualmente por las cámaras, ruidosas, incompletas y probablemente contaminadas por falsas detecciones, se basa en un metodo de asociación bayesiana basado en geometría y color: los resultados de dicha asociación permiten el seguimiento 3D de los objetos de la escena mediante el uso de un filtro de partículas. El sistema de fusión de observaciones propuesto tiene, como principales características, una gran precisión en términos de localización 3D de objetos, y una destacable capacidad de recuperación tras eventuales errores debidos a un número insuficiente de datos de entrada. El sistema automático de localización de cámaras se basa en la observación de múltiples objetos móviles y un mapa esquemático de las áreas transitables del entorno monitorizado para inferir la posición absoluta de dicho sensor. Para este propósito, se propone un novedoso marco bayesiano que combina modelos dinámicos inducidos por el mapa en los objetos móviles presentes en la escena con las trayectorias observadas por la cámara, lo que representa un enfoque nunca utilizado en la literatura existente. El sistema de localización se divide en dos sub-tareas diferenciadas, debido a que cada una de estas tareas requiere del diseño de algoritmos específicos de muestreo para explotar en profundidad las características del marco desarrollado: por un lado, análisis de la ambigüedad del caso específicamente tratado y estimación aproximada de la localización de la cámara, y por otro, refinado de la localización de la cámara. El sistema completo, diseñado y probado para el caso específico de localización de cámaras en entornos de tráfico urbano, podría tener aplicación también en otros entornos y sensores de diferentes modalidades tras ciertas adaptaciones. ABSTRACT Mono-camera tracking systems have proved their capabilities for moving object trajectory analysis and scene monitoring, but their robustness and semantic possibilities are strongly limited by their local and monocular nature and are often insufficient for realistic surveillance applications. This thesis is aimed at extending the possibilities of moving object tracking systems to a higher level of scene understanding. The proposed extension comprises two separate directions. The first one is local, since is aimed at enriching the inferred positions of the moving objects within the area of the monitored scene directly covered by the cameras of the system; this task is achieved through the development of a multi-camera system for robust 3D tracking, able to provide 3D tracking information of multiple simultaneous moving objects from the observations reported by a set of calibrated cameras with semi-overlapping fields of view. The second extension is global, as is aimed at providing local observations performed within the field of view of one camera with a global context relating them to a much larger scene; to this end, an automatic camera positioning system relying only on observed object trajectories and a scene map is designed. The two lines of research in this thesis are addressed using Bayesian estimation as a general unifying framework. Its suitability for these two applications is justified by the flexibility and versatility of that stochastic framework, which allows the combination of multiple sources of information about the parameters to estimate in a natural and elegant way, addressing at the same time the uncertainty associated to those sources through the inclusion of models designed to this end. In addition, it opens multiple possibilities for the creation of different numerical methods for achieving satisfactory and efficient practical solutions to each addressed application. The proposed multi-camera 3D tracking method is specifically designed to work on schematic descriptions of the observations performed by each camera of the system: this choice allows the use of unspecific off-the-shelf 2D detection and/or tracking subsystems running independently at each sensor, and makes the proposal suitable for real surveillance networks with moderate computational and transmission capabilities. The robust combination of such noisy, incomplete and possibly unreliable schematic descriptors relies on a Bayesian association method, based on geometry and color, whose results allow the tracking of the targets in the scene with a particle filter. The main features exhibited by the proposal are, first, a remarkable accuracy in terms of target 3D positioning, and second, a great recovery ability after tracking losses due to insufficient input data. The proposed system for visual-based camera self-positioning uses the observations of moving objects and a schematic map of the passable areas of the environment to infer the absolute sensor position. To this end, a new Bayesian framework combining trajectory observations and map-induced dynamic models for moving objects is designed, which represents an approach to camera positioning never addressed before in the literature. This task is divided into two different sub-tasks, setting ambiguity analysis and approximate position estimation, on the one hand, and position refining, on the other, since they require the design of specific sampling algorithms to correctly exploit the discriminative features of the developed framework. This system, designed for camera positioning and demonstrated in urban traffic environments, can also be applied to different environments and sensors of other modalities after certain required adaptations.

Exploración y evaluación de mecanismos para la captura de la posición y postura de personas en entornos reales

El presente trabajo consiste en el estudio de la viabilidad en el uso de tres posibles opciones orientadas a la captura de la posición y la postura de personas en entornos reales, así como el diseño e implementación de un prototipo de captura en cada uno de ellos. También se incluye una comparativa con el fin de destacar los pros y los contras de cada solución. Una de las alternativas para llevarlo a cabo consiste en un sistema de tracking óptico por infrarrojos de alta calidad y precisión, como es Optitrack; la segunda se basa en una solución de bajo coste como es el periférico Kinect de Microsoft y la tercera consiste en la combinación de ambos dispositivos para encontrar un equilibrio entre precisión y economía, tomando los puntos fuertes de cada uno para contrarrestar sus debilidades. Uno de los puntos importantes del trabajo es que el uso de los prototipos de captura está orientado a entornos de trabajo reales (en concreto en la captura de los movimientos del personal que trabaja en un quirófano), así que han sido necesarias pruebas para minimizar el efecto de las fuentes de luz en los sistemas de infrarrojos, el estudio de los dispositivos para determinar el número de personas que son capaces de capturar a la vez sin que esto afecte a su rendimiento y el nivel de invasión de los dispositivos en los trabajadores (marcadores para el tracking), además de los mecanismos apropiados para minimizar el impacto de las oclusiones utilizando métodos de interpolación y ayudándose del conocimiento del contexto, las restricciones de movimiento del cuerpo humano y la evolución en el tiempo. Se han desarrollado conocimientos en el funcionamiento y configuración dispositivos como el sistema de captura Optitrack de Natural Point y el sistema de detección de movimiento Kinect desarrollado por Microsoft. También se ha aprendido el funcionamiento del entorno de desarrollo y motor de videojuegos multiplataforma homónimos Unity y del lenguaje de programación C# que utiliza dicho entorno para sus scripts de control, así como los protocolos de comunicación entre los distintos sistemas que componen los prototipos como son VRPN y NatNet.---ABSTRACT---This project is about a viability study in the use of three possible options, oriented towards the capture of the position and view of people in a real environment, as well as the design and implementation of a capturing prototype in each of them. A comparative study is also included, in order to emphasise the pros and cons of each solution. One of the alternatives consists of an optical tracking system via high quality and precision infrareds, like Optitrack; the second is based on a low cost solution, such as Microsoft’s Kinect peripheral, and the third consists on a combination of both devices to find a balance between precision and price, taking the strong points of each of the mechanisms to make up for the weaknesses. One of the important parts of this project is that the use of the capturing prototypes is directed towards real life work situations (specifically towards the capturing of the movements of surgery personnel), so various tests have been necessary in order to minimize the effect of light sources in infrared systems, the study of the devices to determine the number of people that they are capable of capturing simultaneously without affecting their performance and the invasion level of the devices towards the workers (tracking markers), as well as the mechanisms adopted to minimize the impact of the occlusions using interpolation methods and with help of the knowledge of the surroundings, the human movement restrictions and the passing of time. Knowledge has been developed on the functioning and configuration of the devices such as Natural Point’s Optitrak capturing system, and the Kinect movement detection system developed by Microsoft. We have also learned about the operating of the development and incentive environment of multiplatform videogames of namesake Unity and of C# programming language, which uses said environment for its control scripts, as well as communication protocols between the different systems that make up prototypes like VRPN and NatNet.

Dispersion aspects of periodically amplified soliton transmission systems

This thesis presents improvements to optical transmission systems through the use of optical solitons as a digital transmission format, both theoretically and experimentally. An introduction to the main concepts and impairments of optical fibre on pulse transmission is included before introducing the concept of solitons in optically amplified communications and the problems of soliton system design. The theoretical work studies two fibre dispersion profiling schemes and a soliton launch improvement. The first provides superior pulse transmission by optimally tailoring the fibre dispersion to better follow the power, and hence nonlinearity, decay and thus allow soliton transmission for longer amplifier spacings and shorter pulse widths than normally possible. The second profiling scheme examines the use of dispersion compensating fibre in the context of soliton transmission over existing, standard fibre systems. The limits for solitons in uncompensated standard fibre are assessed, before the potential benefits of dispersion compensating fibre included as part of each amplifier are shown. The third theoretical investigation provides a simple improvement to the propagation of solitons in a highly perturbed system. By introducing a section of fibre of the correct length prior to the first system amplifier span, the soliton shape can be better coupled into the system thus providing an improved "average soliton" propagation model. The experimental work covers two areas. An important issue for soliton systems is pulse sources. Three potential lasers are studied, two ring laser configurations and one semiconductor device with external pulse shaping. The second area studies soliton transmission using a recalculating loop, reviewing the advantages and draw-backs of such an experiment in system testing and design. One particular example of employing the recirculating loop is also examined, using a novel method of pulse shape stabilisation over long distances with low jitter. The future for nonlinear optical communications is considered with the thesis conclusions.

Nonlinear pulse shaping in fibres for pulse generation and optical processing

The development of new all-optical technologies for data processing and signal manipulation is a field of growing importance with a strong potential for numerous applications in diverse areas of modern science. Nonlinear phenomena occurring in optical fibres have many attractive features and great, but not yet fully explored, potential in signal processing. Here, we review recent progress on the use of fibre nonlinearities for the generation and shaping of optical pulses and on the applications of advanced pulse shapes in all-optical signal processing. Amongst other topics, we will discuss ultrahigh repetition rate pulse sources, the generation of parabolic shaped pulses in active and passive fibres, the generation of pulses with triangular temporal profiles, and coherent supercontinuum sources. The signal processing applications will span optical regeneration, linear distortion compensation, optical decision at the receiver in optical communication systems, spectral and temporal signal doubling, and frequency conversion. © Copyright 2012 Sonia Boscolo and Christophe Finot.

Nonlinearly generated advanced pulse waveforms for optical signal processing

Nonlinear phenomena occurring in optical fibres have many attractive features and great, but not yet fully explored potential in signal processing. Here, we review recent progress on the use of fibre nonlinearities for the generation and shaping of optical pulses, and on the applications of advanced pulse waveforms in all-optical signal processing. Among other topics, we will discuss ultrahigh repetition-rate pulse sources, the generation of parabolic-shaped pulses in active and passive fibres, the generation of pulses with triangular temporal profiles, and coherent supercontinuum sources. The signal processing applications will span optical regeneration, linear distortion compensation, optical decision at the receiver in optical communication systems, spectral and temporal signal doubling, and frequency conversion. © 2012 IEEE.