Advanced data communication techniques for sub-sea applications

This thesis details research carried out in the through-water data communication field. An overview of the phenomena that prohibit acoustic communication in long-range shallow-water channels is constructed. Background research found that robust communications has not been achieved using single receiver reception in this environment. This work investigates the modulation technique itself and aims to improve on existing schemes (that have been applied to this environment). This is achieved with innovative techniques, based on multiple-frequency-shift-keying (MFSK) and space-frequency-shift-keying (SFSK). A number of industrial specified restrictions are placed on this work, including bandwidth restriction. Novel ways of intrinsically transmitting synchronisation information are therefore implemented. The development of appropriate systems is covered with general and platform specific implementation strategies being covered. A single modulation scheme (the three-chip four-frequency-shift-keying, 3C4FSK, scheme) has been put forward for consideration in any future research. Practical lab-based tests and the mathematical analysis is detailed. Conclusions recommend further funding of long-range shallow sea-water trails of the 3C4FSK scheme and for the industrial scope of this work to allow investigation into multiple receiver systems that allow spatial processing of the signal as these schemes have been shown lately to have potential in long-range channels

Adaptive optics in high-contrast imaging

The development of adaptive optics (AO) played a major role in modern astronomy over the last three decades. By compensating for the atmospheric turbulence, these systems enable to reach the diffraction limit on large telescopes. In this review, we will focus on high contrast applications of adaptive optics, namely, imaging the close vicinity of bright stellar objects and revealing regions otherwise hidden within the turbulent halo of the atmosphere to look for objects with a contrast ratio lower than 10^-4 with respect to the central star. Such high-contrast AO-corrected observations have led to fundamental results in our current understanding of planetary formation and evolution as well as stellar evolution. AO systems equipped three generations of instruments, from the first pioneering experiments in the nineties, to the first wave of instruments on 8m-class telescopes in the years 2000, and finally to the extreme AO systems that have recently started operations. Along with high-contrast techniques, AO enables to reveal the circumstellar environment: massive protoplanetary disks featuring spiral arms, gaps or other asymmetries hinting at on-going planet formation, young giant planets shining in thermal emission, or tenuous debris disks and micron-sized dust leftover from collisions in massive asteroid-belt analogs. After introducing the science case and technical requirements, we will review the architecture of standard and extreme AO systems, before presenting a few selected science highlights obtained with recent AO instruments.Comment: 24 pages, 14 figure

Spectrum Sensing and Multiple Access Schemes for Cognitive Radio Networks

Increasing demands on the radio spectrum have driven wireless engineers to rethink approaches by which devices should access this natural, and arguably scarce, re- source. Cognitive Radio (CR) has arisen as a new wireless communication paradigm aimed at solving the spectrum underutilization problem. In this thesis, we explore a novel variety of techniques aimed at spectrum sensing which serves as a fundamental mechanism to find unused portions of the electromagnetic spectrum. We present several spectrum sensing methods based on multiple antennas and evaluate their receiving operating characteristics. We study a cyclostationary feature detection technique by means of multiple cyclic frequencies. We make use of a spec- trum sensing method called sequential analysis that allows us to significantly decrease the time needed for detecting the presence of a licensed user. We extend this scheme allowing each CR user to perform the sequential analysis algorithm and send their local decision to a fusion centre. This enables for an average faster and more accurate detection. We present an original technique for accounting for spatial and temporal cor- relation influence in spectrum sensing. This reflects on the impact of the scattering environment on detection methods using multiple antennas. The approach is based on the scattering geometry and resulting correlation properties of the received signal at each CR device. Finally, the problem of spectrum sharing for CR networks is addressed in or- der to take advantage of the detected unused frequency bands. We proposed a new multiple access scheme based on the Game Theory. We examine the scenario where a random number of CR users (considered as players) compete to access the radio spec- trum. We calculate the optimal probability of transmission which maximizes the CR throughput along with the minimum harm caused to the licensed users’ performance

Depolarized Holography with Polarization-multiplexing Metasurface

The evolution of computer-generated holography (CGH) algorithms has prompted significant improvements in the performances of holographic displays. Nonetheless, they start to encounter a limited degree of freedom in CGH optimization and physical constraints stemming from the coherent nature of holograms. To surpass the physical limitations, we consider polarization as a new degree of freedom by utilizing a novel optical platform called metasurface. Polarization-multiplexing metasurfaces enable incoherent-like behavior in holographic displays due to the mutual incoherence of orthogonal polarization states. We leverage this unique characteristic of a metasurface by integrating it into a holographic display and exploiting polarization diversity to bring an additional degree of freedom for CGH algorithms. To minimize the speckle noise while maximizing the image quality, we devise a fully differentiable optimization pipeline by taking into account the metasurface proxy model, thereby jointly optimizing spatial light modulator phase patterns and geometric parameters of metasurface nanostructures. We evaluate the metasurface-enabled depolarized holography through simulations and experiments, demonstrating its ability to reduce speckle noise and enhance image quality.Comment: 15 pages, 13 figures, to be published in SIGGRAPH Asia 202

MICROPHONE ARRAY OPTIMIZATION IN IMMERSIVE ENVIRONMENTS

The complex relationship between array gain patterns and microphone distributions limits the application of traditional optimization algorithms on irregular arrays, which show enhanced beamforming performance for human speech capture in immersive environments. This work analyzes the relationship between irregular microphone geometries and spatial filtering performance with statistical methods. Novel geometry descriptors are developed to capture the properties of irregular microphone distributions showing their impact on array performance. General guidelines and optimization methods for regular and irregular array design are proposed in immersive (near-field) environments to obtain superior beamforming ability for speech applications. Optimization times are greatly reduced through the objective function rules using performance-based geometric descriptions of microphone distributions that circumvent direct array gain computations over the space of interest. In addition, probabilistic descriptions of acoustic scenes are introduced to incorporate various levels of prior knowledge for the source distribution. To verify the effectiveness of the proposed optimization methods, simulated gain patterns and real SNR results of the optimized arrays are compared to corresponding traditional regular arrays and arrays obtained from direct exhaustive searching methods. Results show large SNR enhancements for the optimized arrays over arbitrary randomly generated arrays and regular arrays, especially at low microphone densities. The rapid convergence and acceptable processing times observed during the experiments establish the feasibility of proposed optimization methods for array geometry design in immersive environments where rapid deployment is required with limited knowledge of the acoustic scene, such as in mobile platforms and audio surveillance applications

Innovative Techniques for the Retrieval of Earth’s Surface and Atmosphere Geophysical Parameters: Spaceborne Infrared/Microwave Combined Analyses

With the advent of the first satellites for Earth Observation: Landsat-1 in July 1972 and ERS-1 in May 1991, the discipline of environmental remote sensing has become, over time, increasingly fundamental for the study of phenomena characterizing the planet Earth. The goal of environmental remote sensing is to perform detailed analyses and to monitor the temporal evolution of different physical phenomena, exploiting the mechanisms of interaction between the objects that are present in an observed scene and the electromagnetic radiation detected by sensors, placed at a distance from the scene, operating at different frequencies. The analyzed physical phenomena are those related to climate change, weather forecasts, global ocean circulation, greenhouse gas profiling, earthquakes, volcanic eruptions, soil subsidence, and the effects of rapid urbanization processes. Generally, remote sensing sensors are of two primary types: active and passive. Active sensors use their own source of electromagnetic radiation to illuminate and analyze an area of interest. An active sensor emits radiation in the direction of the area to be investigated and then detects and measures the radiation that is backscattered from the objects contained in that area. Passive sensors, on the other hand, detect natural electromagnetic radiation (e.g., from the Sun in the visible band and the Earth in the infrared and microwave bands) emitted or reflected by the object contained in the observed scene. The scientific community has dedicated many resources to developing techniques to estimate, study and analyze Earth’s geophysical parameters. These techniques differ for active and passive sensors because they depend strictly on the type of the measured physical quantity. In my P.h.D. work, inversion techniques for estimating Earth’s surface and atmosphere geophysical parameters will be addressed, emphasizing methods based on machine learning (ML). In particular, the study of cloud microphysics and the characterization of Earth’s surface changes phenomenon are the critical points of this work