Smart antennas for strategic environment

The objective of this Thesis consists in presenting in a concise and effective way the results achieved during researches and studies on satellite systems interference sources, advanced antenna arrays for satellite systems to mitigate the increasing anti-interference needs and on an innovative way to generates inhomogeneous wave in lossless media for contributing to the design of a novel type of antenna for deep penetrating lossy media

Volumetric Phased Arrays for Satellite Communications

The high amount of scientific and communications data produced by low earth orbiting satellites necessitates economical methods of communication with these satellites. A volumetric phased array for demonstrating horizon-to-horizon electronic tracking of the NASA satellite EO-1 was developed and demonstrated. As a part of this research, methods of optimizing the elemental antenna as well as the antenna on-board the satellite were investigated. Using these optimized antennas removes the variations in received signal strength that are due to the angularly dependent propagation loss exhibited by the communications link. An exhaustive study using genetic algorithms characterized two antenna architectures, and included optimizations for radiation pattern, bandwidth, impedance, and polarization. Eleven antennas were constructed and their measured characteristics were compared to those of the simulated antennas. Additional studies were conducted regarding the optimization of aperiodic arrays. A pattern-space representation of volumetric arrays was developed and used with a novel tracking algorithm for these arrays. This algorithm allows high-resolution direction finding using a small number of antennas while mitigating aliasing ambiguities. Finally, a method of efficiently applying multiple beam synthesis using the Fast Fourier Transform to aperiodic arrays was developed. This algorithm enables the operation of phased arrays combining the benefits of aperiodic element position with the efficiency of FFT multiple beam synthesis. Results of this research are presented along with the characteristics of the volumetric array used to track EO-1. Experimental data and the interpretations of that data are presented, and possible areas of future research are discussed.Ph.D.Committee Chair: Steffes, Paul; Committee Member: Durgin, Gregory; Committee Member: Peterson, Andrew; Committee Member: Roper, Robert; Committee Member: Williams, Dougla

Abstracts on Radio Direction Finding (1899 - 1995)

The files on this record represent the various databases that originally composed the CD-ROM issue of "Abstracts on Radio Direction Finding" database, which is now part of the Dudley Knox Library's Abstracts and Selected Full Text Documents on Radio Direction Finding (1899 - 1995) Collection. (See Calhoun record https://calhoun.nps.edu/handle/10945/57364 for further information on this collection and the bibliography). Due to issues of technological obsolescence preventing current and future audiences from accessing the bibliography, DKL exported and converted into the three files on this record the various databases contained in the CD-ROM. The contents of these files are: 1) RDFA_CompleteBibliography_xls.zip [RDFA_CompleteBibliography.xls: Metadata for the complete bibliography, in Excel 97-2003 Workbook format; RDFA_Glossary.xls: Glossary of terms, in Excel 97-2003 Workbookformat; RDFA_Biographies.xls: Biographies of leading figures, in Excel 97-2003 Workbook format]; 2) RDFA_CompleteBibliography_csv.zip [RDFA_CompleteBibliography.TXT: Metadata for the complete bibliography, in CSV format; RDFA_Glossary.TXT: Glossary of terms, in CSV format; RDFA_Biographies.TXT: Biographies of leading figures, in CSV format]; 3) RDFA_CompleteBibliography.pdf: A human readable display of the bibliographic data, as a means of double-checking any possible deviations due to conversion

Performance Enhancement of Radiation and Scattering Properties of Circularly Polarized Antennas Using Frequency Selective Surface

At millimetre-wave (MMW) frequencies, losses associated with wireless link and system are critical issues that need to be overcome in designing high-performance wireless systems. To compensate the overall loss in a wireless communication system, a high-gain antenna is required. Circularly polarized (CP) antennas are among preferred choices to design because they offer many advantages due to their good resistance to polarization mismatch, mitigation of multipath effects, and some phasing issues and immunity to Faraday rotation. On the other hand, frequency selective surface (FSS) technology is recently employed to enhance the performance of radiation and scattering properties of antennas used in different sectors such as aerospace, medical, and microwave industry. Therefore, it is appropriate and attractive to propose the use of FSS technology to design practical and efficient CP antennas. CP Fabry-Perot cavity (FPC) antennas based on FSS are investigated in this thesis to fulfil the growing demand for broadband high-gain antennas with low radar cross section (RCS). The thesis investigates both characteristic improvement of CP antennas and RCS reduction issues employing FSS structures. Initially, a high gain CP dielectric resonator (DR) antenna is proposed. Using an FSS superstrate layer, a gain enhancement of 8.5 dB is achieved. A detailed theoretical analysis along with different models are presented and used to optimize the superstrate size and the air gap height between the antenna and superstrate layer. The second research theme focusses on developing an effective approach for mitigating the near-field coupling between four-port CP antennas in a Multiple-Input, Multiple-Output (MIMO) system. This is obtained by incorporating a two-layer transmission-type FSS superstrate based on planar crossed-dipole metal strips. Another technique for suppressing the spatially coupling between DR antennas using a new FSS polarization-rotator wall is studied as well. The coupling reduction is achieved by embedding an FSS wall between two DRAs, which are placed in the H-plane. Utilizing this FSS wall, the TE modes of the antennas become orthogonal, which reduces the spatially coupling between the two DRAs. The third research theme of this thesis is to enhance the purity and bandwidth of CP with the least amount of insertion loss by the use of an LP-to-CP-polarizer which is based on multilayer FSS slab. This polarizer is approximately robust under oblique illuminations. To have a high-gain CP antenna, an 8-element LP array antenna with Chebyshev tapered distribution is designed and integrated with the polarizer. Eventually, in order to enhance the scattering property, the fourth research theme investigates on RCS reduction by the use of two different approaches which are based on FSS. Initially, a wideband FSS metasurface for RCS reduction based on a polarization conversion is proposed. To distribute the scattered EM waves and suppress the maximum bistatic RCS of the metasurface over a broad band of incident angles at both polarizations, the elements are arranged using the binary coding matrix achieved by group search optimization (GSO) algorithm. The reflective two-layer metasurface is designed in such a way to generate reflection phase difference of 180° between two elements “0” and “1” on a broad frequency band. A theoretical analysis is performed on the ratio of the “0” and “1” elements using Least Square Error (LSE) method to find the best ratio value. As the second activity of this research theme, wideband CP antenna with low RCS and high gain properties is presented. The proposed antenna is based on a combination of the FPC and sequential feeding technique

Particle Swarm Optimization

Particle swarm optimization (PSO) is a population based stochastic optimization technique influenced by the social behavior of bird flocking or fish schooling.PSO shares many similarities with evolutionary computation techniques such as Genetic Algorithms (GA). The system is initialized with a population of random solutions and searches for optima by updating generations. However, unlike GA, PSO has no evolution operators such as crossover and mutation. In PSO, the potential solutions, called particles, fly through the problem space by following the current optimum particles. This book represents the contributions of the top researchers in this field and will serve as a valuable tool for professionals in this interdisciplinary field

Parametric analysis of microwave and laser systems for communication and tracking. Volume 3 - Reference data for advanced space communication and tracking systems

Reference data for advanced microwave and laser communication and tracking systems - Vol.

Advancing Gesture Recognition with Millimeter Wave Radar

Wireless sensing has attracted significant interest over the years, and with the dawn of emerging technologies, it has become more integrated into our daily lives. Among the various wireless communication platforms, WiFi has gained widespread deployment in indoor settings. Consequently, the utilization of ubiquitous WiFi signals for detecting indoor human activities has garnered considerable attention in the past decade. However, more recently, mmWave Radar-based sensing has emerged as a promising alternative, offering advantages such as enhanced sensitivity to motion and increased bandwidth. This thesis introduces innovative approaches to enhance contactless gesture recognition by leveraging emerging low-cost millimeter wave radar technology. It makes three key contributions. Firstly, a cross-modality training technique is proposed, using mmWave radar as a supplementary aid for training WiFi-based deep learning models. The proposed model enables precise gesture detection based solely on WiFi signals, significantly improving WiFi-based recognition. Secondly, a novel beamforming-based gesture detection system is presented, utilizing commodity mmWave radars for accurate detection in low signal-to-noise scenarios. By steering multiple beams around the gesture performer, independent views of the gesture are captured. A selfattention based deep neural network intelligently fuses information from these beams, surpassing single-beam accuracy. The model incorporates a unique data augmentation algorithm accounting for Doppler shift and multipath effects, enhancing generalization. Notably, the proposed method achieves superior gesture classification performance, outperforming state-of-the-art approaches by 31-43% with only two beams. Thirdly, the research explores receiver antenna diversity in mmWave radars to further improve gesture recognition accuracy by deep learning techniques to combine data from multiple receiver antennas, leveraging inherent diversity for enhanced detection. Extensive experimentation and evaluation demonstrate substantial advancements in contactless gesture recognition using low-cost mmWave radar technology

Digital-At-Every-Element Radar Resource Allocation for Multi-Target Tracking

A sensor's performance is constrained by the amount of resources at its disposal and the utilization of those resources. A radar system, for example, has a limited amount of transmit power-aperture per unit time to track a multitude of targets. A typical approach when tracking multiple dynamic targets is to time interleave the update intervals until all the radar tasks are performed. The advent of more agile sensors, such as digital-at-every-element apertures, opens the possibility for dynamic sensor resource allocation strategies to achieve better tracking performance in target-dense, resource-constrained scenarios. With proper research into aperture allocation, such as the analysis provided in this dissertation, an all-digital radar can intelligently exploit the degrees of freedom offered by all-digital radars to increase tracking performance. In this dissertation, we investigate adaptive aperture allocation for tracking a large number of targets. The strategies are first introduced with a parallel, linear channel model, then increased in realism with a non-linear measurement model, and finally applied to a full tracking system. We derive various strategies for allocating power and aperture, and compare their performance based on tracking related metrics. Finally, we investigate the relationship between the aperture allocation strategies and the target locations for multiple scenarios designed to represent the environment for a radar tracking system. This research provides groundbreaking strategies for optimal radar aperture allocation using the digital-at-every-element architectures to reduce the overall system uncertainty and decrease the uncertainty on a per-target basis. Integrating aperture allocation with the management of other degrees of freedom will increase multi-target tracking performance well beyond the current state of the art

Design patterns and software techniques for large-scale, open and reproducible data reduction

The preparation for the construction of the Square Kilometre Array, and the introduction of its operational precursors, such as LOFAR and MeerKAT, mark the beginning of an exciting era for astronomy. Impressive new data containing valuable science just waiting for discovery is already being generated, and these devices will produce far more data than has ever been collected before. However, with every new data instrument, the data rates grow to unprecedented quantities of data, requiring novel new data-processing tools. In addition, creating science grade data from the raw data still requires significant expert knowledge for processing this data. The software used is often developed by a scientist who lacks proper training in software development skills, resulting in the software not progressing beyond a prototype stage in quality. In the first chapter, we explore various organisational and technical approaches to address these issues by providing a historical overview of the development of radioastronomy pipelines since the inception of the field in the 1940s. In that, the steps required to create a radio image are investigated. We used the lessons-learned to identify patterns in the challenges experienced, and the solutions created to address these over the years. The second chapter describes the mathematical foundations that are essential for radio imaging. In the third chapter, we discuss the production of the KERN Linux distribution, which is a set of software packages containing most radio astronomy software currently in use. Considerable effort was put into making sure that the contained software installs appropriately, all items next to one other on the same system. Where required and possible, bugs and portability fixes were solved and reported with the upstream maintainers. The KERN project also has a website, and issue tracker, where users can report bugs and maintainers can coordinate the packaging effort and new releases. The software packages can be used inside Docker and Singularity containers, enabling the installation of these packages on a wide variety of platforms. In the fourth and fifth chapters, we discuss methods and frameworks for combining the available data reduction tools into recomposable pipelines and introduce the Kliko specification and software. This framework was created to enable end-user astronomers to chain and containerise operations of software in KERN packages. Next, we discuss the Common Workflow Language (CommonWL), a similar but more advanced and mature pipeline framework invented by bio-informatics scientists. CommonWL is supported by a wide range of tools already; among other schedulers, visualisers and editors. Consequently, when a pipeline is made with CommonWL, it can be deployed and manipulated with a wide range of tools. In the final chapter, we attempt something unconventional, applying a generative adversarial network based on deep learning techniques to perform the task of sky brightness reconstruction. Since deep learning methods often require a large number of training samples, we constructed a CommonWL simulation pipeline for creating dirty images and corresponding sky models. This simulated dataset has been made publicly available as the ASTRODECONV2019 dataset. It is shown that this method is useful to perform the restoration and matches the performance of a single clean cycle. In addition, we incorporated domain knowledge by adding the point spread function to the network and by utilising a custom loss function during training. Although it was not possible to improve the cleaning performance of commonly used existing tools, the computational time performance of the approach looks very promising. We suggest that a smaller scope should be the starting point for further studies and optimising of the training of the neural network could produce the desired results