Matching Items (5)
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- All Subjects: Radar
- Creators: Kosut, Oliver
- Creators: Aberle, James
- Resource Type: Text
Description
RF convergence of radar and communications users is rapidly becoming an issue for a multitude of stakeholders. To hedge against growing spectral congestion, research into cooperative radar and communications systems has been identified as a critical necessity for the United States and other countries. Further, the joint sensing-communicating paradigm appears imminent in several technological domains. In the pursuit of co-designing radar and communications systems that work cooperatively and benefit from each other's existence, joint radar-communications metrics are defined and bounded as a measure of performance. Estimation rate is introduced, a novel measure of radar estimation information as a function of time. Complementary to communications data rate, the two systems can now be compared on the same scale. An information-centric approach has a number of advantages, defining precisely what is gained through radar illumination and serves as a measure of spectral efficiency. Bounding radar estimation rate and communications data rate jointly, systems can be designed as a joint optimization problem.
ContributorsPaul, Bryan (Author) / Bliss, Daniel W. (Thesis advisor) / Berisha, Visar (Committee member) / Kosut, Oliver (Committee member) / Tepedelenlioğlu, Cihan (Committee member) / Arizona State University (Publisher)
Created2017
Description
Lossy compression is a form of compression that slightly degrades a signal in ways that are ideally not detectable to the human ear. This is opposite to lossless compression, in which the sample is not degraded at all. While lossless compression may seem like the best option, lossy compression, which is used in most audio and video, reduces transmission time and results in much smaller file sizes. However, this compression can affect quality if it goes too far. The more compression there is on a waveform, the more degradation there is, and once a file is lossy compressed, this process is not reversible. This project will observe the degradation of an audio signal after the application of Singular Value Decomposition compression, a lossy compression that eliminates singular values from a signal’s matrix.
ContributorsHirte, Amanda (Author) / Kosut, Oliver (Thesis director) / Bliss, Daniel (Committee member) / Electrical Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Eigenvalues of the Gram matrix formed from received data frequently appear in sufficient detection statistics for multi-channel detection with Generalized Likelihood Ratio (GLRT) and Bayesian tests. In a frequently presented model for passive radar, in which the null hypothesis is that the channels are independent and contain only complex white Gaussian noise and the alternative hypothesis is that the channels contain a common rank-one signal in the mean, the GLRT statistic is the largest eigenvalue $\lambda_1$ of the Gram matrix formed from data. This Gram matrix has a Wishart distribution. Although exact expressions for the distribution of $\lambda_1$ are known under both hypotheses, numerically calculating values of these distribution functions presents difficulties in cases where the dimension of the data vectors is large. This dissertation presents tractable methods for computing the distribution of $\lambda_1$ under both the null and alternative hypotheses through a technique of expanding known expressions for the distribution of $\lambda_1$ as inner products of orthogonal polynomials. These newly presented expressions for the distribution allow for computation of detection thresholds and receiver operating characteristic curves to arbitrary precision in floating point arithmetic. This represents a significant advancement over the state of the art in a problem that could previously only be addressed by Monte Carlo methods.
ContributorsJones, Scott, Ph.D (Author) / Cochran, Douglas (Thesis advisor) / Berisha, Visar (Committee member) / Bliss, Daniel (Committee member) / Kosut, Oliver (Committee member) / Richmond, Christ (Committee member) / Arizona State University (Publisher)
Created2019
Description
This work focuses on the analysis and design of large-scale millimeter-wave andterahertz (mmWave/THz) beamforming apertures (e.g., reconfigurable reflective surfaces–
RRSs). As such, the small wavelengths and ample bandwidths of these frequencies enable
the development of high-spatial-resolution imaging and high-throughput wireless
communication systems that leverage electrically large apertures to form high-gain
steerable beams.
For the rigorous evaluation of these systems’ performance in realistic application
scenarios, full-wave simulations are needed to capture all the exhibited electromagnetic
phenomena. However, the small wavelengths of mmWave/THz bands lead to enormous
meshes in conventional full-wave simulators. Thus, a novel numerical decomposition
technique is presented, which decomposes the full-wave models in smaller domains with
less meshed elements, enabling their computationally efficient analysis. Thereafter, this
method is leveraged to study a novel radar configuration that employs a rotating linear
antenna with beam steering capabilities to form 3D images. This imaging process requires
fewer elements to carry out high-spatial-resolution imaging compared to traditional 2D
phased arrays, constituting a perfect candidate in low-profile, low-cost applications.
Afterward, a high-yield nanofabrication technique for mmWave/THz graphene
switches is presented. The measured graphene sheet impedances are incorporated into
equivalent circuit models of coplanar switches to identify the optimum mmWave/THz
switch topology that would enable the development of large-scale RRSs.ii
Thereon, the process of integrating the optimized graphene switches into largescale mmWave/THz RRSs is detailed. The resulting RRSs enable dynamic beam steering
achieving 4-bits of phase quantization –for the first time in the known literature–
eliminating the parasitic lobes and increasing the aperture efficiency. Furthermore, the
devised multi-bit configurations use a single switch-per-bit topology retaining low system
complexity and RF losses. Finally, single-bit RRSs are modified to offer single-lobe
patterns by employing a surface randomization technique. This approach allows for the use
of low-complexity single-bit configurations to suppress the undesired quantization lobes
without residing to the use of sophisticated multi-bit topologies.
The presented concepts pave the road toward the implementation and proliferation
of large-scale reconfigurable beamforming apertures that can serve both as mmWave/THz
imagers and as relays or base stations in future wireless communication applications.
ContributorsTheofanopoulos, Panagiotis (Author) / Trichopoulos, Georgios (Thesis advisor) / Balanis, Constantine (Committee member) / Aberle, James (Committee member) / Bliss, Dan (Committee member) / Groppi, Christopher (Committee member) / Arizona State University (Publisher)
Created2021
Description
This Creative Project was carried out in coordination with the capstone project, Around the Corner Imaging with Terahertz Waves. This capstone project deals with a system designed to implement Around the Corner, or Non Line-of-Sight (NLoS) Imaging. This document discusses the creation of a GUI using MATLAB to control the Terahertz Imaging system. The GUI was developed in response to a need for synchronization, ease of operation, easy parameter modification, and data management. Along the way, many design decisions were made ranging from choosing a software platform to determining how variables should be passed. These decisions and considerations are discussed in this document. The resulting GUI has measured up to the design criteria and will be able to be used by anyone wishing to use the Terahertz Imaging System for further research in the field of Around the Corner or NLoS Imaging.
ContributorsWood, Jacob Cannon (Author) / Trichopoulos, Georgios (Thesis director) / Aberle, James (Committee member) / Electrical Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05