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Description
Structural health management (SHM) is emerging as a vital methodology to help engineers improve the safety and maintainability of critical structures. SHM systems are designed to reliably monitor and test the health and performance of structures in aerospace, civil, and mechanical engineering applications. SHM combines multidisciplinary technologies including sensing, signal

Structural health management (SHM) is emerging as a vital methodology to help engineers improve the safety and maintainability of critical structures. SHM systems are designed to reliably monitor and test the health and performance of structures in aerospace, civil, and mechanical engineering applications. SHM combines multidisciplinary technologies including sensing, signal processing, pattern recognition, data mining, high fidelity probabilistic progressive damage models, physics based damage models, and regression analysis. Due to the wide application of carbon fiber reinforced composites and their multiscale failure mechanisms, it is necessary to emphasize the research of SHM on composite structures. This research develops a comprehensive framework for the damage detection, localization, quantification, and prediction of the remaining useful life of complex composite structures. To interrogate a composite structure, guided wave propagation is applied to thin structures such as beams and plates. Piezoelectric transducers are selected because of their versatility, which allows them to be used as sensors and actuators. Feature extraction from guided wave signals is critical to demonstrate the presence of damage and estimate the damage locations. Advanced signal processing techniques are employed to extract robust features and information. To provide a better estimate of the damage for accurate life estimation, probabilistic regression analysis is used to obtain a prediction model for the prognosis of complex structures subject to fatigue loading. Special efforts have been applied to the extension of SHM techniques on aerospace and spacecraft structures, such as UAV composite wings and deployable composite boom structures. Necessary modifications of the developed SHM techniques were conducted to meet the unique requirements of the aerospace structures. The developed SHM algorithms are able to accurately detect and quantify impact damages as well as matrix cracking introduced.
ContributorsLiu, Yingtao (Author) / Chattopadhyay, Aditi (Thesis advisor) / Rajadas, John (Committee member) / Dai, Lenore (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Jiang, Hanqing (Committee member) / Arizona State University (Publisher)
Created2012
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Description
In this thesis, an adaptive waveform selection technique for dynamic target tracking under low signal-to-noise ratio (SNR) conditions is investigated. The approach is integrated with a track-before-detect (TBD) algorithm and uses delay-Doppler matched filter (MF) outputs as raw measurements without setting any threshold for extracting delay-Doppler estimates. The particle filter

In this thesis, an adaptive waveform selection technique for dynamic target tracking under low signal-to-noise ratio (SNR) conditions is investigated. The approach is integrated with a track-before-detect (TBD) algorithm and uses delay-Doppler matched filter (MF) outputs as raw measurements without setting any threshold for extracting delay-Doppler estimates. The particle filter (PF) Bayesian sequential estimation approach is used with the TBD algorithm (PF-TBD) to estimate the dynamic target state. A waveform-agile TBD technique is proposed that integrates the PF-TBD with a waveform selection technique. The new approach predicts the waveform to transmit at the next time step by minimizing the predicted mean-squared error (MSE). As a result, the radar parameters are adaptively and optimally selected for superior performance. Based on previous work, this thesis highlights the applicability of the predicted covariance matrix to the lower SNR waveform-agile tracking problem. The adaptive waveform selection algorithm's MSE performance was compared against fixed waveforms using Monte Carlo simulations. It was found that the adaptive approach performed at least as well as the best fixed waveform when focusing on estimating only position or only velocity. When these estimates were weighted by different amounts, then the adaptive performance exceeded all fixed waveforms. This improvement in performance demonstrates the utility of the predicted covariance in waveform design, at low SNR conditions that are poorly handled with more traditional tracking algorithms.
ContributorsPiwowarski, Ryan (Author) / Papandreou-Suppappola, Antonia (Thesis advisor) / Chakrabarti, Chaitali (Committee member) / Kovvali, Narayan (Committee member) / Arizona State University (Publisher)
Created2011
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Description
This thesis encompasses research performed in the focus area of structural health monitoring. More specifically, this research focuses on high velocity impact testing of carbon fiber reinforced structures, especially plates, and evaluating the damage post-impact. To this end, various non-destructive evaluation techniques such as ultrasonic C-scan testing and flash thermography

This thesis encompasses research performed in the focus area of structural health monitoring. More specifically, this research focuses on high velocity impact testing of carbon fiber reinforced structures, especially plates, and evaluating the damage post-impact. To this end, various non-destructive evaluation techniques such as ultrasonic C-scan testing and flash thermography were utilized for post-impact analysis. MATLAB algorithms were written and refined for the localization and quantification of damage in plates using data from sensors such as piezoelectric and fiber Bragg gratings sensors. Throughout the thesis, the general plate theory and laminate plate theory, the operations and optimization of the gas gun, and the theory used for the damage localization algorithms will be discussed. Additional quantifiable results are to come in future semesters of experimentation, but this thesis outlines the framework upon which all the research will continue to advance.
ContributorsMccrea, John Patrick (Author) / Chattopadhyay, Aditi (Thesis director) / Borkowski, Luke (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor) / Department of Military Science (Contributor)
Created2015-05
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Description
This thesis encompasses research performed in the focus area of structural health monitoring. More specifically, this research focuses on high velocity impact testing of carbon fiber reinforced structures, especially plates, and evaluating the damage post-impact. To this end, various non-destructive evaluation techniques such as ultrasonic C-scan testing and flash thermography

This thesis encompasses research performed in the focus area of structural health monitoring. More specifically, this research focuses on high velocity impact testing of carbon fiber reinforced structures, especially plates, and evaluating the damage post-impact. To this end, various non-destructive evaluation techniques such as ultrasonic C-scan testing and flash thermography were utilized for post-impact analysis. MATLAB algorithms were written and refined for the localization and quantification of damage in plates using data from sensors such as piezoelectric and fiber Bragg gratings sensors. Throughout the thesis, the general plate theory and laminate plate theory, the operations and optimization of the gas gun, and the theory used for the damage localization algorithms will be discussed. Additional quantifiable results are to come in future semesters of experimentation, but this thesis outlines the framework upon which all the research will continue to advance.
ContributorsMccrea, John Patrick (Author) / Chattopadhyay, Aditi (Thesis director) / Borkowski, Luke (Committee member) / Department of Military Science (Contributor) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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Description
This thesis covers the design, development and testing of two high-power radio frequency transmitters that operate in C-band and X-band (System-C/X). The operational bands of System-C/X are 3-6 GHz and 8-11 GHz, respectively. Each system is designed to produce a peak effective isotropic radiated power of at least 50 dBW.

This thesis covers the design, development and testing of two high-power radio frequency transmitters that operate in C-band and X-band (System-C/X). The operational bands of System-C/X are 3-6 GHz and 8-11 GHz, respectively. Each system is designed to produce a peak effective isotropic radiated power of at least 50 dBW. The transmitters use parabolic dish antennas with dual-linear polarization feeds that can be steered over a wide range of azimuths and elevations with a precision of a fraction of a degree. System-C/X's transmit waveforms are generated using software-defined radios. The software-defined radio software is lightweight and reconfigurable. New waveforms can be loaded into the system during operation and saved to an onboard database. The waveform agility of the two systems lends them to potential uses in a wide range of broadcasting applications, including radar and communications. The effective isotropic radiated power and beam patterns for System-C/X were measured during two field test events in July 2021 and January 2022. The performance of both systems was found to be within acceptable limits of their design specifications.
ContributorsGordon, Samuel (Author) / Bliss, Daniel (Thesis advisor) / Mauskopf, Philip (Thesis advisor) / Papandreou-Suppappola, Antonia (Committee member) / Arizona State University (Publisher)
Created2022
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Description
Humanpresence detection is essential for a various number of applications including defense and healthcare. Accurate measurements of distances, relative velocities of humans, and other objects can be made with radars. They are largely impervious to external factors like the impact of smoke, dust, or rain. They are also capable of

Humanpresence detection is essential for a various number of applications including defense and healthcare. Accurate measurements of distances, relative velocities of humans, and other objects can be made with radars. They are largely impervious to external factors like the impact of smoke, dust, or rain. They are also capable of working in varied intensity of light in indoor environments. This report explores the analyzing of real data captured and the application of different detection algorithms. Adaptive thresholding suppresses stationary backgrounds while maintaining detection thresholds to keep false alarm rates low. Using different approaches of Constant False Alarm Rate (CFAR) namely Cell averaging, Smallest of Cell averaging,Greatest of Cell Averaging and Order Statistic, this report aims to show its performance in detecting humans in an indoor environment using real time data collected. The objective of this project is to explain the signal processing chain of presence detection using a small scale RADAR
ContributorsDixit, Anjali (Author) / Bliss, Daniel W (Thesis advisor) / Papandreou-Suppappola, Antonia (Committee member) / Alkhateeb, Ahmed (Committee member) / Arizona State University (Publisher)
Created2024
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Description
As the demand for wireless systems increases exponentially, it has become necessary

for different wireless modalities, like radar and communication systems, to share the

available bandwidth. One approach to realize coexistence successfully is for each

system to adopt a transmit waveform with a unique nonlinear time-varying phase

function. At the receiver of the system

As the demand for wireless systems increases exponentially, it has become necessary

for different wireless modalities, like radar and communication systems, to share the

available bandwidth. One approach to realize coexistence successfully is for each

system to adopt a transmit waveform with a unique nonlinear time-varying phase

function. At the receiver of the system of interest, the waveform received for process-

ing may still suffer from low signal-to-interference-plus-noise ratio (SINR) due to the

presence of the waveforms that are matched to the other coexisting systems. This

thesis uses a time-frequency based approach to increase the SINR of a system by estimating the unique nonlinear instantaneous frequency (IF) of the waveform matched

to the system. Specifically, the IF is estimated using the synchrosqueezing transform,

a highly localized time-frequency representation that also enables reconstruction of

individual waveform components. As the IF estimate is biased, modified versions of

the transform are investigated to obtain estimators that are both unbiased and also

matched to the unique nonlinear phase function of a given waveform. Simulations

using transmit waveforms of coexisting wireless systems are provided to demonstrate

the performance of the proposed approach using both biased and unbiased IF estimators.
ContributorsGattani, Vineet Sunil (Author) / Papandreou-Suppappola, Antonia (Thesis advisor) / Richmond, Christ (Committee member) / Maurer, Alexander (Committee member) / Arizona State University (Publisher)
Created2018
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Description
In recent years, there has been an increased interest in sharing available bandwidth to avoid spectrum congestion. With an ever-increasing number wireless users, it is critical to develop signal processing based spectrum sharing algorithms to achieve cooperative use of the allocated spectrum among multiple systems in order to reduce

In recent years, there has been an increased interest in sharing available bandwidth to avoid spectrum congestion. With an ever-increasing number wireless users, it is critical to develop signal processing based spectrum sharing algorithms to achieve cooperative use of the allocated spectrum among multiple systems in order to reduce interference between systems. This work studies the radar and communications systems coexistence problem using two main approaches. The first approach develops methodologies to increase radar target tracking performance under low signal-to-interference-plus-noise ratio (SINR) conditions due to the coexistence of strong communications interference. The second approach jointly optimizes the performance of both systems by co-designing a common transmit waveform.

When concentrating on improving radar tracking performance, a pulsed radar that is tracking a single target coexisting with high powered communications interference is considered. Although the Cramer-Rao lower bound (CRLB) on the covariance of an unbiased estimator of deterministic parameters provides a bound on the estimation mean squared error (MSE), there exists an SINR threshold at which estimator covariance rapidly deviates from the CRLB. After demonstrating that different radar waveforms experience different estimation SINR thresholds using the Barankin bound (BB), a new radar waveform design method is proposed based on predicting the waveform-dependent BB SINR threshold under low SINR operating conditions.

A novel method of predicting the SINR threshold value for maximum likelihood estimation (MLE) is proposed. A relationship is shown to exist between the formulation of the BB kernel and the probability of selecting sidelobes for the MLE. This relationship is demonstrated as an accurate means of threshold prediction for the radar target parameter estimation of frequency, time-delay and angle-of-arrival.



For the co-design radar and communications system problem, the use of a common transmit waveform for a pulse-Doppler radar and a multiuser communications system is proposed. The signaling scheme for each system is selected from a class of waveforms with nonlinear phase function by optimizing the waveform parameters to minimize interference between the two systems and interference among communications users. Using multi-objective optimization, a trade-off in system performance is demonstrated when selecting waveforms that minimize both system interference and tracking MSE.
ContributorsKota, John S (Author) / Papandreou-Suppappola, Antonia (Thesis advisor) / Berisha, Visar (Committee member) / Bliss, Daniel (Committee member) / Kovvali, Narayan (Committee member) / Arizona State University (Publisher)
Created2016
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Description
Waveform design that allows for a wide variety of frequency-modulation (FM) has proven benefits. However, dictionary based optimization is limited and gradient search methods are often intractable. A new method is proposed using differential evolution to design waveforms with instantaneous frequencies (IFs) with cubic FM functions whose coefficients are constrained

Waveform design that allows for a wide variety of frequency-modulation (FM) has proven benefits. However, dictionary based optimization is limited and gradient search methods are often intractable. A new method is proposed using differential evolution to design waveforms with instantaneous frequencies (IFs) with cubic FM functions whose coefficients are constrained to the surface of the three dimensional unit sphere. Cubic IF functions subsume well-known IF functions such as linear, quadratic monomial, and cubic monomial IF functions. In addition, all nonlinear IF functions sufficiently approximated by a third order Taylor series over the unit time sequence can be represented in this space. Analog methods for generating polynomial IF waveforms are well established allowing for practical implementation in real world systems. By sufficiently constraining the search space to these waveforms of interest, alternative optimization methods such as differential evolution can be used to optimize tracking performance in a variety of radar environments. While simplified tracking models and finite waveform dictionaries have information theoretic results, continuous waveform design in high SNR, narrowband, cluttered environments is explored.
ContributorsPaul, Bryan (Author) / Papandreou-Suppappola, Antonia (Thesis advisor) / Bliss, Daniel W (Thesis advisor) / Tepedelenlioğlu, Cihan (Committee member) / Arizona State University (Publisher)
Created2014
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Description
As the demand for spectrum sharing between radar and communications systems is steadily increasing, the coexistence between the two systems is a growing and very challenging problem. Radar tracking in the presence of strong communications interference can result in low probability of detection even when sequential Monte Carlo

tracking methods

As the demand for spectrum sharing between radar and communications systems is steadily increasing, the coexistence between the two systems is a growing and very challenging problem. Radar tracking in the presence of strong communications interference can result in low probability of detection even when sequential Monte Carlo

tracking methods such as the particle filter (PF) are used that better match the target kinematic model. In particular, the tracking performance can fluctuate as the power level of the communications interference can vary dynamically and unpredictably.

This work proposes to integrate the interacting multiple model (IMM) selection approach with the PF tracker to allow for dynamic variations in the power spectral density of the communications interference. The model switching allows for a necessary transition between different communications interference power spectral density (CI-PSD) values in order to reduce prediction errors. Simulations demonstrate the high performance of the integrated approach with as many as six dynamic CI-PSD value changes during the target track. For low signal-to-interference-plus-noise ratios, the derivation for estimating the high power levels of the communications interference is provided; the estimated power levels would be dynamically used in the IMM when integrated with a track-before-detect filter that is better matched to low SINR tracking applications.
ContributorsZhou, Jian (Author) / Papandreou-Suppappola, Antonia (Thesis advisor) / Kovvali, Narayan (Committee member) / Berisha, Visar (Committee member) / Arizona State University (Publisher)
Created2015