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\begin{document}
\title{\fontsize{13bp}{18bp}\selectfont ON THE POTENTIAL OF ADAPTIVE BEAMFORMING FOR PHASED-ARRAY WEATHER RADAR}
\author{FENG NAI}
\depositdate{\fontsize{13bp}{18bp}\selectfont 2017}
\majorfield{SCHOOL OF ELECTRICAL AND COMPUTER ENGINEERING}
\memberone{Dr. Robert Palmer, Co-Chair}
\membertwo{Dr. Sebasti\'{a}n Torres, Co-Chair}
\memberthree{Dr. Nathan Goodman}
%next two members are used in dissertation
\memberfour{Dr. Tian-You Yu}
\memberfive{Dr. Xuguang Wang}
%%%%
\begin{preface}
\prefacesectionX{\fontsize{13bp}{18bp}\selectfont \textnormal{Dedication}}
\fontsize{13bp}{18bp}\selectfont 
To my mother and father, whose enduring support allowed me to focus all my attention on completing my school work. To my grandparents, whose love and wisdom helped me to push through the most difficult times during this journey. To my aunts and uncles, whose brief visit brought me the delicious food I had always missed since I left home. To my cousins, whose competitiveness always drove me to do better and achieve more. To my friends, whose jokes and stories always cheered up my day. To my best friend, Ms. Zhichao Chen, for her encouragement, patience, and unshakable faith in me. 

\prefacesection{Acknowledgements}

\fontsize{13bp}{18bp}\selectfont I would like to thank my advisors, Dr. Sebasi\'{a}n Torres and Dr. Robert Palmer, who also served as my M. S. advisors. Without their guidance and support, it would not be possible for me to achieve my dream of earning a doctoral degree. From my first day in graduate school, Dr. Torres and Dr. Palmer encouraged me to explore, to read, and to learn as much as possible. When I made progress on my research, no matter how small the advancement was, they always gave me praise and encouragement to keep me motivated. When my research was stuck, they always offered critical analysis and new ideas for me to investigate. More importantly, they always had faith in me to overcome any challenge no matter how insurmountable it seemed at the time. Their patience and understanding allowed me to grow and overcome many of the problems I faced. In my eight years of graduate school, my advisors gave me the opportunity to interact with and to learn from the best role models I can possibly imagine. I would have never become who I am today without the help of my advisors.

I also would like to thank my doctoral committee members, Dr. Tian-You Yu, Dr. Nathan Goodman, and Dr. Xuguang Wang, for their help and support during my years at the University of Oklahoma. Dr. Yu's class on radar engineering taught me the necessary background information on radar systems to understand the importance and nuances of many trade-offs in a radar design. Dr. Goodman's class on radar signal processing taught me the different approaches to translate radar data from random signals to useful information. I would not be able to complete my research without the solid fundation these classes provided to me. 

The journey through graduate school would have been much more difficult without the help of many friends and colleagues in the ARRC. Kenta Hood, who was also a graduate student advised by Dr. Palmer and Dr. Torres, served as my first role model on how to be a graduate student. I will always remember how he printed out and presented his latest results in our weekly meetings. By teaching me how to operate the AIR, Brad Isom set me on the path to spend numerous spring days chasing tornadoes in Oklahoma. David Bodine and Jim Kurdzo are two of the most intelligent and hard-working students I have ever had the pleasure to work with. By operating the AIR together, I learned important teamwork and communication skills from them. Jim's constant drive for perfection and David's calmness are both qualities I respect deeply and aspire to have. My officemate, Fanxing Kong, provided numerous discussions that helped me with my research and future career goals. Redmond Kelly, John Meier, and Matt McCord also provided help to me whenever I needed them, and I am deeply grateful to have known and worked with them.

Finally, it would have been impossible for me to complete this work without the support of my family. My parents, Li Wei and Kang Nai, always supported me as I spent year after year in school. Without their care and love, it would be easy for me to get distracted and lost along the way. They taught me to be humble, to work hard, and to dedicate myself to my dreams. I would not have succeeded without these important life values. For that, I  am deeply thankful. 

 %must leave a blank line next to avoid bug:


\tableofcontents
\listoftables
\listoffigures
\prefacesection{Abstract} 

\fontsize{13bp}{18bp}\selectfont As the Weather Surveillance Radar 1988 Doppler network reaches the end of its expected life, a network of multifunction phased-array radars (MPAR) supporting both aircraft and weather surveillance missions has been proposed. A phased-array system should match the sensitivity, spatial resolution, and data quality of the WSR-88D while having a update time of 60 seconds for weather surveillance. Since an MPAR system must complete both weather and aircraft surveillance missions, the update time reduction provided by having multiple faces is insufficient to achieve the desired 60 second update time for weather surveillance. Therefore, it is likely that multiple simultaneous beams would be needed per face to meet the timeline requirements. An approach to achieve multiple receive beams is to use a spoiled transmit beam and to form a cluster of simultaneous receive beams. However, a significant challenge for this approach is the potential of high sidelobe levels in the two-way radiation pattern, which can result in significantly biased estimates of the radar variables in situations where the signal power has large spatial variation. This dissertation proposes an adaptive beamspace algorithm designed for phased-array weather radar that utilizes a spoiled transmit beam and a cluster of simultaneous receive beams to achieve the desired timeline. Taking advantage of the adaptive algorithm's ability to automatically adjust sidelobe levels to match the scene, the high-sidelobe problem associated with a spoiled transmit beam is mitigated. Through extensive simulations, it is shown that adaptive beamspace processing can produce accurate and calibrated estimates of weather radar variables. Furthermore, it is demonstrated that the adaptive beamspace algorithm can automatically reject interference signals and reduce their impact on the radar-variable estimates. Additionally, it is shown that, despite higher sidelobe levels, the adaptive beamspace algorithm can perform similarly to a conventional system based on a dish antenna in terms of biases when reflectivity gradients are present. Finally, the adaptive beamspace algorithm is shown to compare favorably to some alternative solutions that can also achieve the desired MPAR timeline requirement while preserving data quality. 

\end{preface}


\fontsize{13bp}{18bp}\selectfont 

\chapter{Introduction}
\label{chap.intro}
\input{intro}
\chapter{Weather Radar Fundamentals}
\label{chap.wx_radar_fund}
\input{radar_fund}
\chapter{Phased-Array Radars}
\label{chap.par_fund}
\input{par_fund}
\chapter{Adaptive Beamspace Processing}
\label{chap.adapt_bs}
\input{adap_bs}
\chapter{Comparison of Alternatives}
\label{chap.alt_comp}
\input{alt_comp}
\chapter{Conclusions and Future Work}
\label{chap.conc}
\input{conc}



\newpage
\references{amermeteorsoc}{nai_dissertation}
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\end{document}