Angel's Landing, Zion NP
|A Lee Swindlehurst
Department of Electrical Engineering and Computer Science
University of California, Irvine
Office: 4436 Engineering Hall
Phone: (949) 824-2818
Fax: (949) 824-3779
A. LEE SWINDLEHURST received the B.S., summa cum laude, and M.S. degrees in Electrical Engineering from Brigham Young University, Provo, Utah, in 1985 and 1986, respectively, and the PhD degree in Electrical Engineering from Stanford University in 1991. From 1986-1990, he was employed at ESL, Inc., of Sunnyvale, CA, where he was involved in the design of algorithms and architectures for several radar and sonar signal processing systems. He was on the faculty of the Department of Electrical and Computer Engineering at Brigham Young University from 1990-2007, where he was a Full Professor and served as Department Chair from 2003-2006. During 1996-1997, he held a joint appointment as a visiting scholar at both Uppsala University, Uppsala, Sweden, and at the Royal Institute of Technology, Stockholm, Sweden. From 2006-07, he was on leave working as Vice President of Research for ArrayComm LLC in San Jose, California. He is currently a Professor of Electrical Engineering and Computer Science at the University of California at Irvine.
Dr. Swindlehurst is a Fellow of the IEEE, and a past Secretary of the IEEE Signal Processing Society. He is currently serving as Editor-in-Chief of the IEEE Journal of Selected Topics in Signal Processing, as a member of the Editorial Boards for the EURASIP Journal on Wireless Communications and Networking and the IEEE Signal Processing Magazine, and is a past Associate Editor for the IEEE Transactions on Signal Processing. He is a recipient of several paper awards: the 2000 IEEE W. R. G. Baker Prize Paper Award, the 2006 IEEE Signal Processing Society’s Best Paper Award, the 2006 IEEE Communications Society Stephen O. Rice Prize in the Field of Communication Theory and is co-author of a paper that received the IEEE Signal Processing Society Young Author Best Paper Award in 2001.
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Prof. Swindlehurst conducts research in the application of detection and estimation theory to problems in signal processing and wireless communications. He is primarily interested in applications that involve multiple antennas or sensors, such as source localization and tracking (radar, sonar, EEG, GPS), MIMO wireless communications and channel modeling, interference cancellation, multipath mitigation, etc. Examples of current and past projects include:
|If the nodes in a wireless ad hoc network possess multiple antennas, then a number of possibilities such as multi-packet reception and downlink broadcasting present themselves. This project focuses on cross-layer optimization problems involving the effect of multiple antennas on higher layer network functions such as connectivity, forwarding, scheduling and routing, and how the extra available degrees of freedom can best be used to increase network throughput and link quality.|
|Security is traditionally handled at the higher layers of a communications network, although the availability of multiple antennas at the physical layer offers several interesting security-enhancing possibilities. This project centers on these possibilities, including eavesdropper jamming, secure waveform coding (data hiding), generalized physical layer hopping (constellation and beam hopping), location-based encryption and active jammer avoidance.|
|This work investigates the advantages a network of UAVs provides in tracking and enhancing network connectivity. In the tracking application, Prof. Swindlehurst views the UAVs as meta-elements in a large reconfigurable sensor array; the positions and headings of the UAVs can be controlled in order to improve their ability to detect, localize and track targets. For communications, he has explored the use of UAVs as relay nodes that can be positioned in order to increase the connectivity and throughput of an ad hoc network.|
|Airborne surveillance radars must counteract strong ground clutter that obstructs target returns in the spatial domain, as well as broadband jamming, which obstructs target in the frequency domain. Using space-only (e.g., beamforming) or time-only adaptive filters yields poor performance in difficult environments. This project emphasizes the use of parametric space-time clutter and jammer models that provide acceptable performance with a fraction of the normally required secondary data support and computational complexity.|
|Noninvasively characterizing the location and type of electrical brain activity is a key to developing brain-computer interfaces that allow individuals with disabilities to interact with the world. This research has focused on the application of advanced techniques from radar signal processing to the problem of characterizing the electroencephalography (EEG) activity of the brain. Difficult environments involving strong non-stationary background brain activity, coherent waveforms, moving sources and short data segments are of particular interest.|
|Multipath interference and jamming are key impediments to the accuracy of geo-positioning systems such as GPS. Multi-antenna GPS receivers offer both interference and multipath suppression as well as enhanced time synchronization performance, and can provide order-of-magnitude improvements in localization accuracy. In this work, algorithms have been developed that simultaneously and adaptively account for arbitrary jammer statistics and same-signal multipath reflections, both coherent and incoherent.|
|In downlink or broadcast MIMO channels, a trade-off must be made between obtaining high throughput to an individual user and reducing unwanted interference received by other users. While so-called “dirty paper” techniques have been shown to be optimal for this application, Prof. Swindlehurst’s work has focused on lower-complexity linear and non-linear transmit beamforming algorithms that provide reasonable performance with significantly reduced cost.|
|The term “blind” here refers to the use of methods that do not require knowledge of any pilot symbols broadcast by the transmitter, and hence are of interest in non-cooperative surveillance applications. In this project, it was demonstrated that knowledge of only the transmitter’s space-time coding strategy, and not the actual transmitted symbols, was sufficient for reliable decoding of the transmitted data. In cases where training symbols are also known, improved performance can be obtained.|
|Together with colleagues at Brigham Young University, Prof. Swindlehurst participated in the development of several MIMO testbeds that were used to collect MIMO channel data in a number of environments. This data was used to construct and validate realistic channel models for both indoor and outdoor applications, and to evaluate the benefits of different types of antennas, array geometries and polarization orientations.|
|This long-term effort has involved the study of direction-of-arrival estimation techniques in low SNR or highly coherent environments using arrays that are imprecisely calibrated.|
In addition to the projects described above, Prof. Swindlehurst has served as a consultant to several companies on recent efforts including DARPA’s MNM (Mobile Networked MIMO) and NSC (Novel Satellite Communications) projects, and a Navy project on low-angle tracking over the ocean surface.