Menu Close


Professor Swindlehurst works in the Department of Electrical Engineering and Computer Science at the University of California, Irvine. He 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:

Current Project

  • Space-time communications for mobile tactical ad hoc networks
    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.
  • Multiple antenna techniques for secure physical layer communications
    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.
  • Adaptive tracking and communications with Unmanned Aerial Vehicles
    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.
  • Space-time adaptive processing (STAP) for airborne surveillance radars
    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.
  • Localization and Dipole Moment Estimation for EEG Sources
    Non-invasively 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.
  • Robust synchronization and time-delay estimation for navigation systems (GPS)
    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.
  • Multiuser MIMO wireless communications
    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.
  • Blind MIMO channel estimation and equalization
    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.
  • MIMO channel modeling, prediction and propagation characterization
    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.
  • Direction finding in adverse environments
    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.

For more information, please visit his webpage.