Prof. Richard J. Kozick
Professor of Electrical Engineering at Bucknell Univ
SPIE Involvement:
Author | Instructor
Area of Expertise:
Signal processing , Localization and tracking
Websites:
Publications (9)

Proceedings Article | 12 May 2011 Paper
Richard Kozick, Gene Whipps, Joshua Ash
Proceedings Volume 8046, 804604 (2011) https://doi.org/10.1117/12.884700
KEYWORDS: Sensors, Statistical analysis, Radon, Statistical modeling, Data modeling, Monte Carlo methods, Algorithm development, 3D modeling, Cadmium, Sensor networks

Proceedings Article | 11 May 2007 Paper
Proceedings Volume 6562, 656207 (2007) https://doi.org/10.1117/12.719874
KEYWORDS: Magnetism, Acoustics, Brain-machine interfaces, Data modeling, Feature extraction, Magnetic sensors, Sensors, Motion models, Magnetometers, Roads

Proceedings Article | 1 September 2004 Paper
Brian Sadler, Richard Kozick, Sandra Collier
Proceedings Volume 5417, (2004) https://doi.org/10.1117/12.541361
KEYWORDS: Signal to noise ratio, Sensors, Scattering, Atmospheric propagation, Spatial coherence, Turbulence, Wave propagation, Acoustics, Statistical analysis, Signal attenuation

Proceedings Article | 7 August 2002 Paper
Proceedings Volume 4743, (2002) https://doi.org/10.1117/12.444512
KEYWORDS: Sensors, Doppler effect, Signal to noise ratio, Motion models, Data fusion, Data communications, Interference (communication), Signal processing, Sensor networks, Detection and tracking algorithms

Proceedings Article | 27 September 2001 Paper
Proceedings Volume 4393, (2001) https://doi.org/10.1117/12.441255
KEYWORDS: Sensors, Signal to noise ratio, Spatial coherence, Source localization, Signal processing, Acoustics, Spectral coherence, Doppler effect, Array processing, Wave propagation

Showing 5 of 9 publications
Course Instructor
SC712: Energy-Constrained Sensor Networks, Aeroacoustics, and Distributed Signal Processing
This course presents the rich interplay between sensing, signal processing, and communications in energy-constrained sensor networks. The communications load in the network is highly dependent on the distributed signal processing strategy that is used for detection and estimation tasks. Decoupled design of the signal processing algorithms and communication network protocols may be drastically inefficient from the perspectives of minimizing communications bandwidth and node energy consumption. A cross-layer design approach that spans sensing, signal processing, and communications is the key to energy-constrained network design. The first half of the course presents a broad view of many aspects of communications and network topology, including a DoD perspective on current and future applications. Topics include duty cycling for energy savings, network architecture and capacity, network synchronization, node geolocation, and the interaction of the physical, MAC, and higher layers for energy saving communications. The second half of the course is focused on the specific application of an aeroacoustic sensor network used for detection, localization, classification, and tracking of acoustic sources such as vehicles. Topics include the basics of acoustic propagation, source detection, angle-of-arrival estimation, Doppler processing, and source localization. The theory is illustrated with many experimental examples. The network performance is strongly impacted by aeroacoustic propagation, and we present distributed signal processing schemes that maintain nearly globally optimal performance with significantly reduced communications load.
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