EE Colloquium: Human Detection and Characterization through Barriers

Abstract:

This talk will address the phenomenology and characteristics of wave propagation through barriers, such as ground, walls, foliage, etc. behind which targets may be hidden, as a function of frequency and material properties. Techniques for detecting such obscured targets using radar techniques will be discussed. Both conventional and emerging waveforms will be presented. The tutorial will be subdivided into the following main sections.

Part I will describe different types of radar waveforms in general use, both conventional and emerging. These will include pulsed, impulse, dual-frequency, FMCW (linear and stepped), noise (random and pseudorandom), and noise-like (chaotic), with special reference to the unique requirements for through-the-barrier imaging applications.

In Part II, we will discuss how specific waveforms are affected by the electromagnetic environment and assess the limitations of current techniques. We will describe how the waveforms can be adapted or tailored to suit the unique needs of through-the-barrier detection.

In Part III, we will consider emerging waveform design for optimal target detection in enclosed structures behind barriers. Techniques based on signature exploitation, such as matched illumination theory and mutual information formulation, will be presented for both monostatic and multistatic operation.

Part IV will conclude by providing directions for further research.

Bio:

Ram Narayanan received his B.Tech. from IIT Madras in 1976 and his doctorate from UMass Amherst in 1988. He served as research and development engineer at Bharat Electronics Limited in India from 1976–83, as graduate research assistant at UMass from 1983–88, and as a faculty member at the University of Nebraska-Lincoln from 1988–2003. He is currently a professor of electrical engineering at Penn State. Dr. Narayanan has coauthored more than 160 journal papers and 400 conference publications. His current research interests include image analysis, radar detection of mines and IEDs, nonlinear radar, noise radar, cognitive radar, medical radar, quantum radar, radar networks, compressive sensing, and machine learning. He is a fellow of IEEE, SPIE, and IETE.

 

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Media Contact: Iam-Choon Khoo

 
 

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The School of Electrical Engineering and Computer Science was created in the spring of 2015 to allow greater access to courses offered by both departments for undergraduate and graduate students in exciting collaborative research fields.

We offer B.S. degrees in electrical engineering, computer science, computer engineering and data science and graduate degrees (master's degrees and Ph.D.'s) in electrical engineering and computer science and engineering. EECS focuses on the convergence of technologies and disciplines to meet today’s industrial demands.

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