IEEE Geoscience and Remote Sensing Magazine - June 2017 - 73

Range (cm) (Pr = 1.8)

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0
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radar-derived and in situ measured snow-thickness data
using the latest Snow Radar data that now include system-response deconvolution. We have demonstrated
that snow depths derived from the Snow Radar system
agree favorably with coincident in situ measurements.
The NASA OIB Snow Radar data set, which includes the
system response deconvolution, is now available to the
community for further use and evaluation at the NSIDC
website (https://nsidc.org/data/irsno1b).
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Distance (km)

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fIgURE 19. The radar echograms for the flight lines shown in

Snow Thickness (cm) (Pr = 1.8)

Figure 18.

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Snow Radar Data
fIgURE 20. The radar-derived snow-thickness data from the radar
echogram shown in Figure 19.

R = 0.89144

Radar Measured Thickness (cm)

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Data
Fit
Y=T

10
0

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In Situ Measured Thickness (cm)

fIgURE 21. The scatterplots of the radar-derived and in situ snow-

thickness data collected over the sea ice offshore of Barrow, Alaska,
with the NRL DISTANCE program, shown in Figures 18-20.
june 2017

ieee Geoscience and remote sensing magazine

ACKNOWLEDgMENT
We would like to thank all of the past and present faculty,
staff, and students at CReSIS who have contributed to the
development and field operation of the Snow Radar. We
would also like to thank Melinda Webster for providing the
in situ snow-thickness data collected from the BROMEX mission and the NRL team for collecting the in situ snow data.
This work was supported in part by NSF under grant ANT0424589, NASA under grant NNX10AT68GT, NRL under
contract N00173-13-C-2032, and the German Ministry for
Education and Research under grant 03F0700A. Funding for
the NRL Arctic flight data was provided by the NRL under
program element 61153N.
AUTHOR INfORMATION
jie-bang Yan (jbyan@ua.edu) received his B.Eng. degree (firstclass honors) in electronic and communications engineering from the University of Hong Kong, China, in 2006,
his M.Phil. degree in electronic and computer engineering
from the Hong Kong University of Science and Technology,
China, in 2008, and his Ph.D. degree in electrical and computer engineering from the University of Illinois at Urbana-
Champaign, in 2011. He is currently an assistant professor
of electrical and computer engineering at the University of
Alabama, Tuscaloosa. He holds two U.S. patents and a U.S.
patent application related to novel antenna technologies.
He was a recipient of the Best Paper Award at the 2007 IEEE
(Hong Kong) Antennas and Propagation Society/Microwave
Theory and Techniques Society Postgraduate Conference.
His current research interests include the design and analysis of antennas and phased arrays, ultrawide-band radar systems, radar signal processing, and remote sensing. He is a
Member of the IEEE.
Sivaprasad gogineni (pgogineni@ua.edu) received his
Ph.D. degree in electrical engineering from the University of
Kansas (KU), Lawrence, in 1984. He is currently a Cudworth
professor with the Department of Electrical and Computer
Engineering and the Department of Aerospace Engineering
and Mechanics at the University of Alabama, Tuscaloosa. He
was formerly a Deane E. Ackers distinguished professor at
KU, where he was the director of the National Science Foundation Science and Technology with the Center for Remote
Sensing of Ice Sheets. He developed several radar systems
that are currently being used at KU for the sounding and
imaging of polar ice sheets. He has also participated in field
experiments in the Arctic and Antarctica. He has authored
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