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With recent advances in both algorithm and component technologies, THrough
Wall At RF (THWARF) is emerging as an affordable sensor technology supporting
a variety of applications, such as emergency rescue and firefighting. Due
to the complexities associated with the development of successful through-wall
systems, commercial offerings of through-wall technology have been limited
to date. THWARF sensing presents numerous technical challenges including
a less-than-cooperative propagation environment, (often) ad hoc antenna
deployments, and inhomogeneities and non-stationarities in both the background
environment and target set, thereby rendering through-wall imaging and sensing
a difficult proposition.
While through-wall addresses a number of practical problems, it is dual-use
with obvious military applications. This, combined with intellectual property
issues, tends to reduce the incentive to collaborate and socialize ideas,
and generally stifles innovation in the field. It is our contention that
system development suffers and sub-optimal solutions emerge from less-than-systematic
development and evaluation processes. Although many of the institutional
problems will likely never be overcome, development efforts can be improved
by standardizing at some levels. At present, it is difficult to compare
and evaluate systems in a consistent manner. The community lacks agreed
upon performance metrics and standardized test scenes. In addition, unlike
other communities such as speech, adaptive array processing, and automatic
target recognition, the through-wall community lacks benchmark datasets.
Benchmark datasets could facilitate the standardization of performance metrics
and the development and comparison of algorithms and system concepts.
CACs Through-The-Wall Imaging Experiments
In an attempt to increase the coherence of algorithm and technology development
and evaluation relevant to TWARF sensing, the Center for Advanced Communications
(CAC) at Villanova University has conducted several preliminary through-the-wall
imaging experiments and collected datasets under the supervision of Defense
Advanced Research Project Agency (DARPA) and in collaboration with the Air
Force Research Laboratory (AFRL). The datasets were collected in general
engineering work space at the University that has been lined with radar
absorbing material. Data is collected with largely off-the-shelf equipment
including an Agilent network analyzer, Model ENA 5071B.
The datasets include
free-space and through-wall collections for three different arrangements
of the room's contents: empty scene, calibration scene, and populated scene.
The empty scene allows measurement of the noise/clutter background and supports
coherent subtraction with the other two scenes. The calibration scene contains
isolated reflectors that may be used to determine a fully-polarimetric radiometric
calibration solution for the experimental system. The populated scene contains
a number of common objects such as a phone, computer, tables, chair and
filing cabinet. In addition, a jug of saline solution has been added to
crudely approximate a human.
The wall is composed of plywood and gypsum
board on a wooden frame. Two horn antennas are mounted on a 2D scanner that
moves the antennas along and adjacent to the wall and is controlled by the
network analyzer. Two additional antennas are fixed to the scanner frame
and act as bistatic receivers. Other attributes of the data include a 1
GHz bandwidth stepped-frequency waveform centered at 2.5 GHz and a two-dimensional
synthetic aperture, 49" on a side, with a sample spacing of 0.875" on a
square grid. For more information, please view the detailed description of the RF system and experimental
conditions.
The datasets are admittedly sterile and somewhat naïve as they relate to problems encountered in real-world applications. The datasets represent a necessary compromise given the potential military utility of the technology. We hope that others will consider both natural and novel extensions to our work.
Please send all queries regarding this web site to Dr. Fauzia Ahmad
at fauzia.ahmad@villanova.edu.
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Tests on Data and Equipment Artifacts
The data collections, available on the “Experiments on Through-the-wall
Imaging” website, are among the first taken by the recently integrated instrumentation
suite at Villanova. Researchers here are just beginning to analyze the data.
Initial results suggest that objects are generally and clearly visible in
beamformed outputs. However, there are as yet unexplained signals in the
dataset. This isn't unexpected. Because of the dynamic ranges of the scenes,
the resulting environment is quite complicated, despite our efforts to simplify
it. These unexplained features may prove to be real or equipment-related
artifacts, but likely represent interesting opportunities for researchers
in either case. We are currently in the process of conducting tests to resolve
these issues and will post our results here periodically.
For More Information For more information you can view the
ReadMe
file for an explanation of the datasets or the the
scene details
for their detailed dimensions.
Please send all queries regarding this web site to Dr. Fauzia Ahmad at
fauzia.ahmad@villanova.edu
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