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

Upcoming Symposium

Benjamin Franklin Medalist

The CAC is proud to host a symposium honoring Dr. Shunichi Iwasaki and Dr. Mark H. Kryder, recipients of the 2014 Benjamin Franklin Medal in Electrical Engineering.

April 23, 2014
Free registration and details

Contact Us

Dr. Moeness Amin
Center for Advanced Communications
Phone: 610-519-4263

Janice J. Moughan
Center Coordinator
Center for Advanced Communications
Phone: 610-519-4599

Address: 800 Lancaster Ave
Villanova University
Villanova, PA 19085

Research Activities

Research emphases of the Center for Advanced Communications encompass several aspects of advances in broadband wireless communications and RF acoustic sensing, and imaging. Some research activities include:

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.

•  Cable Response
•  Antenna Bandwidth and Gain
•  Wall Frequency Response

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