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Center for Surveillance Research (CSR)

Center Overview

The Center for Surveillance Research (CSR) is a collaborative effort by academia, government, and industry to conduct research and student training for the next generation of technology leaders in surveillance systems, so as to advance the body of knowledge in that field.

Surveillance abilities and situational awareness are needed to address societal needs of safety and security. Surveillance technology is used to provide our nation with both international and homeland security; situational awareness is necessary for disaster mitigation and management, and environmental monitoring. The key to addressing potential security and environmental threats is the effective use of sensors and sensor systems. While individual sensor technology is advancing, there is no mature theory for understanding composite surveillance systems. The challenge is to design quantitative tools that aid in designing optimal surveillance systems to achieve particular inference goals and to develop a theory for predicting surveillance performance.

There is an increasing need and urgency to train and educate qualified scientists and engineers who can become the next generation of thought leaders in the surveillance systems field. Surveillance theory is a broad, multidisciplinary topic that integrates ideas and techniques across several disciplines, including sensor phenomenology, signal and image processing, machine learning, sensor technology (e.g., radar, acoustic, chemical/biological, etc.), and human factors engineering..

Universities

Ohio State University
Wright State University

View Center Website

Center Personnel

Bob Myers
Center Staff
+1 937 545 0393
robert.a.myers@wright.edu

Lee Potter
Center Co-Director
+1 614 247 8672
potter@ece.osu.edu

Brian Rigling
Center Director
+1 937 775 5001
brian.rigling@wright.edu

Edmund Zelnio
IAB Chair
+1 937 255 5668
edmund.zelnio@us.af.mil

Research Focus

CSR's scientific research program addresses the breadth and depth of surveillance science. The core disciplines include sensor exploitation, signature prediction, computation, and functional baseline descriptions. Performance prediction and uncertainty characterization accompany every level (signal, feature, detection, localization, tracking, targeting, and intent). Thus, the performance bounds and information metrics are likewise relevant at each level.

Recent research topics include:

Advanced regression techniques for automatic target recognition (ATR) system-performance modeling.
Algorithms for efficient, wide-field-of-view synthetic aperture radar ground moving target indication (SAR GMTI).
Deep learning for cognitive radar.
Drone synthetic aperture radar (SAR).
Evaluating impact of trust in human-ATR interaction.
Generative models with visual attention for target tracking and reacquisition
The geo-aware mobility traffic simulation framework.
Knowledge-empowered real-time event-centric situational analysis.
Merging deep networks with algorithms for imaging inverse problems.
Processing of optimally constructed, noncontiguous radar transmission spectra.

Structured covariance matrix estimation with space-time adaptive processing applications.

Awards

1539961

I/UCRC Phase II: Collaborative Research: I/UCRC Center for Surveillance Research, Phase II

The Center for Surveillance Research (CSR) was founded in 2010 as a Phase I NSF I/UCRC. This award enables the Center to become a Phase 2 I/UCRC. Both founding sites of the Center, at Wright State University and at Ohio State University, will move to Phase 2. The main objective of CSR is to develop the theory and practice for modern surveillance. It has a healthy membership profile that has a mix of federal and industry members. In Phase 2, Wright State University seeks to become the Lead Site of the Center, as opposed to Phase 1 lead site of Ohio State. The fundamental intellectual issues addressed by the Center's continuing research portfolio have immediate application in application domains including medical imaging, transportation, and law enforcement. Further, the center will continue to host summer internship programs, in collaboration with the Air Force Minority Leaders Program and others, to attract participation by a diverse population of students. While use of sensor technology is pervasive in modern society, fundamental questions about the performance of sensor systems remain unaddressed. The inability to answer these questions, or even properly phrase the questions, impacts not only the development of sensors themselves, but also the development of data exploitation algorithms. Further, these unanswered questions are critical for eventually providing human users the ability to understanding the reliability of sensor performance under new and changing operating conditions. Specifically, sensors are developed under an assumed mode of use, and the exploitation algorithms are then left to extract whatever information the resultant sensor may afford, without that prior development having been properly informed by a realistic performance model. Moreover, the exploitation algorithms themselves are developed under presumed statistical models that may have varying degrees of agreement with actual sensor phenomenology, and these algorithms are then trained (e.g., to set operating parameters) based on a representative set of training measurements. However, the sensor community lacks any means to propagate mismatch between statistical assumptions and sensor phenomenology, or mismatch between training data and operational data, into the sensor algorithm or to even reliably predict a sensor's ultimate performance. Under Phase II, the Center for Surveillance Research will continue to address these shortcomings in existing sensor technology. Read More >

1539960