Villanova University was founded in 1842 by the Order of Saint Augustine. To this day, Villanova’s Augustinian Catholic intellectual tradition is the cornerstone of an academic community in which students learn to think critically, act compassionately and succeed while serving others. Villanova prepares students to become ethical leaders who create positive change everywhere life takes them.


The strength of the Villanova experience comes in part from the University’s welcoming community. All members are bonded together by a shared responsibility to uphold the ideals of Saint Augustine and let the principles of truth, unity and love guide their lives. The Villanova community helps students grow intellectually, professionally and spiritually, and challenges them to reach their full potential.


The University’s rigorous academic experience, rooted in the liberal arts, forms an environment in which students and professors are partners in learning. The Villanova community is dedicated to providing a personalized experience that fosters every student’s intellectual and spiritual well-being. As part of their education, students are encouraged to enrich their own lives by working for those in need. Through academic and service programs, students use their knowledge, skills and compassion to better the world around them.


There are more than 10,000 undergraduate, graduate and law students in the University’s six colleges—the College of Liberal Arts and Sciences, the Villanova School of Business, the College of Engineering, the College of Nursing, the College of Professional Studies and the Villanova University Charles Widger School of Law. These colleges are the setting for an experience that develops both the heart and the mind, and creates the atmosphere where students are called to ignite change.


Villanova University is located in a suburban community 12 miles west of Philadelphia, Pa.

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The IEEE Dennis J. Picard Medal for Radar Technologies and Applications was established in 1999, in honor of Dennis J. Picard. Dr. Amin was recognized for his contributions to radar signal processing across a wide range of applications including through-the-wall imaging and health monitoring.

2022 IEEE Picard Gold Medal in Radar Technologies and Applications

The Fulbright Distinguished Chair Awards comprise approximately 40 distinguished lecturing, research and lecturing/research awards that range from three to 12 month tenures. Dr. Amin’s Fulbright Distinguished Chair appointment is to the Defense Science and Technology Group (DSTG), Australia.

2017 Fulbright Distinguished Chair in Advanced Defense Science and Technology

The Alexander von Humboldt Prize is sponsored by the Alexander von Humboldt Foundation. This international honor recognizes the lifetime achievements of researchers whose fundamental discoveries and new theories and insights have had a significant impact on their discipline, and who are “expected to continue producing cutting-edge achievements" in the future. Dr. Amin will spend a period of six months from 2016 to 2019 at the Technical University of Darmstadt.

2016 Alexander von Humboldt Prize

The Institution of Engineering and Technology (IET) Achievement Medals are awarded to individuals who have made major and distinguished contributions in the various sectors of science, engineering and technology, covering energy, transport, manufacturing, information and communications and the built environment. Dr. Amin’s award reflects his outstanding achievements and seminal contributions to signal analysis and processing over the past three decades.

2016 IET Achievement Medal

This award, given by the Institute of Electrical and Electronic Engineers, Signal Processing Society, honors a person who, over a period of years, has made outstanding technical contributions to theory and/or practice in technical areas within the scope of the Society. Dr. Amin’s award citation is for "fundamental contributions to signal processing algorithms for communications, satellite navigations and radar imaging."

2014 IEEE Signal Processing Society Technical Achievement Award

The European Association of Signal Processing grants the Technical Achievement Award to a scientist who has made significant research contributions in Signal Processing Theory and Applications. Dr. Amin’s citation is for  "contributions to radar imaging and interference mitigation in communications and navigation systems.”

2009 EURASP Individual Technical Achievement Award

Member of the Board of the Proceedings for the Institute of Electrical and Electronics Engineers

Sensing, Tracking, and Recognition of Macro–Micro Hand Gestures Using Interferometric MIMO Radar

Radar Based Joint Human Activity and Agility Recognition via Multi Input Multi Task Learning

Automatic Arm Motion Recognition Based on Radar Micro-Doppler Signature Envelopes

Through-the-wall radar imaging (TWRI) allows police, fire and rescue personnel, first responders, and defense forces to detect, identify, classify, and track the whereabouts of humans and moving objects. Electromagnetic waves are considered the most effective at achieving this objective, yet advances in this multi-faceted and multi-disciplinary technology require taking phenomenological issues into consideration and must be based on a solid understanding of the intricacies of EM wave interactions with interior and exterior objects and structures. Providing a broad overview of the myriad factors involved, namely size, weight, mobility, acquisition time, aperture distribution, power, bandwidth, standoff distance, and, most importantly, reliable performance and delivery of accurate information, Through-the-Wall Radar Imaging examines this technology from the algorithmic, modeling, experimentation, and system design perspectives. It begins with coverage of the electromagnetic properties of walls and building materials, and discusses techniques in the design of antenna elements and array configurations, beamforming concepts and issues, and the use of antenna array with collocated and distributed apertures.  Detailed chapters discuss several suitable waveforms inverse scattering approaches and revolve around the relevance of physical-based model approaches in TWRI along with theoretical and experimental research in 3D building tomography using microwave remote sensing, high-frequency asymptotic modeling methods, synthetic aperture radar (SAR) techniques, impulse radars, airborne radar imaging of multi-floor buildings strategies for target detection, and detection of concealed targets. The book concludes with a discussion of how the Doppler principle can be used to measure motion at a very fine level of detail. The book provides a deep understanding of the challenges of TWRI, stressing its multidisciplinary and phenomenological nature. The breadth and depth of topics covered presents a highly detailed treatment of this potentially life-saving technology. 

Through-the-Wall Radar Imaging

With the emergence of compressive sensing and sparse signal reconstruction, approaches to urban radar have shifted toward relaxed constraints on signal sampling schemes in time and space, and to effectively address logistic difficulties in data acquisition. Traditionally, these challenges have hindered high resolution imaging by restricting both bandwidth and aperture, and by imposing uniformity and bounds on sampling rates. Compressive Sensing for Urban Radar is the first book to focus on a hybrid of two key areas: compressive sensing and urban sensing. It explains how reliable imaging, tracking, and localization of indoor targets can be achieved using compressed observations that amount to a tiny percentage of the entire data volume. Capturing the latest and most important advances in the field, this state-of-the-art text:   Covers both ground-based and airborne synthetic aperture radar (SAR) and uses different signal waveforms Demonstrates successful applications of compressive sensing for target detection and revealing building interiors  Describes problems facing urban radar and highlights sparse reconstruction techniques applicable to urban environments Deals with both stationary and moving indoor targets in the presence of wall clutter and multipath exploitation Provides numerous supporting examples using real data and computational electromagnetic modeling   Featuring 13 chapters written by leading researchers and experts, Compressive Sensing for Urban Radar is a useful and authoritative reference for radar engineers and defense contractors, as well as a seminal work for graduate students and academia.

Compressive Sensing for Urban Radar

This book aims to capture recent advances and breakthroughs in in-home radar monitoring of human motions and activities. It addresses three key attributes of radar for in-door human monitoring, namely: motion classification including fall, detection of vital signs, and categorization of human gait for risk assessment and progression of physical impairments and disabilities. It explores recent developments in radar technology for human monitoring inside homes and residences. The reader will learn enhanced detection and classification techniques of radar signals associated with human micro- and macro-motions. Furthermore, the book includes examples using real data collected from healthy individuals, patients, and retirement communities based on the subject Doppler and range information, and using different single and multi-antenna radar system configurations. Results are also presented using modeled data based on biomechanics and kinematics. Indoor monitoring is further demonstrated using alternative technologies of infrared sensors and RF signals of opportunities.

Radar for In-Door Monitoring: Detection, Classification, and Assessment

Dr. Amin is an internationally recognized expert who has made major contributions to the advances of the theory of signal and array processing with applications to radar, sonar, communications, satellite navigations, ultrasound, healthcare and RFID. He is the leading expert on through-the-wall radar imaging, which could have applications for search and rescue and law enforcement. Innovations generated by the Center for Advanced Communications have important functions in both industry and government. The holder of two U.S. patents, Dr. Amin has over 750 journal and conference publications in the areas of wireless communication, time-frequency analysis, smart antennas, interference cancellation in broadband communication platforms, anti-jam GPS, compressive sensing, target detection, classification, localization and tracking, multiple-input/multiple-output radar and communications and frequency spectrum sharing and co-existence. Dr. Amin is a fellow of four societies and recipient of three technical achievement awards.

Array Signal Processing

Machine Learning

Radar Imaging

Radar

Satellite Navigations

Smart Antennas

Sonar    

Surveillance                                                                                

Wireless Communications

Villanova University Center for Advanced Communications

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Keeping the Elderly Safe with RADAR: Technology Could Help Track Breathing, Heart Rates and Accidents

New Technologies to Help Seniors Age in Place

Who Will Watch You Fall? A Radar Detection Program for the Elderly

Professor of Electrical and Computer Engineering; Director of the Center for Advanced Communications | Villanova College of Engineering

Examining the Use of Through-the-Wall Radar Imaging to Assist the Elderly Living Alone

The United States is facing a great challenge as the number of aging Americans is rapidly rising. Right now, 40 million Americans are over the age of 65, and the Census Bureau predicts that by the year 2030, 80 million Americans will be 65 or older. Due to these rising statistics, families, communities and health care providers are at a cross-road in terms of how to best serve this growing aging population. 
Many elderly individuals choose to live alone, which poses a great risk as falls and other ailments become more likely as a person ages. In order to increase the safety and security of an elderly person living alone, researchers at Villanova University are examining the use of through-the-wall radar technology to detect falls and monitor the elderly in their individual living spaces. 
Dr. Moeness Amin, Director of the Center for Advanced Communications in the College of Engineering at Villanova University, is the Principal Investigator for this project. An internationally recognized expert in the area of radar imaging, Dr. Amin's research focuses on various applications for this technology, including search and rescue, defense, and law enforcement.  He has edited two books on the subject and written more than 150 articles related to radar signal processing and imaging methods. 
Dr. Amin and his team, through a grant from Qatar University, are now developing a series of algorithms to identify the patterns and routines of an elderly person in his or her home. The radar, with the help of these algorithms, can detect when a person is sitting, standing, walking, etc., and when a person is at risk for injury. Elderly motion detection and classification can be achieved in all rooms inside the home with one or few radar units, utilizing the radar capability of "seeing" through walls.  
Graduate students in the College of Engineering were trained in walking, falling, and functioning like an elderly person and experiments were conducted in the radar-imaging lab on Villanova's campus. Kelly Nestor, MSN, ANP-BC, a clinical instructor in Villanova's College of Nursing and an expert in the growing elderly population, educated and trained the students on how the elderly carry themselves and walk -- with or without the assistance of canes or walkers.

Examining the Use of Through-the-Wall Radar Imaging to Assist the Elderly Living Alone

Engineering professor Moeness Amin discusses winning the Humboldt Prize for his radar signal processing research with KYW Newsradio.

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