With today’s technology, radio frequency front-end architectures are very similar in radar and wireless communication systems. Further, in an effort to access more bandwidth, wireless systems have been shifting to frequency bands that have been traditionally occupied by radar systems. Given the hardware and frequency convergence, there is a lot of recent interest in the integration of the radar and communication functions in one system. Such integration will enable more efficient use of spectrum, reduce device size/cost and power consumption, and will also offer the potential for significant performance enhancement of both sensing and communication functions. Dual Function Radar-Communication (DFRC) systems is a class of integrated sensing-communication (ISC) systems that use the same waveform as well as the same hardware platform for both sensing and communication purposes. Thus, DFRC systems can achieve higher spectral efficiency than most ISC systems, require simpler transmitter hardware and a smaller, less expensive device. DFRC systems are prime candidates for autonomous driving vehicles, unmanned aerial vehicles, surveillance, search and rescue, and networked robots in advanced manufacturing applications that rely on censing and communications.

In the talk a novel DFRC system that uses the available bandwidth efficiently for both communication as well as sensing was presented. The system transmits wideband, orthogonal frequency division multiplexing (OFDM) waveforms and allows the transmit antennas to use subcarriers in a shared fashion. When all subcarriers are used in a shared fashion, the proposed system achieves high communication rate, while its sensing performance is limited by the size of the receive array. By reserving some subcarriers for exclusive use by transmit antennas (private subcarriers), the communication rate can be traded off for improved sensing performance. The improvement is achieved by using the private subcarriers to construct a large virtual array that yields higher resolution angle estimates. The system is endowed with beamforming capability, via waveform precoding, where the precoding matrix is optimally designed to meet a joint sensing-communication system performance metric. We also present novel hybrid analog-digital architectures for achieving good performance with reduced hardware and energy cost via the use of double-phase shifters.

Speaker Profile: Athina P. Petropulu is Distinguished Professor at the Electrical and Computer Engineering (ECE) Department at Rutgers, having served as chair of the department during 2010-2016. Prior to joining Rutgers she was a Professor of ECE at Drexel University (1992-2010). She held Visiting Scholar appointments at SUPELEC, Universite’ Paris Sud, Princeton University and University of Southern California. Dr. Petropulu’s research interests span the area of statistical signal processing, wireless communications, signal processing in networking, physical layer security, and radar signal processing. Her research has been funded by various government industry sponsors including the National Science Foundation (NSF), the Office of Naval research, the US Army, the National Institute of Health, the Whitaker Foundation, Lockheed Martin and Raytheon. Dr. Petropulu is Fellow of IEEE and the American Association for the Advancement of Science (AAAS), and recipient of the 1995 Presidential Faculty Fellow Award given by NSF and the White House. She is 2022 President of the IEEE Signal Processing Society (SPS) and 2020 President-Elect of IEEE SPS. She has served as Editor-in-Chief of the IEEE Transactions on Signal Processing (2009-2011) and IEEE Signal Processing Society Vice President-Conferences (2006-2008). She was General Chair of 2020 and 2021 IEEE SPS PROGRESS Workshops, General Co-Chair of the 2018 IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Kalamata Greece, and General Chair of the 2005 International Conference on Acoustics Speech and Signal Processing (ICASSP-05), Philadelphia PA. She was Distinguished Lecturer for the Signal Processing Society for 2017-2018, and is currently Distinguished Lecturer for the IEEE Aerospace & Electronics Systems Society. She is recipient of the 2012 IEEE Signal Processing Society Meritorious Service Award, and co-recipient of the 2005 IEEE Signal Processing Magazine Best Paper Award, the 2020 IEEE Signal Processing Society Young Author Best Paper Award (B. Li), the 2021 IEEE Signal Processing Society Young Author Best Paper Award (F. Liu), the 2021 Barry Carlton Best Paper Award by IEEE Aerospace and Electronic Systems Society, and the 2022 IEEE Sensor Array and Multichannel Signal Processing Workshop Best Student paper Award (Y. Li).

Over the past fifteen years, “cognition” has emerged as an enabling technology for incorporating learning and adaptivity on both transmit and receive to optimize or make more robust the radar performance in dynamic environments. The term ‘cognitive radar’ was coined in 2006, but the foundations of the cognitive systems date back several decades to research on knowledge-aided signal processing, and adaptive radar design. The main element of cognitive radar systems is the ‘perception-action cycle’, that is the feedback mechanism between receiver and transmitter that allows the radar system to learn information about a target and its environment and adapt its transmissions so as to optimize one or more missions, according to a desired goal. But a truly cognitive radar should not be only able to adapt on the fly its transmission waveforms and parameters based on internal fixed rules and on what learned about the environment, but it should also be able to optimize these rules learning with time from its mistakes, as some biological system does. And this is still a big challenge for radar experts.

This talk provided an overview of the main concept, of methods for modeling cognitive processes in a radar system and of some application example. Some insights into future directions of research were be provided as concluding remarks.

Speaker Profile : Maria Sabrina Greco graduated in Electronic Engineering in 1993 and received the Ph.D. degree in Telecommunication Engineering in 1998, from University of Pisa, Italy. Her general interests are in the areas of statistical signal processing, estimation and detection theory. In particular, her research interests include clutter models, coherent and incoherent detection in non-Gaussian clutter, CFAR techniques, bistatic/multi-static active and passive radars, cognitive radars and integrated sensing and communications. She co-authored many book chapters and more than 220 journal and conference papers.

From December 1997 to May 1998 she joined the Georgia Tech Research Institute, Atlanta, USA as a visiting research scholar where she carried on research activity in the field of radar detection in non-Gaussian background. In 1993 she joined the Dept. of Information Engineering of the University of Pisa, where she is Full Professor since 2017.

In May-June 2015 and in January-February 2018 she visited as invited Professor the Université Paris-Sud, CentraleSupélec, Paris, France.

She is an IEEE fellow since Jan. 2011. She was co-recipient of the 2001 and 2012 IEEE Aerospace and Electronic Systems Society’s Barry Carlton Awards for Best Paper published on the T-AES, co-recipient of 2019 EURASIP JASP Best Paper Award, co-recipient of the 2019 H Mimno Award for the best paper published on the AE Systems Magazine, recipient of the 2008 Fred Nathanson Young Engineer of the Year award for contributions to signal processing, estimation, and detection theory and of IEEE AESS Board of Governors Exceptional Service Award for “Exemplary Service and Dedication and Professionalism, as EiC of the IEEE AES Magazine”. She has been general-chair, technical program chair and organizing committee member of many international conferences over the last 15 years. She has been also lead-guest editor of many journal special issues on Radar Signal Processing. She is the Editor in Chief of the EURASIP Journal of Advances in Signal Processing (JASP) and Associate Editor of IET Proceedings – Sonar, Radar and Navigation. She’s has been member of the IEEE SPS BoG (2015-17), Chair of the IEEE AESS Radar Panel (2015-16), SPS Distinguished Lecturer for the years 2014-2015, AESS Distinguished Lecturer for the years 2015-2023, and AESS VP Publications (2018-2020), IEEE SPS Director-at-Large for Region 8 (2021-22). She is also a member of EURASIP Board of Directors and Chair of the SPS SAM Technical Committee.

She is now the President-Elect of IEEE AESS (2022-23) and will be President of IEEE AESS (2024-25).