- Friday, 21 June 2019
- EWI Van der Poelzaal
Misspecification, Robustness and Cognition in Radar Signal Processing: Some ResultsProf. Dr. Maria Sabrina Greco
Dept. of Information Engineering of the University of Pisa
After a brief survey of the activities of the Radar Signal Processing Group of the Dept. of Information Engineering, University of Pisa, the talk will focus on some of the recent and on-going research topics in which Prof. Greco is involved.
Any scientific experiment which aims to gain some knowledge about a real-word phenomenon, in radar systems as in other applications, starts with the data collection. In statistical signal processing, all the available knowledge about a physical phenomenon of interest is summarized in the probability density function (pdf) of the collected observations. In practice, the pdf or/and its characteristic parameters are partly or fully unknown, then any inference procedure starts with its estimation. The easy case is when the hypothesized statistical model and the true one are the same, so they are matched. However, a certain amount of mismatch is often inevitable in practice. The reasons for a model misspecification can be various: it may be due to an imperfect knowledge of the true data model or to the need to fulfill some operative constraints on the estimation algorithm (processing time, simple hardware implementation, and so on).
The first part of the talk aims at providing a short overview on the misspecified estimation framework with a particular focus on the Misspecified Cramér-Rao bound (MCRB). Then a possible approach to minimize the misspecification risk is presented. Specifically, a more general semiparametric characterization of the statistical behavior of the collected data is addressed and some application to the radar scenario is shown.
The talk will then continue with a short introduction to the concept of cognition applied to passive and active radars highlighting the limits and the path forward and will describe some new results regarding the application of some machine learning techniques to “cognitive” MIMO radar.
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. 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. She’s IEEE fellow since Jan. 2011 and she was co-recipient of the 2001 and 2012 IEEE Aerospace and Electronic Systems Society’s Barry Carlton Awards for Best Paper and recipient of the 2008 Fred Nathanson Young Engineer of the Year award for contributions to signal processing, estimation, and detection theory. In May-June 2015 and in January-February 2018 she visited as invited Professor the Université Paris-Sud, CentraleSupélec, Paris, France.
She has been general-chair, technical program chair and organizing committee member of many international conferences over the last 10 years. She has been guest editor of the special issue on “Machine Learning for Cognition in Radio Communications and Radar” of the IEEE Journal on Special Topics of Signal Processing, lead guest editor of the special issue on "Advanced Signal Processing for Radar Applications" of the IEEE Journal on Special Topics of Signal Processing, December 2015, guest co-editor of the special issue of the Journal of the IEEE Signal Processing Society on Special Topics in Signal Processing on "Adaptive Waveform Design for Agile Sensing and Communication," published in June 2007 and lead guest editor of the special issue of International Journal of Navigation and Observation on” Modelling and Processing of Radar Signals for Earth Observation published in August 2008. She’s Associate Editor of IET Proceedings – Sonar, Radar and Navigation, member of the Editorial Board of the Springer Journal of Advances in Signal Processing (JASP), and Senior area chair of the IEEE Transactions on Signal Processing. She’s member of the IEEE AESS Board of Governors and has been member of the IEEE SPS BoG (2015-17) and Chair of the IEEE AESS Radar Panel (2015-16). She has been as well SPS Distinguished Lecturer for the years 2014-2015, and now she's AESS Distinguished Lecturer for the years 2015-2019, and AESS VP Publications.
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, radar waveform diversity and bistatic/mustistatic active and passive radars, cognitive radars. She co-authored many book chapters and more than 190 journal and conference papers.
- Tue, 19 Nov 2019
- Aula Senaatszaal
PhD Thesis Defence
Capacitively-Coupled Bridge Readout Circuits
This Ph.D. dissertation describes the design and realization of energy efficient readout integrated circuits (ROICs), that have an input referred noise density < 5 nV/√Hz and a linearity of < 30 ppm, as required by Wheatstone bridge sensors used in precision mechatronic systems. Novel techniques were developed, at both the system-level and circuit-level, to improve the ROIC’s energy-efficiency, while preserving its stability and precision. Two prototypes are presented, each with best-in-class energy efficiency, to demonstrate the effectiveness of the proposed techniques.
- Fri, 17 Jan 2020
- Aula Senaatszaal
PhD Thesis Defence
3D Elements for Phased-Array Systems: Analysis and Design.
Phased arrays for radar and communication systems require supporting frequency and angular selectivity functions to reduce interference and enable more flexible operation. Frequency selective surfaces with large rejection bands and their integration with phased arrays are investigated. Moreover, array of tilted dipole elements are proposed to achieve radiation with asymmetric field of view.