Distinguished Lecturer: Professor Markus Gardill

The IEEE Northern Canada Section Antennas & Propagation Society and the Microwave Theory & Techniques Society (IEEE NCS APS/MTTS) joint chapter would like to invite you to attend the next installment of our invited talks.  Professor Markus Gardill, University of Würzburg, Germany, will be giving a presentation titled “Automotive Radar – A Signal Processing Perspective on Current Technology and Future Systems

Where: ETLC Solarium, University of Alberta
When: 3-March-2020, 12:00PM to 01:00PM

A small memorial will take place before the talk to honour the tragic loss of our friends and colleagues Professor Mojgan Daneshmand (co-founder and co-chair of this Chapter) and Professor Pedram Mousavi (vice-chair).

Where: ETLC Solarium, University of Alberta
When: 3-March-2020, 11:30PM to 12:00PM

Abstract

Radar systems are a key technology of modern vehicle safety & comfort systems. Without doubt it will only be the symbiosis of Radar, Lidar and camera-based sensor systems which can enable advanced autonomous driving functions soon. This presentation will introduce the topic with a review on the fundamentals of FMCW radar and then dive into the details of fast-chirp FMCW processing. Starting with the fundamentals of target range and velocity estimation based on the radar data matrix, the spatial dimension available using modern single-input multiple-output (SIMO) and multiple-input multiple-output (MIMO) radar systems will be introduced and radar processing based on the radar data cube is discussed. Of interest is the topic of angular resolution – one of the key drawbacks which e.g. render Lidar systems superior to radar in some situations. Consequently, traditional and modern methods for direction of arrival estimation in FMCW radar systems are presented. The talk concludes with an outlook on future system aspects such as application of neural networks or over-the-air de-ramping.

About the Speaker:

Markus Gardill is professor for Satellite Communication Systems at the chair of computer science VII – robotics and telematics at the university of Würzburg.
He received the Dipl.-Ing. and Dr.-Ing. degree in systems of information and multimedia technology/electrical engineering from the Friedrich-Alexander-University Erlangen-Nürnberg, Germany, in 2010 and 2015, respectively, where he was a research assistant, teaching fellow, and later head of the team for radio communication technology.

Between 2015 and 2020 he was R&D engineer and research cluster owner for optical and imaging metrology systems at Robert Bosch GmbH. Later he joined InnoSenT GmbH as head of the group radar signal processing & tracking, developing together with his team new generations of automotive radar sensors for advanced driver assistance systems and autnomous driving.

His main research interest include radar and communication systems, antenna (array) design, and signal processing algorithms.
His particular interest is space-time processing such as e.g. beamforming and direction-of-arrival estimation, together with cognitive and adaptive systems. He has a special focus on combining the domains of signal processing and microwave/electromagnetics to develop new approaches on antenna array implementation and array signal processing. His further research activities include distributed coherent/non-coherent networks for advanced detection and perception, machine-learning techniques for spatial signal processing, highly-flexible software defined radio/radar systems, and communication systems for NewSpace.

Markus Gardill is member of the IEEE Microwave Theory and Techniques Society (IEEE MTT-S).
He served as co-chair of the IEEE MTT-S Technical Committee Digital Signal Processing (MTT-9), regularly acts as reviewer and TPRC member for several journals and conferences, and currently serves as associate editor of the Transactions on Microwave Theory and Techniques. He is a Distinguished Microwave Lecturer (DML) for the DML term 2018-2020 with a presentation on signal processing and system aspects of automotive radar systems.