TY - JOUR
T1 - MIMO Radar for Advanced Driver-Assistance Systems and Autonomous Driving
T2 - Advantages and Challenges
AU - Sun, Shunqiao
AU - Petropulu, Athina P.
AU - Poor, H. Vincent
N1 - Funding Information:
Athina P. Petropulu (athinap@rutgers.edu) received her B.S. degree from the National Technical University of Athens, Greece, and her M.S. and Ph.D. degrees from Northeastern University, Boston, all in electrical and computer engineering. She is a distinguished professor in the Department of Electrical and Computer Engineering, Rutgers University, New Jersey, which she chaired from 2010 to 2016. Her research interests include statistical signal processing, wireless communications, signal processing in networking, physicallayer security, and radar signal processing. She received the 1995 Presidential Faculty Fellow Award from the National Science Foundation and the White House. In 2005, she received the IEEE Signal Processing Magazine Best Paper Award, and in 2012, the IEEE Signal Processing Society Meritorious Service Award for exemplary service in technical leadership capacities. She is the presidentelect of the IEEE Signal Processing Society and a Fellow of the IEEE.
Publisher Copyright:
© 1991-2012 IEEE.
PY - 2020/7
Y1 - 2020/7
N2 - Important requirements for automotive radar are high resolution, low hardware cost, and small size. Multiple-input, multiple-output (MIMO) radar technology has been receiving considerable attention from automotive radar manufacturers because it can achieve a high angular resolution with relatively small numbers of antennas. For that ability, it has been exploited in the current-generation automotive radar for advanced driverassistance systems (ADAS) as well as in next-generation highresolution imaging radar for autonomous driving. This article reviews MIMO radar basics, highlighting the features that make this technology a good fit for automotive radar and reviewing important theoretical results for increasing the angular resolution. The article also describes challenges arising during the application of existing MIMO radar theory to automotive radar that provide interesting problems for signal processing researchers.
AB - Important requirements for automotive radar are high resolution, low hardware cost, and small size. Multiple-input, multiple-output (MIMO) radar technology has been receiving considerable attention from automotive radar manufacturers because it can achieve a high angular resolution with relatively small numbers of antennas. For that ability, it has been exploited in the current-generation automotive radar for advanced driverassistance systems (ADAS) as well as in next-generation highresolution imaging radar for autonomous driving. This article reviews MIMO radar basics, highlighting the features that make this technology a good fit for automotive radar and reviewing important theoretical results for increasing the angular resolution. The article also describes challenges arising during the application of existing MIMO radar theory to automotive radar that provide interesting problems for signal processing researchers.
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U2 - 10.1109/MSP.2020.2978507
DO - 10.1109/MSP.2020.2978507
M3 - Article
AN - SCOPUS:85087912380
SN - 1053-5888
VL - 37
SP - 98
EP - 117
JO - IEEE Signal Processing Magazine
JF - IEEE Signal Processing Magazine
IS - 4
M1 - 9127853
ER -