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DTSTART:20180311T030000
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BEGIN:VEVENT
DTSTAMP:20171030T185806Z
UID:694C1B41-A221-11E7-8752-0050568D2FB3
DTSTART;TZID=US/Pacific:20171128T183000
DTEND;TZID=US/Pacific:20171128T200000
DESCRIPTION:Radar not only has found widespread application in advanced dri
 ver assistance systems (ADAS) but also is one of the key technologies to e
 nable environmental perception in autonomous driving. Compared with LiDAR 
 and camera\, radar technology provides reliable measurements of range\, ve
 locity and angle information of obstacles surrounding vehicle in all kinds
  of weather conditions. Unlike the traditional phased-array radar system w
 hich transmits via its antenna array a single waveform with different phas
 e shift\, multiple-input multiple-output (MIMO) radar can transmit multipl
 e waveforms that may be chosen freely. As compared to traditional radar sy
 stem with the same number of transmit and receive antennas\, MIMO radar ac
 hieves significantly improved spatial resolution by exploiting waveform di
 versity. Due to its advantages\, MIMO radar technology has been widely use
 d in designing millimeter-wave radar sensors for ADAS and self-driving car
 s.\n\nThe Part I talk will focus on the fundamentals of MIMO radar as well
  as novel MIMO radar approaches with the emerging sparse sensing technique
 s. This talk will cover the radar basics\, MIMO radar architecture and wav
 eform design\, sparse sensing methods in MIMO radar including compressive 
 sensing (CS) based MIMO radar as well as novel MIMO radar approach using m
 atrix completion (MC).\n\nThe Part II talk will focus on the role of radar
  in autonomous driving and various aspects of automotive radar signal proc
 essing techniques. This talk will cover the radar system requirements and 
 architecture for autonomous driving\, principles of frequency-modulated co
 ntinuous-wave (FMCW) radar\, high resolution angle finding methods\, “sm
 art” radar sensors with machine learning\, as well as unique problems as
 sociated with automotive radars for autonomous driving such as pedestrian 
 detection.\n\nCo-sponsored by: Cristian Cismaru\n\nSpeaker(s): Dr. Shunqia
 o Sun\, \, Dr. Shunqiao Sun\, \n\nAgenda: \n6:30-7:00pm Gather and Pizza/R
 efreshments\n\n7:00-8:00pm Presentation\n\nBldg: 889\, Skyworks Solutions\
 , Inc.\, 649 Lawrence Drive\, Newbury Park\, California\, United States\, 
 91320
LOCATION:Bldg: 889\, Skyworks Solutions\, Inc.\, 649 Lawrence Drive\, Newbu
 ry Park\, California\, United States\, 91320
ORGANIZER:ccismaru@ieee.org
SEQUENCE:7
SUMMARY:MIMO Radar: Fundamentals\, Sparse Sensing and its Application in Au
 tonomous Driving (Part II)
URL;VALUE=URI:https://events.vtools.ieee.org/m/47265
X-ALT-DESC:Description: <br /><p><span style="font-size: 10pt\;">Radar not 
 only has found widespread application in advanced driver assistance system
 s (ADAS) but also is one of the key technologies to enable environmental p
 erception in autonomous driving. Compared with LiDAR and camera\, radar te
 chnology provides reliable measurements of range\, velocity and angle info
 rmation of obstacles surrounding vehicle in all kinds of weather condition
 s. Unlike the traditional phased-array radar system which transmits via it
 s antenna array a single waveform with different phase shift\, multiple-in
 put multiple-output (MIMO) radar can transmit multiple waveforms that may 
 be chosen freely. As compared to traditional radar system with the same nu
 mber of transmit and receive antennas\, MIMO radar achieves significantly 
 improved spatial resolution by exploiting waveform diversity. Due to its a
 dvantages\, MIMO radar technology has been widely used in designing millim
 eter-wave radar sensors for ADAS and self-driving cars.</span></p>\n<p><sp
 an style="font-size: 10pt\;">The Part I talk will focus on the fundamental
 s of MIMO radar as well as novel MIMO radar approaches with the emerging s
 parse sensing techniques. This talk will cover the radar basics\, MIMO rad
 ar architecture and waveform design\, sparse sensing methods in MIMO radar
  including compressive sensing (CS) based MIMO radar as well as novel MIMO
  radar approach using matrix completion (MC).</span></p>\n<p><span style="
 font-size: 10pt\;">The Part II talk will focus on the role of radar in aut
 onomous driving and various aspects of automotive radar signal processing 
 techniques. This talk will cover the radar system requirements and archite
 cture for autonomous driving\, principles of frequency-modulated continuou
 s-wave (FMCW) radar\, high resolution angle finding methods\, &ldquo\;smar
 t&rdquo\; radar sensors with machine learning\, as well as unique problems
  associated with automotive radars for autonomous driving such as pedestri
 an detection.</span></p><br /><br />Agenda: <br /><p>6:30-7:00pm Gather an
 d Pizza/Refreshments</p>\n<p>&nbsp\;</p>\n<p>7:00-8:00pm Presentation</p>\
 n<p>&nbsp\;</p>
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