000 01803naaaa2200361uu 4500
001 https://directory.doabooks.org/handle/20.500.12854/56494
005 20220219202212.0
020 _aKSP/1000090003
020 _a9783731508885
024 7 _a10.5445/KSP/1000090003
_cdoi
041 0 _aEnglish
042 _adc
100 1 _aVisentin, Tristan
_4auth
245 1 0 _aPolarimetric Radar for Automotive Applications
260 _bKIT Scientific Publishing
_c2019
300 _a1 electronic resource (IX, 159 p. p.)
506 0 _aOpen Access
_2star
_fUnrestricted online access
520 _aCurrent automotive radar sensors prove to be a weather robust and low-cost solution, but are suffering from low resolution and are not capable of classifying detected targets. However, for future applications like autonomous driving, such features are becoming ever increasingly important. On the basis of successful state-of-the-art applications, this work presents the first in-depth analysis and ground-breaking, novel results of polarimetric millimeter wave radars for automotive applications.
540 _aCreative Commons
_fhttps://creativecommons.org/licenses/by-sa/4.0/
_2cc
_4https://creativecommons.org/licenses/by-sa/4.0/
546 _aEnglish
653 _aMachine-Learning
653 _aMillimeter-Wave Radar
653 _aAutomotive Radar
653 _aPolarimetric Radar
653 _aTarget Classification
653 _aPolarimetrie
653 _aMillimeterwellen-Radar
653 _aObjekterkennung
653 _aKI
653 _aAutomotive-Radar
856 4 0 _awww.oapen.org
_uhttps://www.ksp.kit.edu/9783731508885
_70
_zDOAB: download the publication
856 4 0 _awww.oapen.org
_uhttps://directory.doabooks.org/handle/20.500.12854/56494
_70
_zDOAB: description of the publication
999 _c41501
_d41501