Results 31 to 40 of about 662,591 (288)
CARRADA Dataset: Camera and Automotive Radar with Range-Angle-Doppler Annotations
, 2021 High quality perception is essential for autonomous driving (AD) systems. To reach the accuracy and robustness that are required by such systems, several types of sensors must be combined. Currently, mostly cameras and laser scanners (lidar) are deployed
Newson, A. +4 more
core +2 more sources
CNN‐based estimation of heading direction of vehicle using automotive radar sensor
IET Radar, Sonar & Navigation, 2021 Modern autonomous vehicles are being equipped with various automotive sensors to perform special functions. Especially, it is important to predict the heading direction of the front vehicle to adjust the speed of the ego‐vehicle and select appropriate ...
Sohee Lim +4 more
doaj +1 more source
People Walking Classification Using Automotive Radar [PDF]
Electronics, 2020 Automotive radars are able to guarantee high performances at the expenses of a relatively low cost, and recently their application has been extended to several fields in addition to the original one. In this paper we consider the use of this kind of radars to discriminate different types of people’s movements in a real context.
Linda Senigagliesi +3 more
openaire +1 more source
Extrapolation-RELAX Estimator Based on Spectrum Partitioning for DOA Estimation of FMCW Radar
IEEE Access, 2019 This paper proposes an extrapolation-RELAX estimator based on spectrum partitioning (SP) for the direction of arrival (DOA) estimation of frequency-modulated continuous-wave (FMCW) radar.
Sangdong Kim +3 more
doaj +1 more source
IEEE Transactions on Aerospace and Electronic Systems, 2022 Range/Doppler migration and velocity ambiguity are two well-known problems encountered in high-speed moving target detection using a linear-frequency-modulated continuous-wave automotive radar.
Luzhou Xu, J. Lien, Jian Li
semanticscholar +1 more source
Practical classification of different moving targets using automotive radar and deep neural networks [PDF]
, 2018 In this work, the authors present results for classification of different classes of targets (car, single and multiple people, bicycle) using automotive radar data and different neural networks.
Angelov, Aleksandar +3 more
core +1 more source
The Journal of Engineering, 2019 Modern radar applications, such as automotive, integration of radar and communications, have become an important requirement. Systems able to provide joint radar and communications would exploit the same hardware while providing enhanced capabilities to ...
Pasquale Striano +3 more
doaj +1 more source
Coherent Automotive Radar Networks: The Next Generation of Radar-Based Imaging and Mapping
IEEE Journal of Microwaves, 2021 Imaging radar is a key perception technology for automotive and industrial applications. A lot of progress has been made with high channel count systems, deploying, for example, 12 transmit and 16 receive channels with cascaded monolithic microwave ...
Michael Gottinger +6 more
semanticscholar +1 more source
Mitigation of automotive radar interference
2018 IEEE Radar Conference (RadarConf18), 2018 This paper presents a new approach to mitigating radar interference and focuses on the application of automotive radar. Traditional interference mitigation techniques in automotive radar depend on detection and identification of the interference. With this paper, we propose a novel method based on advanced signal separation techniques which do not need
Uysal, Faruk (author) +1 more
openaire +3 more sources
Object detection for automotive radar point clouds – a comparison
AI Perspectives, 2021 Automotive radar perception is an integral part of automated driving systems. Radar sensors benefit from their excellent robustness against adverse weather conditions such as snow, fog, or heavy rain.
Nicolas Scheiner +4 more
semanticscholar +1 more source