Results 1 to 10 of about 2,277 (132)

Interference Analysis for mmWave Automotive Radar Considering Blockage Effect [PDF]

open access: yesSensors, 2021
Due to the increasing number of vehicles equipped with millimeter wave (mmWave) radars, interference among automotive radars is becoming a major issue. This paper explores the automotive radar interference in both two-lane and multi-lane scenarios using ...
Liping Kui, Sai Huang, Zhiyong Feng
doaj   +2 more sources

Automotive radar interference study for different radar waveform types

open access: yesIET Radar, Sonar & Navigation, 2022
Mutual interference between different radar waveforms used in automotive radar applications is studied. The existing interference analysis is extended to a generalised radar‐to‐radar interference equation that covers most of the common interference ...
Utku Kumbul   +3 more
doaj   +2 more sources

Deep Learning Based Image Enhancement for Automotive Radar Trained With an Advanced Virtual Sensor

open access: yesIEEE Access, 2022
This paper introduces a novel deep learning based concept for image enhancement and distortion suppression in automotive radar signal processing. The deep neural network (DNN) is trained solely on virtual data that is generated by an automotive MIMO ...
Christian SCHUsLER   +4 more
doaj   +3 more sources

Mounting Angle Prediction for Automotive Radar Using Complex-Valued Convolutional Neural Network [PDF]

open access: yesSensors
In advanced driver-assistance systems (ADASs), the misalignment of the mounting angle of the automotive radar significantly affects the accuracy of object detection and tracking, impacting system safety and performance.
Sunghoon Moon, Younglok Kim
doaj   +2 more sources

A Machine Learning Perspective on Automotive Radar Direction of Arrival Estimation

open access: yesIEEE Access, 2022
Millimeter-wave sensing using automotive radar imposes high requirements on the applied signal processing in order to obtain the necessary resolution for current imaging radar.
Jonas Fuchs   +4 more
doaj   +3 more sources

YOLO-Based Simultaneous Target Detection and Classification in Automotive FMCW Radar Systems

open access: yesSensors, 2020
This paper proposes a method to simultaneously detect and classify objects by using a deep learning model, specifically you only look once (YOLO), with pre-processed automotive radar signals.
Woosuk Kim   +4 more
doaj   +3 more sources

Estimating the Magnitude and Phase of Automotive Radar Signals Under Multiple Interference Sources With Fully Convolutional Networks

open access: yesIEEE Access, 2021
Radar sensors are gradually becoming a wide-spread equipment for road vehicles, playing a crucial role in autonomous driving and road safety. The broad adoption of radar sensors increases the chance of interference among sensors from different vehicles ...
Nicolae-Catalin Ristea   +2 more
doaj   +1 more source

Ground Reflection-Based Misalignment Detection of Automotive Radar Sensors

open access: yesIEEE Access, 2023
In this paper, we propose a method for detecting the misalignment of automotive radar sensors. Ensuring the accurate operation of automotive radar sensors is essential for the safety of drivers and passengers.
Chanul Park, Seongwook Lee
doaj   +1 more source

Overview of Signal Processing Techniques for Automotive Millimeter-wave Radar

open access: yesLeida xuebao, 2023
As one of the core components of Advanced Driver Assistance Systems (ADAS), automotive millimeter-wave radar has become the focus of scholars and manufacturers at home and abroad because it has the advantages of all-day and all-weather operation ...
Yan HUANG   +15 more
doaj   +1 more source

Home - About - Disclaimer - Privacy