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Automotive Radar Optimization Design in a Spectrally Crowded V2I Communication Environment

IEEE transactions on intelligent transportation systems (Print), 2023
A main challenge for radar-aided millimeter wave (mmWave) vehicle-to-infrastructure (V2I) communication application, is that it requires mitigating the mutual interference between vehicular radar and communication operating at same frequency bands.
Yu Yao   +5 more
semanticscholar   +1 more source

Deep-Neural-Network-Enabled Vehicle Detection Using High-Resolution Automotive Radar Imaging

IEEE Transactions on Aerospace and Electronic Systems, 2023
Advanced driver assistance systems (ADASs) and autonomous vehicles rely on different types of sensors, such as camera, radar, ultrasonic, and LiDAR, to sense the surrounding environment.
Ru-dan Zheng   +3 more
semanticscholar   +1 more source

Channel Measurement and Ray-Tracing Simulation for 77 GHz Automotive Radar

IEEE transactions on intelligent transportation systems (Print), 2023
Millimeter-wave automotive radar is essential for realizing autonomous driving. Realistic channel model and simulation are important for system and sensing algorithm design.
Danping He   +6 more
semanticscholar   +1 more source

Periodic Asymmetric Trapezoidal Perturbation Microstrip Antenna for Millimeter-Wave Automotive Radar Sensors

IEEE Transactions on Antennas and Propagation, 2023
This article presents a new design and experimental verification of a broadband wide-beam microstrip array antenna for short-range automotive radar sensors. The antenna is designed based on a pure microstrip transmission line, by inserting short inverted
Hao Yi   +4 more
semanticscholar   +1 more source

Performance Analysis of Uncoordinated Interference Mitigation for Automotive Radar

IEEE Transactions on Vehicular Technology, 2023
As a key sensor for Advanced Driving Assistance System (ADAS), millimeter automotive radar has been a promising candidate for fulfilling tasks including adaptive cruise control and collision avoidance.
Yi Wang   +5 more
semanticscholar   +1 more source

Cross-Modal Supervision-Based Multitask Learning With Automotive Radar Raw Data

IEEE Transactions on Intelligent Vehicles, 2023
With the rapid development of autonomous driving technology, radar sensors play a vital role in the perception system due to their robustness under harsh environmental conditions, exact range and velocity perception capability.
Yi Jin   +3 more
semanticscholar   +1 more source

Performance Analysis of Coordinated Interference Mitigation Approach for Automotive Radar

IEEE Internet of Things Journal, 2023
Millimeter automotive radar has great potential in advanced driver assistance systems (ADASs) to enable safety features, such as adaptive cruise control and collision avoidance.
Yi Wang   +4 more
semanticscholar   +1 more source

Detection of Ghost Targets for Automotive Radar in the Presence of Multipath

IEEE Transactions on Signal Processing, 2023
Colocated multiple-input multiple-output (MIMO) technology has been widely used in automotive radars as it provides accurate angular estimation of the objects with a relatively small number of transmitting and receiving antennas.
Le Zhen   +4 more
semanticscholar   +1 more source

Automotive Radar Signal Processing: Research Directions and Practical Challenges

IEEE Journal on Selected Topics in Signal Processing, 2021
Automotive radar is used in many applications of advanced driver assistance systems and is considered as one of the key technologies for highly automated driving.
Florian Engels   +5 more
semanticscholar   +1 more source

Road Surface Conditions Identification via H α A Decomposition and Its Application to mm-Wave Automotive Radar

IEEE Transactions on Radar Systems, 2023
A novel approach based on the entropy-alpha-anisotropy decomposition, also known as the $H\alpha A$ decomposition, for the recognition of road surface conditions using automotive radar is presented.
Wietse Bouwmeester   +2 more
semanticscholar   +1 more source

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