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IEEE Transactions on Radar Systems, 2023
Deep learning methods have triggered significant progress in automotive radar-based object detection and classification. However, with an increasing number of radar sensors on the road, mutual interference is unavoidable since these sensors share the ...
Shengyi Chen +5 more
semanticscholar +1 more source
Deep learning methods have triggered significant progress in automotive radar-based object detection and classification. However, with an increasing number of radar sensors on the road, mutual interference is unavoidable since these sensors share the ...
Shengyi Chen +5 more
semanticscholar +1 more source
4D Automotive Radar Sensing for Autonomous Vehicles: A Sparsity-Oriented Approach
IEEE Journal on Selected Topics in Signal Processing, 2021We propose a high-resolution imaging radar system to enable high-fidelity four-dimensional (4D) sensing for autonomous driving, i.e., range, Doppler, azimuth, and elevation, through a joint sparsity design in frequency spectrum and array configurations ...
Shunqiao Sun, Yimin D. Zhang
semanticscholar +1 more source
Person Reidentification Based on Automotive Radar Point Clouds
IEEE Transactions on Geoscience and Remote Sensing, 2021Person reidentification (ReID) systems play a key role in intelligent visual surveillance systems and have widespread applications, for example, in public security. Usually, person ReID systems can identify a person with cameras.
Yuwei Cheng, Yimin Liu
semanticscholar +1 more source
Advanced Computing and Communications, 2017
Automotive radars, along with other sensors such as lidar, (which stands for “light detection and ranging”), ultrasound, and cameras, form the backbone of self-driving cars and advanced driver assistant systems (ADASs). These technological advancements are enabled by extremely complex systems with a long signal processing path from radars/sensors to ...
Sujeet Patole +3 more
openaire +1 more source
Automotive radars, along with other sensors such as lidar, (which stands for “light detection and ranging”), ultrasound, and cameras, form the backbone of self-driving cars and advanced driver assistant systems (ADASs). These technological advancements are enabled by extremely complex systems with a long signal processing path from radars/sensors to ...
Sujeet Patole +3 more
openaire +1 more source
Automotive Radar-Based Vehicle Tracking Using Data-Region Association
IEEE transactions on intelligent transportation systems (Print), 2022For automotive radar-based extended object tracking, this paper proposes a new approach, which jointly estimates the kinematic state and the extension of a vehicle.
Xiaomeng Cao, Jiang Lan, X. Li, Yu Liu
semanticscholar +1 more source
Road-Map Aided GM-PHD Filter for Multivehicle Tracking With Automotive Radar
IEEE Transactions on Industrial Informatics, 2022Nowadays, accurate and real-time vehicle tracking is critical to ensure the safety of intelligent vehicles. However, tracking in the complex traffic environments still remains a challenging issue.
Kun Shi +5 more
semanticscholar +1 more source
IEEE Sensors Letters, 2021
This letter reports the measurements and results of tests conducted on the detection of unmanned aircraft systems (UASs) or drones using a millimeter-wave (mmWave) automotive radar sensor. Designed for the detection of automotive targets with radar cross
P. Morris, K. Hari
semanticscholar +1 more source
This letter reports the measurements and results of tests conducted on the detection of unmanned aircraft systems (UASs) or drones using a millimeter-wave (mmWave) automotive radar sensor. Designed for the detection of automotive targets with radar cross
P. Morris, K. Hari
semanticscholar +1 more source
Automotive radar gridmap representations
2015 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM), 2015In robotic applications gridmaps are a common representation of the environment. For the automotive field, radar as sensing technology is suitable due to its robustness. This paper presents two radar-based grid-mapping algorithms for automotive applications like self-localization.
Klaudius Werber +6 more
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A Broadband E-Band Single-Layer-SIW-to-Waveguide Transition for Automotive Radar
IEEE Microwave and Wireless Components Letters, 2022An $E$ -band air-filled rectangular waveguide (RWG) to single thin-layer (0.127 mm) substrate integrated waveguide (SIW) transition is proposed for automotive radar applications.
Kaiqiang Zhu +4 more
semanticscholar +1 more source
Automotive Radar Signal Analysis
2020This chapter provides a brief, albeit in-depth, explanation of automotive radar and signal processing. It explains a comparative study, wherein the performance of a conventional radar solution is compared to an innovative method. Radar has been extensively examined as a solution among industry, military, and academic researchers for solving issues ...
Hassan Moradi, Ashish Basireddy
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