期刊
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
卷 7, 期 3, 页码 533-555出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIV.2022.3167733
关键词
Radar; Chirp; Radar antennas; Radar applications; Reflection; Mixers; Millimeter wave radar; Automotive applications; learning (artificial intelligence); millimeter wave radar; radar detection; simultaneous localization and mapping
Millimeter-wave FMCW RADARs have broad potential applications in automotive industry with improved accuracy and affordability. However, they have lower-density outputs and noise compared to other RADAR technologies, requiring specific algorithms for adaptation.
MmWave (millimeter wave) Frequency Modulated Continuous Waves (FMCW) RADARs are sensors based on frequency-modulated electromagnetic which see their environment in 3D at a long-range. The recent introduction of millimeter-wave RADARs with frequencies from 60 GHz to 300 GHz has broadened their potential applications thanks to their improved accuracy in angle, range, and velocity. MmWave FMCW RADARs have better resolution and accuracy than narrowband and ultra-wideband (UWB) RADARs. In comparison with cameras and LiDARs, they possess several strong advantages such as long-range perception, robustness to lightning, and weather conditions while being cheaper. However, their noisy and lower-density outputs even compared to other technologies of RADARs, and their ability to measure the targets' velocities require specific algorithms tailored for them. Working principles of mmWave FMCW RADARs are presented as well as the separate ways to represent data and their applications. This paper describes algorithms and applications adapted or developed for these sensors in automotive applications. Finally, current challenges and directions for future works are presented.
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