Experimental study on low‐THz automotive radar signal attenuation during snowfall

Norouzian, Fatemeh; Marchetti, Emidio; Hoare, Edward; Gashinova, Marina; Constantinou, Costas; Gardner, P.; Cherniakov, M.

doi:10.1049/iet-rsn.2018.5644

Cited by 27 publications

(14 citation statements)

References 22 publications

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“…In an explicit study of the effects of adverse weather on automotive radar, Zhang et al [47] note that rain, snow, mist, and hail, can all have a significant impact, showing for example how the received power and probabilities of detection of vehicles and pedestrians reduce considerably as rain density increases. Noruzian et al [48] measured experimentally the effects of snowfall, concluding that as the density of snow increases, so the attenuation increases at all measured wavelengths. Comparing wet and dry snow, higher attenuation occurred in the former case.…”

Section: A Comparison With Automotive Radarmentioning

confidence: 99%

Full Waveform LiDAR for Adverse Weather Conditions

Wallace

Halimi

Buller

2020

IEEE Trans. Veh. Technol.

100

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We present and discuss the case for full waveform pixel and image acquisition and processing to enable LiDAR sensors to penetrate and reconstruct 3D surface maps through obscuring media. To that end, we review work on signal propagation, on scanning and arrayed sensors, on signal processing strategies for independent pixels and employing spatial context, on reducing complexity and accelerating processing by sensor design, algorithmic changes, compressed sensing, and parallel processing. We report several experimental studies on LiDAR imaging through complex media, and how these can inform the automotive LiDAR scenario. We conclude with a discussion of future development and potential for full waveform LiDAR (FWL).

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Section: A Comparison With Automotive Radarmentioning

confidence: 99%

Full Waveform LiDAR for Adverse Weather Conditions

Wallace

Halimi

Buller

2020

IEEE Trans. Veh. Technol.

100

View full text Add to dashboard Cite

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“…It is noted that noise is high at a low frequency and causes false-positive errors at the receiver. Similarly, in [ 89 ], wet and dry snowfall impact on radar at 77 and 300 GHz frequencies was studied. The findings concluded that attenuation due to snow contributed to a decreased range of about 12~18.5 dB/km, and the study also noted that the attenuation varied greatly with snow water content.…”

Section: Sensorsmentioning

confidence: 99%

The Perception System of Intelligent Ground Vehicles in All Weather Conditions: A Systematic Literature Review

Mohammed

Amamou

Ayevide

et al. 2020

Sensors

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Perception is a vital part of driving. Every year, the loss in visibility due to snow, fog, and rain causes serious accidents worldwide. Therefore, it is important to be aware of the impact of weather conditions on perception performance while driving on highways and urban traffic in all weather conditions. The goal of this paper is to provide a survey of sensing technologies used to detect the surrounding environment and obstacles during driving maneuvers in different weather conditions. Firstly, some important historical milestones are presented. Secondly, the state-of-the-art automated driving applications (adaptive cruise control, pedestrian collision avoidance, etc.) are introduced with a focus on all-weather activity. Thirdly, the most involved sensor technologies (radar, lidar, ultrasonic, camera, and far-infrared) employed by automated driving applications are studied. Furthermore, the difference between the current and expected states of performance is determined by the use of spider charts. As a result, a fusion perspective is proposed that can fill gaps and increase the robustness of the perception system.

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“…However, there are transmission windows around 340 GHz, 400 GHz, and 650 GHz where atmospheric loss in clear air does not exceed 10 dB/km, 20 dB/km, and 60 dB/km, respectively [ 14 ]. The results obtained in [ 16 ] for frequencies of 77 GHz and 300 GHz show that even in heavy rain the attenuation of the radar signal did not exceed 20 dB/km, and in [ 17 ] measured attenuation during snowfall was below 15 dB/km. Therefore, for the automotive radar operational range of up to 100 m, atmospheric loss will not exceed 10 dB and makes a relatively small contribution to the power budget needed to guarantee system efficiency [ 18 ].…”

Section: Introductionmentioning

confidence: 99%

Study of Low Terahertz Radar Signal Backscattering for Surface Identification

Sabery

Bystrov

Navarro‐Cía

et al. 2021

Sensors

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This study explores the scattering of signals within the mm and low Terahertz frequency range, represented by frequencies 79 GHz, 150 GHz, 300 GHz, and 670 GHz, from surfaces with different roughness, to demonstrate advantages of low THz radar for surface discrimination for automotive sensing. The responses of four test surfaces of different roughness were measured and their normalized radar cross sections were estimated as a function of grazing angle and polarization. The Fraunhofer criterion was used as a guideline for determining the type of backscattering (specular and diffuse). The proposed experimental technique provides high accuracy of backscattering coefficient measurement depending on the frequency of the signal, polarization, and grazing angle. An empirical scattering model was used to provide a reference. To compare theoretical and experimental results of the signal scattering on test surfaces, the permittivity of sandpaper has been measured using time-domain spectroscopy. It was shown that the empirical methods for diffuse radar signal scattering developed for lower radar frequencies can be extended for the low THz range with sufficient accuracy. The results obtained will provide reference information for creating remote surface identification systems for automotive use, which will be of particular advantage in surface classification, object classification, and path determination in autonomous automotive vehicle operation.

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Experimental study on low‐THz automotive radar signal attenuation during snowfall

Cited by 27 publications

References 22 publications

Full Waveform LiDAR for Adverse Weather Conditions

Full Waveform LiDAR for Adverse Weather Conditions

The Perception System of Intelligent Ground Vehicles in All Weather Conditions: A Systematic Literature Review

Study of Low Terahertz Radar Signal Backscattering for Surface Identification

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