Low-THz Radar, Lidar and Optical Imaging through Artificially Generated Fog

Daniel, Liam; Phippen, Dominic; Hoare, Edward; Stove, A.G.; Cherniakov, M.; Gashinova, Marina

doi:10.1049/cp.2017.0369

Cited by 40 publications

(17 citation statements)

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“…Indoor fog chambers are used both for experimentally investigating the performance of sensors [6][7][8][9][10][11] and for validating the developed models against real conditions [1,3]. Many have built their own chamber to mimic fog or rain and some have used the state-of-the-art fog chamber of CEREMA.…”

Section: Introductionmentioning

confidence: 99%

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Testing and Validation of Automotive Point-Cloud Sensors in Adverse Weather Conditions

2019

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Light detection and ranging sensors (LiDARS) are the most promising devices for range sensing in automated cars and therefore, have been under intensive development for the last five years. Even though various types of resolutions and scanning principles have been proposed, adverse weather conditions are still challenging for optical sensing principles. This paper investigates proposed methods in the literature and adopts a common validation method to perform both indoor and outdoor tests to examine how fog and snow affect performances of different LiDARs. As suspected, the performance degraded with all tested sensors, but their behavior was not identical.

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Section: Introductionmentioning

confidence: 99%

“…Daniel et al [10] presented a test setup with a sensor set that consisted of a low-THz imaging radar, a LiDAR, and a stereo optical camera. Their aim is to highlight the need for low-THz radar as a part of automotive sensor setup especially in weather conditions where optical systems fail.…”

Section: Introductionmentioning

confidence: 99%

Testing and Validation of Automotive Point-Cloud Sensors in Adverse Weather Conditions

2019

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“…Regarding maximum range, LiDARs and radars can provide up to 100 m. However, the current technology of the low-THz radar can provide range up to 20 meters [142].…”

Section: Maximum Rangementioning

confidence: 99%

“…A Multi-Modal Object Recognition Dataset for Autonomous Cars in Adverse Weather in good weather. On the other hand, a radar sensor is known to be more robust in many adverse conditions [142,191,192]. However, there are few public radar datasets for automotive applications, especially with object annotation and in bad weather.…”

Section: Introductionmentioning

confidence: 99%

300 GHz radar object recognition based on deep neural networks and transfer learning

Sheeny

Wallace

Wang

2020

IET Radar, Sonar & Navigation

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“…The same study showed that for 50 mm/h rainfall, the attenuation peaks at around 100 GHz and above this, remains constant or decreases. In [15], the authors have shown the results of measurements of attenuation in fog which demonstrated the little effect of fog on the imaging performance of the radar operating at 150 GHz.…”

Section: Introductionmentioning

confidence: 99%

Application of Doppler beam sharpening for azimuth refinement in prospective low‐THz automotive radars

Daniel

Stove

Hoare

et al. 2018

IET Radar, Sonar & Navigation

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In this study, the authors investigate the application of the Doppler beam sharpening (DBS) technique for angular refinement to the emerging area of low-terahertz (THz) radar sensing. Ultimately this is to improve radar image quality in the azimuth plane to complement the excellent range resolution and thus improve object classification in low-THz radar imaging systems for autonomous platforms. The study explains the fundamental theory behind the process of DBS and describes the applicability of DBS to automotive sensing, indicating the potential for synthetic beamwidths of a fraction of a degree. Low-THz DBS was experimentally tested under controlled laboratory conditions, not only to accurately localised target objects in Cartesian space but also to provide unique object imaging at low-THz frequencies with wide azimuthal beamwidth antennas. It was shown that a stationary (i.e. non-scanned) wide beam antenna mounted on a moving platform can deliver imagery at least comparable to that produced by physical beamforming, be that steering arrays or narrow beam scanning antennas as in the experimental case presented.

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Low-THz Radar, Lidar and Optical Imaging through Artificially Generated Fog

Cited by 40 publications

References 0 publications

Testing and Validation of Automotive Point-Cloud Sensors in Adverse Weather Conditions

Testing and Validation of Automotive Point-Cloud Sensors in Adverse Weather Conditions

300 GHz radar object recognition based on deep neural networks and transfer learning

Application of Doppler beam sharpening for azimuth refinement in prospective low‐THz automotive radars

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