Abstract:The top down approach to derive requirements for future radar sensors for autonomous driving is due to its complexity hardly possible. Thus this paper presents the bottom up approach and shows future trends and directions of automotive radar development. This overview paper focusses on functional and non-functional aspects, whereas technological trends are only treated very shortly.
“…iv. Application of DBS mapping using (8) to transform Doppler to angle. This produces the range-azimuth surface.…”
Section: Measurement Overview and Signal Processing Outlinementioning
confidence: 99%
“…Therefore, with the frequency increase, scattering from rougher surfaces becomes more diffuse, less specular and backscatter is received from a fuller extent of an object, enabling more complete imaging of that object [7]. The shift to higher frequencies also has benefits for automotive manufacturers from a cost-space saving perspective, allowing for more compact components [8]. This includes smaller antennas able to deliver narrower beam widths, enabling higher angular resolutions.…”
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.
“…iv. Application of DBS mapping using (8) to transform Doppler to angle. This produces the range-azimuth surface.…”
Section: Measurement Overview and Signal Processing Outlinementioning
confidence: 99%
“…Therefore, with the frequency increase, scattering from rougher surfaces becomes more diffuse, less specular and backscatter is received from a fuller extent of an object, enabling more complete imaging of that object [7]. The shift to higher frequencies also has benefits for automotive manufacturers from a cost-space saving perspective, allowing for more compact components [8]. This includes smaller antennas able to deliver narrower beam widths, enabling higher angular resolutions.…”
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.
“…The drawback of these solutions is obvious -of all negative factors that reduce optical visibility are linked to insufficient illumination. Thus, the main way to solve the actual problem of improving the safety of road transport, under limited or non-existent optical visibility conditions, is to use a radar sensor whose operation does not depend on the time of the day, on weather conditions (snow, rain, fog), or on the presence of smoke or dust [2]- [9]. The range of such a sensor can be a multiple of the expected length of the stopping distance.…”
This article presents the features of an all-weather radio vision system (RVS) ensuring the safety of movement of ground, airborne and sea vehicles and automation of vehicle traffic control under limited or non-existent visibility conditions. New and promising RVS applications in the aviation and rail transport sectors are presented. The potential use of RVS based on an interferometric radar with aperture synthesis, capable of estimating the position of ice fields and the height of icebergs is considered as well.
“…Conventional automotive radar systems mostly look forward in the direction of travel since that is the area of greatest interest to a driver. Keeping in mind, however, the progress being made towards autonomous automobiles [1] [2], it is arguably equally crucial to have a radar which is capable of imaging the scenario to the side of the automobile, so that sensitive road users and traffic situations can be recognised in good time, without the assistance of a human driver. The requirement of an imaging radar can be fulfilled by synthetic aperture radar (SAR), which can take images of the stationary objects in the scenario next to the car as the car is being driven.…”
In this paper a 77 GHz patch array radar is used in combination with the line processing and range Doppler algorithms to produce synthetic aperture radar (SAR) images of automotive scenarios. Measurements are made using a linear rail unit and the images are briefly discussed. In the latter part of the paper, a position error investigation is carried out, where the measurements are customised to fit a real automotive scenario where the automobile experiences acceleration errors which are not detected by the acceleration sensors fixed in the car. The images with errors are then presented and a quantitative analysis is carried out.
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