79-GHz Four-RFIC Cascading Radar System for Autonomous Driving

Kim, Jong-Seok; Kim, Byung-Kwan; Choi, Sungdo; Cho, Hyunwoong; Kim, Woosuk; Eo, Minsung; Khang, Seung-Tae; Lee, Seongwook; Sugiura, T.; Nikishov, Artem; Tanji, Koki; Lukyanov, Anton

doi:10.1109/iscas45731.2020.9180805

Cited by 11 publications

(3 citation statements)

References 8 publications

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“…Multi-Input Multi-Output (MIMO) is a technology that effectively increases the total number of antennas by introducing a virtual antenna concept [8,9]. The orthogonality of each transmitting signals can be obtained through specific methods such as time division multiplexing and MIMO, which improves angular resolution through an increased antenna aperture with a virtual array [10,11]. Combined with an appropriate antenna array arrangement, high-resolution point cloud information of the surroundings can be obtained from the radar.…”

Section: Radar Systemmentioning

confidence: 99%

Implementation of MIMO Radar-Based Point Cloud Images for Environmental Recognition of Unmanned Vehicles and Its Application

Kim,

Khang,

Choi

et al. 2024

Remote Sensing

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High-performance radar systems are becoming increasingly popular for accurately detecting obstacles in front of unmanned vehicles in fog, snow, rain, night and other scenarios. The use of these systems is gradually expanding, such as indicating empty space and environment detection rather than just detecting and tracking the moving targets. In this paper, based on our high-resolution radar system, a three-dimensional point cloud image algorithm is developed and implemented. An axis translation and compensation algorithm is applied to minimize the point spreading caused by the different mounting positions and the alignment error of the Global Navigation Satellite System (GNSS) and radar. After applying the algorithm, a point cloud image for a corner reflector target and a parked vehicle is created to directly compare the improved results. A recently developed radar system is mounted on the vehicle and it collects data through actual road driving. Based on this, a three-dimensional point cloud image including an axis translation and compensation algorithm is created. As a results, not only the curbstones of the road but also street trees and walls are well represented. In addition, this point cloud image is made to overlap and align with an open source web browser (QtWeb)-based navigation map image to implement the imaging algorithm and thus determine the location of the vehicle. This application algorithm can be very useful for positioning unmanned vehicles in urban area where GNSS signals cannot be received due to a large number of buildings. Furthermore, sensor fusion, in which a three-dimensional point cloud radar image appears on the camera image, is also implemented. The position alignment of the sensors is realized through intrinsic and extrinsic parameter optimization. This high-performance radar application algorithm is expected to work well for unmanned ground or aerial vehicle route planning and avoidance maneuvers in emergencies regardless of weather conditions, as it can obtain detailed information on space and obstacles not only in the front but also around them.

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Section: Radar Systemmentioning

confidence: 99%

Implementation of MIMO Radar-Based Point Cloud Images for Environmental Recognition of Unmanned Vehicles and Its Application

Kim,

Khang,

Choi

et al. 2024

Remote Sensing

Self Cite

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“…Recent publications discuss multiple-input multiple-output (MIMO) radars with more than 100 [3], [4], [5] or even up to 1700 [6] virtual channels, typically achieved by using a radar frontend with multiple transceiver chips. While these approaches show a high performance in terms of radar imaging, they also lead to large, inflexible hardware designs, as all channels must be placed on a single printed circuit board (PCB).…”

Section: Introductionmentioning

confidence: 99%

Multichannel Repeater for Coherent Radar Networks Enabling High-Resolution Radar Imaging

Werbunat,

Woischneck,

Lerch

et al. 2024

IEEE Trans. Microwave Theory Techn.

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Coherent radar networks allow for spanning very large apertures that include all sensors with their subapertures in the network, resulting in very good angular resolution. However, as a radar network typically has a sparse array, its performance depends on the flexibility of the antenna and network node placement. Thus, in this work, a new type of radar network is presented, allowing for a highly flexible network and array design and providing an excellent performance in direction-of-arrival (DoA) estimation. This is reached by using multichannel repeaters (MCRs) in combination with a single multiple-input multipleoutput (MIMO) radar. The MCRs receives the radar's signal via a line-of-sight path, and then re-transmits it via multiple transmit channels, each with a dedicated mixer used for multiplexing. To show the feasibility and the performance of this concept, a 77-GHz radar network consisting of a digital 4 × 4 MIMO radar and two four-channel MCRs is presented. It is designed following network array design recommendations mathematically derived in this work and combined with an adapted signal processing and network-based DoA estimation. The high performance of the system is demonstrated not only via systematic measurements in an anechoic chamber, but also in various automotive scenarios including multiple road users.

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“…plane are realized. This leads either to a wide beamwidth [18] or a large sparsity [19] in the elevation (el.) plane.…”

Section: Introductionmentioning

confidence: 99%

System Performance of a 79 GHz High-Resolution 4D Imaging MIMO Radar With 1728 Virtual Channels

Schwarz¹,

Riese²,

Dorsch³

et al. 2022

IEEE J. Microw.

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Future driver assistance and autonomous driving systems require high-resolution 4D imaging radars that provide detailed and robust information about the vehicle's surroundings, even in poor weather or lighting conditions. In this work, a novel high-resolution radar system with 1728 virtual channels is presented, exceeding the state-of-the-art channel count for automotive radar sensors by a factor of 9. To realize the system, a new mixed feedthrough and distribution network topology is employed for the distribution of the ramp oscillator signal. A multilayer printed circuit board is designed and fabricated with all components assembled on the back side, while the radio frequency signal distribution is on a buried layer and only the antennas are on the front side. The array is optimized to enable both multipleinput multiple-output operation and transmit beamforming. A sparse array with both transmit and receive antennas close to the transceivers is realized to form a 2D array with a large unambiguous region of 130 • × 75 • with a maximal sidelobe level of −15 dB. The array features a 3 dB beamwidth of 0.78 • × 3.6 • in azimuth and elevation, respectively. Radar measurements in an anechoic chamber show that even the individual peaks of the absorber in the chamber can be detected and separated in the range-angle cut of the 4D radar image. The performance is validated by measurements of a parking lot, where cars, a pedestrian, a fence, and a street lamp can be detected, separated, and estimated correctly in size and position.INDEX TERMS Advanced driver assistance systems (ADAS), automotive radar, chirp sequence modulation, direction-of-arrival (DoA) estimation, frequency modulated continuous wave (FMCW), imaging radar, local oscillator (LO) feedthrough, mm-wave, multiple-input multiple-output (MIMO), time delay correction.This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination.

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79-GHz Four-RFIC Cascading Radar System for Autonomous Driving

Cited by 11 publications

References 8 publications

Implementation of MIMO Radar-Based Point Cloud Images for Environmental Recognition of Unmanned Vehicles and Its Application

Implementation of MIMO Radar-Based Point Cloud Images for Environmental Recognition of Unmanned Vehicles and Its Application

Multichannel Repeater for Coherent Radar Networks Enabling High-Resolution Radar Imaging

System Performance of a 79 GHz High-Resolution 4D Imaging MIMO Radar With 1728 Virtual Channels

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