Dual-polarized slot-coupled patch antennas on Duroid with teflon lenses for 76.5-GHz automotive radar systems

1999 ◽  
Vol 47 (12) ◽  
pp. 1836-1842 ◽  
Author(s):  
B.G. Porter ◽  
L.L. Rauth ◽  
J.R. Mura ◽  
S.S. Gearhart
Keyword(s):  
Patch Antennas ◽  
Automotive Radar ◽  
Radar Systems ◽  
Dual Polarized

scholarly journals Lens-based 77 GHZ MIMO radar for angular estimation in multitarget environments

2014 ◽  
Vol 6 (3-4) ◽  
pp. 397-404 ◽  
Author(s):  
Steffen Lutz ◽  
Thomas Walter ◽  
Robert Weigel
Keyword(s):  
Direction Of Arrival ◽  
Doa Estimation ◽  
Mimo Radar ◽  
Separation Performance ◽  
Patch Antennas ◽  
Waveform Generator ◽  
Automotive Radar ◽  
Sensor Performance ◽  
Radar Systems ◽  
77 Ghz

The demanding tasks for automotive radar systems in multitarget scenarios require an increased target separation performance and new sensor concepts. In this contribution, a highly integrated 77 GHz time domain multiplex (TDM) MIMO radar is presented. The sensor is feasible for advanced direction of arrival (DOA) estimation in azimuth and elevation. For efficient and high-quality measurements a fractional-n phased locked loop (PLL) with integrated waveform generator, enabling chirp and frequency modulated continous waveform (FMCW) modulations, is implemented. Spatial beamforming is done with series feed array patch antennas in combination with a dielectric cylindrical lens. For the improvement of the direction of arrival (DOA) estimation performance a new lens-based MIMO radar approach is introduced. Therefore the classical MIMO approach is combined with the advantages of an optical beamforming concept. Due to the usage of these techniques the sensor performance in accuracy, ambiguity suppression, and angular resolution can be significantly increased.

Automotive Radars

2017 ◽  
Author(s):  
Sujeet Patole ◽  
Murat Torlak ◽  
Dan Wang ◽  
Murtaza Ali
Keyword(s):  
Signal Processing ◽  
Pedestrian Detection ◽  
Radar Signal ◽  
Automotive Radar ◽  
Estimation Algorithms ◽  
Radar Systems ◽  
Starting Point ◽  
Processing Techniques ◽  
Automotive Radars ◽  
Signal Processing Techniques

Automotive radars, along with other sensors such as lidar, (which stands for “light detection and ranging”), ultrasound, and cameras, form the backbone of self-driving cars and advanced driver assistant systems (ADASs). These technological advancements are enabled by extremely complex systems with a long signal processing path from radars/sensors to the controller. Automotive radar systems are responsible for the detection of objects and obstacles, their position, and speed relative to the vehicle. The development of signal processing techniques along with progress in the millimeter- wave (mm-wave) semiconductor technology plays a key role in automotive radar systems. Various signal processing techniques have been developed to provide better resolution and estimation performance in all measurement dimensions: range, azimuth-elevation angles, and velocity of the targets surrounding the vehicles. This article summarizes various aspects of automotive radar signal processing techniques, including waveform design, possible radar architectures, estimation algorithms, implementation complexity-resolution trade-off, and adaptive processing for complex environments, as well as unique problems associated with automotive radars such as pedestrian detection. We believe that this review article will combine the several contributions scattered in the literature to serve as a primary starting point to new researchers and to give a bird’s-eye view to the existing research community.

Pedestrian Classification for 79 GHz Automotive Radar Systems

2018 ◽  
Author(s):  
Robert Prophet ◽  
Marcel Hoffmann ◽  
Alicja Ossowska ◽  
Waqas Malik ◽  
Christian Sturm ◽  
...  
Keyword(s):  
Automotive Radar ◽  
Radar Systems
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