Classification and Tracking of Moving Objects from 77 GHz Automotive Radar Sensors

2018 ◽  
Author(s):  
Yue Wang ◽  
Yilong Lu
Keyword(s):  
Moving Objects ◽  
Automotive Radar ◽  
Radar Sensors ◽  
77 Ghz

scholarly journals Constraint-Based Hierarchical Cluster Selection in Automotive Radar Data

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3410
Author(s):  
Claudia Malzer ◽  
Marcus Baum
Keyword(s):  
Moving Objects ◽  
Hierarchical Cluster ◽  
Autonomous Driving ◽  
Radar Data ◽  
Background Information ◽  
Automotive Radar ◽  
Data Set ◽  
Radar Sensors ◽  
Small Clusters ◽  
Cluster Level

High-resolution automotive radar sensors play an increasing role in detection, classification and tracking of moving objects in traffic scenes. Clustering is frequently used to group detection points in this context. However, this is a particularly challenging task due to variations in number and density of available data points across different scans. Modified versions of the density-based clustering method DBSCAN have mostly been used so far, while hierarchical approaches are rarely considered. In this article, we explore the applicability of HDBSCAN, a hierarchical DBSCAN variant, for clustering radar measurements. To improve results achieved by its unsupervised version, we propose the use of cluster-level constraints based on aggregated background information from cluster candidates. Further, we propose the application of a distance threshold to avoid selection of small clusters at low hierarchy levels. Based on exemplary traffic scenes from nuScenes, a publicly available autonomous driving data set, we test our constraint-based approach along with other methods, including label-based semi-supervised HDBSCAN. Our experiments demonstrate that cluster-level constraints help to adjust HDBSCAN to the given application context and can therefore achieve considerably better results than the unsupervised method. However, the approach requires carefully selected constraint criteria that can be difficult to choose in constantly changing environments.

Angular measurements in azimuth and elevation with 77 GHz radar sensors

2013 ◽  
Vol 5 (1) ◽  
pp. 35-42 ◽  
Author(s):  
Klaus Baur ◽  
Marcel Mayer ◽  
Steffen Lutz ◽  
Thomas Walter
Keyword(s):  
Elevation Angle ◽  
Azimuth Angle ◽  
Radar Signal ◽  
Automotive Radar ◽  
Radar Sensor ◽  
Radar Sensors ◽  
Dielectric Lens ◽  
Angular Measurements ◽  
Array Structure ◽  
77 Ghz

An antenna concept for direction of arrival estimation in azimuth and elevation is proposed for 77 GHz automotive radar sensors. This concept uses the amplitude information of the radar signal for the azimuth angle and the phase information for the elevation angle. The antenna consists of a combination of a series-fed-array structure with a cylindrical dielectric lens. This concept is implemented into a radar sensor based on SiGe MMICs for validation. A two- and a four-beam configuration are presented and discussed with respect to angular accuracy and ambiguities.

Target simulator concept for chirp modulated 77 GHz automotive radar sensors

2014 ◽  
Author(s):  
Steffen Lutz ◽  
Christian Erhart ◽  
Thomas Walte ◽  
Robert Weigel
Keyword(s):  
Automotive Radar ◽  
Radar Sensors ◽  
77 Ghz

Millimeter-Wave Technology for Automotive Radar Sensors in the 77 GHz Frequency Band

2012 ◽  
Vol 60 (3) ◽  
pp. 845-860 ◽  
Author(s):  
Jürgen Hasch ◽  
Eray Topak ◽  
Raik Schnabel ◽  
Thomas Zwick ◽  
Robert Weigel ◽  
...  
Keyword(s):  
Millimeter Wave ◽  
Frequency Band ◽  
Automotive Radar ◽  
Radar Sensors ◽  
Wave Technology ◽  
77 Ghz

IMIKO-Radar Project: Laboratory Interference Measurements of Automotive Radar Sensors

2020 ◽  
Author(s):  
Alicja Ossowska ◽  
Leen Sit ◽  
Sarath Manchala ◽  
Thomas Vogler ◽  
Kevin Krupinski ◽  
...  
Keyword(s):  
Automotive Radar ◽  
Radar Sensors ◽  
Interference Measurements
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