Target tracking with infrared imaging and millimetre-wave radar sensor

2013 ◽  
Author(s):  
Zhang Xuejing ◽  
Ma Long ◽  
Chen He ◽  
Yang Jing
Keyword(s):  
Target Tracking ◽  
Infrared Imaging ◽  
Radar Sensor ◽  
Millimetre Wave ◽  
Wave Radar

Face identification using millimetre-wave radar sensor data

2020 ◽  
Vol 56 (20) ◽  
pp. 1077-1079
Author(s):  
J. Kim ◽  
J.-E. Lee ◽  
H.-S. Lim ◽  
S. Lee
Keyword(s):  
Sensor Data ◽  
Face Identification ◽  
Radar Sensor ◽  
Millimetre Wave ◽  
Wave Radar

scholarly journals One‐shot learning‐based driver's head movement identification using a millimetre‐wave radar sensor

2022 ◽  
Author(s):  
Hong Nhung Nguyen ◽  
Seongwook Lee ◽  
Tien‐Tung Nguyen ◽  
Yong‐Hwa Kim
Keyword(s):  
Head Movement ◽  
Radar Sensor ◽  
Millimetre Wave ◽  
Wave Radar

scholarly journals Millimeter-Wave Radar Sensor for Automated Tomographic Imaging of Composite Materials in a Manufacturing Environment

2021 ◽  
Vol 5 (3) ◽  
pp. 1-4
Author(s):  
Dominik Meier ◽  
Christian Zech ◽  
Benjamin Baumann ◽  
Bersant Gashi ◽  
Matthias Malzacher ◽  
...  
Keyword(s):  
Composite Materials ◽  
Millimeter Wave ◽  
Tomographic Imaging ◽  
Radar Sensor ◽  
Manufacturing Environment ◽  
Millimeter Wave Radar ◽  
Wave Radar

Virtual Radar: Real-Time Millimeter-Wave Radar Sensor Simulation for Perception-driven Robotics

2021 ◽  
pp. 1-1
Author(s):  
Christian Schoffmann ◽  
Barnaba Ubezio ◽  
Christoph Boehm ◽  
Stephan Muhlbacher-Karrer ◽  
Hubert Zangl
Keyword(s):  
Real Time ◽  
Millimeter Wave ◽  
Radar Sensor ◽  
Millimeter Wave Radar ◽  
Wave Radar

scholarly journals Simultaneous Target Classification and Moving Direction Estimation in Millimeter-Wave Radar System

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5228
Author(s):  
Jin-Cheol Kim ◽  
Hwi-Gu Jeong ◽  
Seongwook Lee
Keyword(s):  
Millimeter Wave ◽  
Radar System ◽  
Sensor Data ◽  
Test Field ◽  
Target Classification ◽  
Radar Sensor ◽  
Millimeter Wave Radar ◽  
Direction Estimation ◽  
Wave Radar ◽  
Moving Direction

In this study, we propose a method to identify the type of target and simultaneously determine its moving direction in a millimeter-wave radar system. First, using a frequency-modulated continuous wave (FMCW) radar sensor with the center frequency of 62 GHz, radar sensor data for a pedestrian, a cyclist, and a car are obtained in the test field. Then, a You Only Look Once (YOLO)-based network is trained with the sensor data to perform simultaneous target classification and moving direction estimation. To generate input data suitable for the deep learning-based classifier, a method of converting the radar detection result into an image form is also proposed. With the proposed method, we can identify the type of each target and its direction of movement with an accuracy of over 95%. Moreover, the pre-trained classifier shows an identification accuracy of 85% even for newly acquired data that have not been used for training.

Implementation and vehicle tests of a vehicle stop-and-go cruise control system

2002 ◽  
Vol 216 (7) ◽  
pp. 537-544 ◽  
Author(s):  
K Yi ◽  
N Ryu ◽  
H J Yoon ◽  
K Huh ◽  
D Cho ◽  
...  
Keyword(s):  
Control System ◽  
Control Algorithm ◽  
Speed Control ◽  
Step Motor ◽  
Cruise Control ◽  
Longitudinal Control ◽  
Linear Quadratic Optimal Control ◽  
Millimetre Wave ◽  
Stop And Go ◽  
Wave Radar

Implementation and vehicle tests of a vehicle longitudinal control algorithm for stop-and-go cruise control have been performed. The vehicle longitudinal control scheme consists of a set-speed control algorithm, a speed control algorithm, and a distance control algorithm. A desired acceleration for the vehicle for the control of vehicle-to-vehicle relative speed and clearance has been designed using linear quadratic optimal control theory. Performance of the control algorithm has been investigated via vehicle tests. Vehicle tests have been conducted using two test vehicles. A 2000 cm3 passenger car equipped with a radar distance sensor, throttle/brake actuators and a controller has been used as a subject vehicle in the vehicle tests. A millimetre wave radar sensor has been used for distance measurement. A step motor and an electronic vacuum booster have been used for throttle/brake actuators. It has been shown that the implemented vehicle longitudinal control system can provide satisfactory performance in vehicle set-speed control and vehicle clearance control at lower speeds.

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