Simultaneous human detection and ranging using a millimeter-wave radar system transmitting wideband noise with an embedded tone

2012 ◽  
Author(s):  
Kyle A. Gallagher ◽  
Ram M. Narayanan
Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5228
Author(s):  
Jin-Cheol Kim ◽  
Hwi-Gu Jeong ◽  
Seongwook Lee

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.


2013 ◽  
Vol E96.B (9) ◽  
pp. 2313-2322 ◽  
Author(s):  
Takaaki KISHIGAMI ◽  
Tadashi MORITA ◽  
Hirohito MUKAI ◽  
Maiko OTANI ◽  
Yoichi NAKAGAWA

2014 ◽  
Author(s):  
Uwe Aulenbacher ◽  
Klaus Rech ◽  
Johannes Sedlmeier ◽  
Hans Pratisto ◽  
Peter Wellig

2012 ◽  
Author(s):  
Darren S. Goshi ◽  
Timothy J. Case ◽  
John B. McKitterick ◽  
Long Q. Bui

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