A DNN-LSTM based Target Tracking Approach using mmWave Radar and Camera Sensor Fusion

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Author
Sengupta, Arindam
Jin, Feng
Cao, Siyang
Affiliation
Univ Arizona, Dept Elect & Comp Engn
Issue Date
2020-04-09
Keywords
Sensor Fusion
DNN
LSTM
Target Tracking
mmWave Radar
Monocular Camera

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Publisher
IEEE
Citation
A. Sengupta, F. Jin and S. Cao, "A DNN-LSTM based Target Tracking Approach using mmWave Radar and Camera Sensor Fusion," 2019 IEEE National Aerospace and Electronics Conference (NAECON), Dayton, OH, USA, 2019, pp. 688-693, doi: 10.1109/NAECON46414.2019.9058168.
Journal
PROCEEDINGS OF THE 2019 IEEE NATIONAL AEROSPACE AND ELECTRONICS CONFERENCE (NAECON)
Rights
Copyright © 2019, IEEE.
Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
Abstract
A new sensor fusion study for monocular camera and mmWave radar using deep neural network and LSTMs is presented. The proposed study includes a decision framework to produce reliable output when either sensor fails. Experiment results to demonstrate single sensor uncertainty and the proposed method's advantages are also presented.
ISSN
0547-3578
DOI
10.1109/naecon46414.2019.9058168
Version
Final accepted manuscript
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