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

Arindam Sengupta, Feng Jin, Siyang Cao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

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.

Original languageEnglish (US)
Title of host publication2019 IEEE National Aerospace and Electronics Conference, NAECON 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages688-693
Number of pages6
ISBN (Electronic)9781728114163
DOIs
StatePublished - Jul 2019
Event2019 IEEE National Aerospace and Electronics Conference, NAECON 2019 - Dayton, United States
Duration: Jul 15 2019Jul 19 2019

Publication series

NameProceedings of the IEEE National Aerospace Electronics Conference, NAECON
Volume2019-July
ISSN (Print)0547-3578
ISSN (Electronic)2379-2027

Conference

Conference2019 IEEE National Aerospace and Electronics Conference, NAECON 2019
Country/TerritoryUnited States
CityDayton
Period7/15/197/19/19

Keywords

  • DNN
  • LSTM
  • MmWave Radar
  • Monocular Camera
  • Sensor Fusion
  • Target Tracking

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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