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ThinkMind // ACCSE 2018, The Third International Conference on Advances in Computation, Communications and Services // View article accse_2018_1_20_90021


Radar-Camera Sensor Fusion Based Object Detection for Smart Vehicles

Authors:
Eugin Hyun
Young-Seok Jin
Hyeong-Cheol Jeon
Young-Nam Shin

Keywords: Post processing; Sensor fusion; ADAS.

Abstract:
We propose a post-data processing scheme for radar sensors in a fusion system consisting of a camera and radar sensors. The proposed scheme is divided into the recursive least square filter, the ghost target and clutter cancellation, and region of interest (ROI) selection. Especially for the recursive least square filter, we determine whether detections are valid tracks or are new tracks to initialize or update the filter parameters. Next, we apply the valid detections to the filter to reduce detection errors. Next, we cancel ghost targets as comparing the current tracks and the last tracks, and suppress clutter using the detected radial velocity. Finally, we select the ROI and determine the transfer coordinates to provide these values to the camera sensor. To verify the proposed method, we use Delphi commercial radar and carry out the measurements in a chamber and on the real road.

Pages: 5 to 10

Copyright: Copyright (c) IARIA, 2018

Publication date: July 22, 2018

Published in: conference

ISSN: 2519-8459

ISBN: 978-1-61208-658-3

Location: Barcelona, Spain

Dates: from July 22, 2018 to July 26, 2018

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