Enhanced Iron-Tunnel Recognition for Automotive Radars
- Authors
- Lee, Jae-Eun; Lim, Hae-Seung; Jeong, Seong-Hee; Kim, Seong-Cheol; Shin, Hyun-Chool
- Issue Date
- Jun-2016
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- Keywords
- Adaptive cruise control (ACC); automotive radar; iron tunnel; vehicle
- Citation
- IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, v.65, no.6, pp.4412 - 4418
- Journal Title
- IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
- Volume
- 65
- Number
- 6
- Start Page
- 4412
- End Page
- 4418
- URI
- http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/7599
- DOI
- 10.1109/TVT.2015.2460992
- ISSN
- 0018-9545
- Abstract
- In this paper, we propose a novel iron-tunnel recognition method to overcome the deterioration of the target or vehicle detection performance due to iron-tunnel clutters. Although a few studies on the reflection and diffraction on road surfaces have been conducted for automotive radar sensors, most of these studies did not consider the situation in which structures with larger reflection, such as an iron tunnel, are densely distributed. The proposed method measures the degree of spectral spreading through the analysis of the spectrum characteristics of the received radar signal under different road conditions. The proposed method can successfully detect iron tunnels. In addition, experimental results show that early detection and missing problem of a forward target vehicle in an iron tunnel under adaptive cruise control ( ACC) is improved.
- Files in This Item
- There are no files associated with this item.
- Appears in
Collections - College of Information Technology > ETC > 1. Journal Articles
![qrcode](https://api.qrserver.com/v1/create-qr-code/?size=55x55&data=https://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/7599)
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.