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Beam Slice-Based Recognition Method for Acoustic Landmark With Multi-Beam Forward Looking Sonar SCIE SCOPUS

Title
Beam Slice-Based Recognition Method for Acoustic Landmark With Multi-Beam Forward Looking Sonar
Authors
Pyo, JuhyunCho, HyeonwooYu, Son-Cheol
Date Issued
2017-11
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Abstract
Autonomous underwater vehicles (AUVs) have been widely used for many risky underwater tasks. For these tasks, AUVs require navigational aids, such as active beacon-type underwater acoustic landmarks, which are the most widely used. It requires heavy installation loads and regular maintenance with high price sensors. In this paper, we propose a novel localization method in shallow water with a multi-beam forward looking sonar (MFLS), where positioning is based on passive-type acoustic landmarks. The proposed landmark comprises a combination of concrete pillars with a highly reliable and efficient recognition method for the real-time use of AUVs. The proposed landmark system has many advantages in the practical use, such as no maintenance, being strong on the marine bio-fouling, and light installation load with low price concrete pillars. The proposed recognition method is divided into two processes to verify the landmark. First, a pillarlike object is separated from the background, and the height of the pillar is calculated by the length of the shadow, which has a very high recognition rate and accuracy. Through modeling, the distance from the landmark to the MFLS can be calculated. The proposed method stochastically updates the navigation data based on the positional relationship with the landmark. The performance of the proposed landmark and its recognition method is verified through a water tank and field experiments using the AUV (Cyclops). The recognition rate and accuracy are also discussed.
Keywords
IMAGE SEQUENCES; OBJECT RECOGNITION; UNDERWATER VEHICLE; CLASSIFICATION; TRACKING
URI
https://oasis.postech.ac.kr/handle/2014.oak/50748
DOI
10.1109/JSEN.2017.2755547
ISSN
1530-437X
Article Type
Article
Citation
IEEE SENSORS JOURNAL, vol. 17, no. 21, page. 7074 - 7085, 2017-11
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