Bayesian estimator based target localization in ship monitoring system using multiple compact high frequency surface wave radars

Sangwook Park; Chul Jin Cho; Younglo Lee; Andrew Da Costa; Sang Ho Lee; Hanseok Ko

doi:10.1007/978-3-319-90509-9_9

Bayesian estimator based target localization in ship monitoring system using multiple compact high frequency surface wave radars

Sangwook Park, Chul Jin Cho, Younglo Lee, Andrew Da Costa, Sang Ho Lee, Hanseok Ko

School of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Recently, the usage of high frequency surface wave radars has been expanded to monitoring of ships within observable region because it can always observe wide target region with low power consumption. However, ship monitoring systems using high frequency radars suffer from the fact that a detection position is far away from true position. To resolve this problem, the proposed method determines final location by applying Bayesian estimator to detection results from each ship monitoring system in high frequency radar network. According to Bayesian theory, a posterior distribution is factorized into likelihood and prior distributions, and both distributions are modeled by using each detection results and auto-identification system data, respectively. Effectiveness of the proposed method is demonstrated through appropriate synthetic and real data. From the results, location accuracy can be improved when the proposed method is applied to location estimation.

Original language	English
Title of host publication	Multisensor Fusion and Integration in the Wake of Big Data, Deep Learning and Cyber Physical System - An Edition of the Selected Papers from the 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems MFI 2017
Editors	Hanseok Ko, Sukhan Lee, Songhwai Oh
Publisher	Springer Verlag
Pages	157-167
Number of pages	11
ISBN (Print)	9783319905082
DOIs	https://doi.org/10.1007/978-3-319-90509-9_9
Publication status	Published - 2018
Event	13th IEEE International Conference on Multisensor Integration and Fusion, IEEE MFI 2017 - Daegu, Korea, Republic of Duration: 2017 Nov 16 → 2017 Nov 22

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	501
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Other

Other	13th IEEE International Conference on Multisensor Integration and Fusion, IEEE MFI 2017
Country/Territory	Korea, Republic of
City	Daegu
Period	17/11/16 → 17/11/22

Bibliographical note

Publisher Copyright:
© 2018, Springer International Publishing AG, part of Springer Nature.

Keywords

Compact HF radar network
Distributed sensor network
Fusion
HF surface wave radar
Ship detection

ASJC Scopus subject areas

Industrial and Manufacturing Engineering

Access to Document

10.1007/978-3-319-90509-9_9

Cite this

Park, S., Cho, C. J., Lee, Y., Da Costa, A., Lee, S. H., & Ko, H. (2018). Bayesian estimator based target localization in ship monitoring system using multiple compact high frequency surface wave radars. In H. Ko, S. Lee, & S. Oh (Eds.), Multisensor Fusion and Integration in the Wake of Big Data, Deep Learning and Cyber Physical System - An Edition of the Selected Papers from the 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems MFI 2017 (pp. 157-167). (Lecture Notes in Electrical Engineering; Vol. 501). Springer Verlag. https://doi.org/10.1007/978-3-319-90509-9_9

Bayesian estimator based target localization in ship monitoring system using multiple compact high frequency surface wave radars. / Park, Sangwook; Cho, Chul Jin; Lee, Younglo et al.
Multisensor Fusion and Integration in the Wake of Big Data, Deep Learning and Cyber Physical System - An Edition of the Selected Papers from the 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems MFI 2017. ed. / Hanseok Ko; Sukhan Lee; Songhwai Oh. Springer Verlag, 2018. p. 157-167 (Lecture Notes in Electrical Engineering; Vol. 501).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Park, S, Cho, CJ, Lee, Y, Da Costa, A, Lee, SH & Ko, H 2018, Bayesian estimator based target localization in ship monitoring system using multiple compact high frequency surface wave radars. in H Ko, S Lee & S Oh (eds), Multisensor Fusion and Integration in the Wake of Big Data, Deep Learning and Cyber Physical System - An Edition of the Selected Papers from the 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems MFI 2017. Lecture Notes in Electrical Engineering, vol. 501, Springer Verlag, pp. 157-167, 13th IEEE International Conference on Multisensor Integration and Fusion, IEEE MFI 2017, Daegu, Korea, Republic of, 17/11/16. https://doi.org/10.1007/978-3-319-90509-9_9

Park S, Cho CJ, Lee Y, Da Costa A, Lee SH, Ko H. Bayesian estimator based target localization in ship monitoring system using multiple compact high frequency surface wave radars. In Ko H, Lee S, Oh S, editors, Multisensor Fusion and Integration in the Wake of Big Data, Deep Learning and Cyber Physical System - An Edition of the Selected Papers from the 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems MFI 2017. Springer Verlag. 2018. p. 157-167. (Lecture Notes in Electrical Engineering). doi: 10.1007/978-3-319-90509-9_9

Park, Sangwook ; Cho, Chul Jin ; Lee, Younglo et al. / Bayesian estimator based target localization in ship monitoring system using multiple compact high frequency surface wave radars. Multisensor Fusion and Integration in the Wake of Big Data, Deep Learning and Cyber Physical System - An Edition of the Selected Papers from the 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems MFI 2017. editor / Hanseok Ko ; Sukhan Lee ; Songhwai Oh. Springer Verlag, 2018. pp. 157-167 (Lecture Notes in Electrical Engineering).

@inproceedings{81ad7af6fca84f1595052bad9e8d74b1,

title = "Bayesian estimator based target localization in ship monitoring system using multiple compact high frequency surface wave radars",

abstract = "Recently, the usage of high frequency surface wave radars has been expanded to monitoring of ships within observable region because it can always observe wide target region with low power consumption. However, ship monitoring systems using high frequency radars suffer from the fact that a detection position is far away from true position. To resolve this problem, the proposed method determines final location by applying Bayesian estimator to detection results from each ship monitoring system in high frequency radar network. According to Bayesian theory, a posterior distribution is factorized into likelihood and prior distributions, and both distributions are modeled by using each detection results and auto-identification system data, respectively. Effectiveness of the proposed method is demonstrated through appropriate synthetic and real data. From the results, location accuracy can be improved when the proposed method is applied to location estimation.",

keywords = "Compact HF radar network, Distributed sensor network, Fusion, HF surface wave radar, Ship detection",

author = "Sangwook Park and Cho, {Chul Jin} and Younglo Lee and {Da Costa}, Andrew and Lee, {Sang Ho} and Hanseok Ko",

note = "Publisher Copyright: {\textcopyright} 2018, Springer International Publishing AG, part of Springer Nature.; 13th IEEE International Conference on Multisensor Integration and Fusion, IEEE MFI 2017 ; Conference date: 16-11-2017 Through 22-11-2017",

year = "2018",

doi = "10.1007/978-3-319-90509-9_9",

language = "English",

isbn = "9783319905082",

series = "Lecture Notes in Electrical Engineering",

publisher = "Springer Verlag",

pages = "157--167",

editor = "Hanseok Ko and Sukhan Lee and Songhwai Oh",

booktitle = "Multisensor Fusion and Integration in the Wake of Big Data, Deep Learning and Cyber Physical System - An Edition of the Selected Papers from the 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems MFI 2017",

}

TY - GEN

T1 - Bayesian estimator based target localization in ship monitoring system using multiple compact high frequency surface wave radars

AU - Park, Sangwook

AU - Cho, Chul Jin

AU - Lee, Younglo

AU - Da Costa, Andrew

AU - Lee, Sang Ho

AU - Ko, Hanseok

PY - 2018

Y1 - 2018

N2 - Recently, the usage of high frequency surface wave radars has been expanded to monitoring of ships within observable region because it can always observe wide target region with low power consumption. However, ship monitoring systems using high frequency radars suffer from the fact that a detection position is far away from true position. To resolve this problem, the proposed method determines final location by applying Bayesian estimator to detection results from each ship monitoring system in high frequency radar network. According to Bayesian theory, a posterior distribution is factorized into likelihood and prior distributions, and both distributions are modeled by using each detection results and auto-identification system data, respectively. Effectiveness of the proposed method is demonstrated through appropriate synthetic and real data. From the results, location accuracy can be improved when the proposed method is applied to location estimation.

AB - Recently, the usage of high frequency surface wave radars has been expanded to monitoring of ships within observable region because it can always observe wide target region with low power consumption. However, ship monitoring systems using high frequency radars suffer from the fact that a detection position is far away from true position. To resolve this problem, the proposed method determines final location by applying Bayesian estimator to detection results from each ship monitoring system in high frequency radar network. According to Bayesian theory, a posterior distribution is factorized into likelihood and prior distributions, and both distributions are modeled by using each detection results and auto-identification system data, respectively. Effectiveness of the proposed method is demonstrated through appropriate synthetic and real data. From the results, location accuracy can be improved when the proposed method is applied to location estimation.

KW - Compact HF radar network

KW - Distributed sensor network

KW - Fusion

KW - HF surface wave radar

KW - Ship detection

UR - http://www.scopus.com/inward/record.url?scp=85049971147&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-90509-9_9

DO - 10.1007/978-3-319-90509-9_9

M3 - Conference contribution

AN - SCOPUS:85049971147

SN - 9783319905082

T3 - Lecture Notes in Electrical Engineering

SP - 157

EP - 167

BT - Multisensor Fusion and Integration in the Wake of Big Data, Deep Learning and Cyber Physical System - An Edition of the Selected Papers from the 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems MFI 2017

A2 - Ko, Hanseok

A2 - Lee, Sukhan

A2 - Oh, Songhwai

PB - Springer Verlag

T2 - 13th IEEE International Conference on Multisensor Integration and Fusion, IEEE MFI 2017

Y2 - 16 November 2017 through 22 November 2017

ER -

Bayesian estimator based target localization in ship monitoring system using multiple compact high frequency surface wave radars

Abstract

Publication series

Other

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this