A novel method of underwater multitarget classification based on Multidimensional Scaling analysis

Ruhang Wang; Jianguo Huang; Xiaodong Cui; Qunfei Zhang

doi:10.1109/ICOSP.2010.5655129

A novel method of underwater multitarget classification based on Multidimensional Scaling analysis

Ruhang Wang, Jianguo Huang, Xiaodong Cui, Qunfei Zhang

School of Marine Science and Technology

Northwestern Polytechnical University Xian

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

1 Scopus citations

Abstract

In order to solve the problem of robustly classifying underwater multiple targets in shallow sea, a novel classification method based on Multidimensional Scaling (MDS) is proposed. This algorithm extracts the robust and distinct feature difference between targets by means of MDS, and optimizes the feature distance by combining with kernel function. A modified K-means classifier is utilized to cluster the extracted features without knowing the prior information of class number. Experiment results on real sonar detecting data indicate that the classifying probability increases by 13.4% compared with PCA, and the probability and robustness of underwater target classification are improved effectively.

Original language	English
Title of host publication	ICSP2010 - 2010 IEEE 10th International Conference on Signal Processing, Proceedings
Pages	361-364
Number of pages	4
DOIs	https://doi.org/10.1109/ICOSP.2010.5655129
State	Published - 2010
Event	2010 IEEE 10th International Conference on Signal Processing, ICSP2010 - Beijing, China Duration: 24 Oct 2010 → 28 Oct 2010

Publication series

Name	International Conference on Signal Processing Proceedings, ICSP

Conference

Conference	2010 IEEE 10th International Conference on Signal Processing, ICSP2010
Country/Territory	China
City	Beijing
Period	24/10/10 → 28/10/10

Keywords

Distance matrix
Multidimensional Scaling
Target classification
Underwater multitargets

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10.1109/ICOSP.2010.5655129

Cite this

Wang, R., Huang, J., Cui, X., & Zhang, Q. (2010). A novel method of underwater multitarget classification based on Multidimensional Scaling analysis. In ICSP2010 - 2010 IEEE 10th International Conference on Signal Processing, Proceedings (pp. 361-364). Article 5655129 (International Conference on Signal Processing Proceedings, ICSP). https://doi.org/10.1109/ICOSP.2010.5655129

@inproceedings{1883cce4d3044c5ba9809c279899cdba,

title = "A novel method of underwater multitarget classification based on Multidimensional Scaling analysis",

abstract = "In order to solve the problem of robustly classifying underwater multiple targets in shallow sea, a novel classification method based on Multidimensional Scaling (MDS) is proposed. This algorithm extracts the robust and distinct feature difference between targets by means of MDS, and optimizes the feature distance by combining with kernel function. A modified K-means classifier is utilized to cluster the extracted features without knowing the prior information of class number. Experiment results on real sonar detecting data indicate that the classifying probability increases by 13.4% compared with PCA, and the probability and robustness of underwater target classification are improved effectively.",

keywords = "Distance matrix, Multidimensional Scaling, Target classification, Underwater multitargets",

author = "Ruhang Wang and Jianguo Huang and Xiaodong Cui and Qunfei Zhang",

year = "2010",

doi = "10.1109/ICOSP.2010.5655129",

language = "英语",

isbn = "9781424458981",

series = "International Conference on Signal Processing Proceedings, ICSP",

pages = "361--364",

booktitle = "ICSP2010 - 2010 IEEE 10th International Conference on Signal Processing, Proceedings",

note = "2010 IEEE 10th International Conference on Signal Processing, ICSP2010 ; Conference date: 24-10-2010 Through 28-10-2010",

}

Wang, R, Huang, J, Cui, X & Zhang, Q 2010, A novel method of underwater multitarget classification based on Multidimensional Scaling analysis. in ICSP2010 - 2010 IEEE 10th International Conference on Signal Processing, Proceedings., 5655129, International Conference on Signal Processing Proceedings, ICSP, pp. 361-364, 2010 IEEE 10th International Conference on Signal Processing, ICSP2010, Beijing, China, 24/10/10. https://doi.org/10.1109/ICOSP.2010.5655129

A novel method of underwater multitarget classification based on Multidimensional Scaling analysis. / Wang, Ruhang; Huang, Jianguo; Cui, Xiaodong et al.
ICSP2010 - 2010 IEEE 10th International Conference on Signal Processing, Proceedings. 2010. p. 361-364 5655129 (International Conference on Signal Processing Proceedings, ICSP).

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

TY - GEN

T1 - A novel method of underwater multitarget classification based on Multidimensional Scaling analysis

AU - Wang, Ruhang

AU - Huang, Jianguo

AU - Cui, Xiaodong

AU - Zhang, Qunfei

PY - 2010

Y1 - 2010

N2 - In order to solve the problem of robustly classifying underwater multiple targets in shallow sea, a novel classification method based on Multidimensional Scaling (MDS) is proposed. This algorithm extracts the robust and distinct feature difference between targets by means of MDS, and optimizes the feature distance by combining with kernel function. A modified K-means classifier is utilized to cluster the extracted features without knowing the prior information of class number. Experiment results on real sonar detecting data indicate that the classifying probability increases by 13.4% compared with PCA, and the probability and robustness of underwater target classification are improved effectively.

AB - In order to solve the problem of robustly classifying underwater multiple targets in shallow sea, a novel classification method based on Multidimensional Scaling (MDS) is proposed. This algorithm extracts the robust and distinct feature difference between targets by means of MDS, and optimizes the feature distance by combining with kernel function. A modified K-means classifier is utilized to cluster the extracted features without knowing the prior information of class number. Experiment results on real sonar detecting data indicate that the classifying probability increases by 13.4% compared with PCA, and the probability and robustness of underwater target classification are improved effectively.

KW - Distance matrix

KW - Multidimensional Scaling

KW - Target classification

KW - Underwater multitargets

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U2 - 10.1109/ICOSP.2010.5655129

DO - 10.1109/ICOSP.2010.5655129

M3 - 会议稿件

AN - SCOPUS:78651068036

SN - 9781424458981

T3 - International Conference on Signal Processing Proceedings, ICSP

SP - 361

EP - 364

BT - ICSP2010 - 2010 IEEE 10th International Conference on Signal Processing, Proceedings

T2 - 2010 IEEE 10th International Conference on Signal Processing, ICSP2010

Y2 - 24 October 2010 through 28 October 2010

ER -

A novel method of underwater multitarget classification based on Multidimensional Scaling analysis

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