DocumentCode :
3391888
Title :
A novel method of underwater multitarget classification based on Multidimensional Scaling analysis
Author :
Wang, Ruhang ; Huang, Jianguo ; Cui, Xiaodong ; Zhang, Qunfei
Author_Institution :
Coll. of Marine Eng., Northwestern Polytech. Univ., Xi´´an, China
fYear :
2010
fDate :
24-28 Oct. 2010
Firstpage :
361
Lastpage :
364
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 :
geophysical image processing; oceanographic techniques; pattern classification; principal component analysis; target tracking; K-means classifier; PCA; multidimensional scaling analysis; shallow sea; underwater multitarget classification; Artificial neural networks; Feature extraction; Kernel; Principal component analysis; Robustness; Sonar; Target recognition; distance matrix; multidimensional scaling; target classification; underwater multitargets;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing (ICSP), 2010 IEEE 10th International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-5897-4
Type :
conf
DOI :
10.1109/ICOSP.2010.5655129
Filename :
5655129
Link To Document :
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