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A clutter reduction algorithm based on clustering for active sonar systems
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 Title & Authors
A clutter reduction algorithm based on clustering for active sonar systems
Kwak, ChulHyun; Cheong, Myoung Jun; Ahn, Jae-Kyun;
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 Abstract
In this paper, we propose a new clutter reduction algorithm, which rejects heavy clutter density in shallow water environments, based on a clustering method. At first, it applies the density-based clustering to active sonar measurements by considering speed of targets, pulse repetition intervals, etc. We assume clustered measurements as target candidates and remove noise, which is a set of unclustered measurements. After clustering, we classify target and clutter measurements by the validation check method. We evaluate the performance of the proposed algorithm on synthetic data and sea-trial data. The results demonstrate that the proposed algorithm provides significantly better performances to reduce clutter than the conventional algorithm.
 Keywords
Clutter reduction;Active sonar;Clustering;Principal component analysis;
 Language
Korean
 Cited by
 References
1.
R. J. Urick, Principles of Underwater Sound for Engineers (McGraw-Hill, New York, 1967), pp. 211-262.

2.
J. M. Fialkowski and R. C. Gauss, "Methods for identifying and controlling sonar clutter," IEEE J. Ocean. Eng. 35, 330-354 (2010). crossref(new window)

3.
D. A. Abraham and S. F. Johnson, "Statistical modeling of broadband clutter," IEEE Int. Symp. Reverberat. Clutter, 247-254 (2008).

4.
D. A. Abraham and A. P. Lyons, "Novel physical interpretations of K-distributed reverberation," IEEE J. Ocean. Eng. 27, 800-813 (2002). crossref(new window)

5.
D. A. Abraham, "Array modeling of active sonar clutter," IEEE J. Ocean. Eng. 33, 158-170, (2008). crossref(new window)

6.
D. A. Abraham, "The effect of multipath on the envelope statistics of bottom clutter," IEEE J. Ocean. Eng. 32, 848-861 (2007). crossref(new window)

7.
D. D. Ellis, "Measurements and analysis of reverberation and clutter data," Defence R&D Canada - Atlantic. Rep., 2007.

8.
J. R. Preston, "Studies on sonar clutter and reverberation," ARL-PSU, Rep., 2012.

9.
F. B. Shin, D. H. Kil, and R. Wayland, "IER clutter reduction in shallow water," IEEE Int. Conf. ICASSP, 6, 3041-3044 (1996).

10.
G. J. Dobeck, "Algorithm fusion for automated sea mine detection and classification," IEEE Oceans Conf. 1, 130-134 (2001).

11.
J. M. Aughenbaugh, B. A. Yocom, and B. R. La Cour, "Active clutter reduction through fusion with passive data," IEEE FUSION, 1-8 (2010).

12.
E. Hanusa, D. Krout, and M. R. Gupta, "Clutter rejection by clustering likelihood-based similarities," IEEE FUSION, 1-6 (2011).

13.
S. W. Kim, "Hough transform clutter reduction algorithm for piecewise linear path active sonar target detection and tracking improvement" (in Korean), J. Acoust. Soc. Kr. 32, 354-360 (2013). crossref(new window)

14.
C. H. Kwak and M. J. Jeoung, "Robust clutter reduction algorithm in shallow sea reverberation background" (in Korean), J. KIMST, 416-417 (2015).

15.
M. Ester, H. P. Kriegel, J. Sander, and X. Xu, "A density-based algorithm for discovering clusters in large spatial databases with noise," KDD-96, 226-231 (1996).

16.
Y. S. Lee, H. S. Koo, and C. S. Jeong, "A straight line detection using principal component analysis," Pattern Recognition Letters, 27, 14-15, 1744-1754 (2006). crossref(new window)

17.
S. S. Blackman, Multiple-Target Tracking with Radar Applications (Artech House, Dedham, 1986), pp. 115-146.

18.
P. Swerling, "Probability of detection for fluctuating targets," IEEE Trans. Inform. Theory 6, 269-308 (1960). crossref(new window)