The Journal of the Acoustical Society of Korea (한국음향학회지)

The Acoustical Society of Korea (한국음향학회)
권호 표지
DOI QR코드

DOI QR Code

A clutter reduction algorithm based on clustering for active sonar systems

능동소나 시스템을 위한 군집화 기반의 클러터 제거 기법

  • 곽철현 (국방과학연구소 소나체계단) ;
  • 정명준 (국방과학연구소 소나체계단) ;
  • 안재균 (국방과학연구소 소나체계단)
  • Received : 2015.12.09
  • Accepted : 2016.01.11
  • Published : 2016.03.31
Download PDF
⟨ Previous Next ⟩

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.

본 논문에서는 천해 환경에서 고밀도로 형성되는 클러터를 제거하는 군집화 기반의 능동소나 클러터 제거 기법을 제안한다. 먼저 제안하는 기법에서는 표적의 속도, 송신 핑 주기 등을 고려하여 측정치에 대해 밀도 기반의 군집화를 수행한다. 군집으로 분류된 측정치들을 실제 표적에 대한 후보로 가정하고 군집화 되지 않은 측정치인 잡음을 제거한다. 군집화 후 군집별 표적 여부를 판단하기 위해 유효성 검사를 실시하여 표적과 클러터를 구분한다. 최종적으로 표적으로 분류되지 않은 군집의 측정치들을 클러터로 간주하여 제거한다. 제안한 기법을 모의신호와 해상실험데이터를 이용하여 성능 분석한 결과, 본 논문에서 제안한 군집화 기반의 능동소나 클러터 기법의 성능이 기존 방법보다 우수함을 확인하였다.

Keywords

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). https://doi.org/10.1109/JOE.2010.2044912
  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). https://doi.org/10.1109/JOE.2002.804324
  5. D. A. Abraham, "Array modeling of active sonar clutter," IEEE J. Ocean. Eng. 33, 158-170, (2008). https://doi.org/10.1109/JOE.2008.919604
  6. D. A. Abraham, "The effect of multipath on the envelope statistics of bottom clutter," IEEE J. Ocean. Eng. 32, 848-861 (2007). https://doi.org/10.1109/JOE.2007.906984
  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). https://doi.org/10.7776/ASK.2013.32.4.354
  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). https://doi.org/10.1016/j.patrec.2006.04.016
  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). https://doi.org/10.1109/TIT.1960.1057561