Journal of the Korea Institute of Military Science and Technology (한국군사과학기술학회지)

The Korea Institute of Military Science and Technology (한국군사과학기술학회)
권호 표지
DOI QR코드

DOI QR Code

Optimal Search Pattern of Ships based on Performance Surface

음향 탐지 성능 분포도 기반에서 함정 최적탐색패턴에 관한 연구

  • Cheon, Minki (Naval Academy in Department of Oceanography) ;
  • Kim, Sunhyo (Department of Marine Sciences and Convergent Technology, Hanyang University) ;
  • Choi, Jee Woong (Department of Marine Sciences and Convergent Technology, Hanyang University) ;
  • Choi, Cheolwoo (Navy Headquaters) ;
  • Son, Su-Uk (The 6th Research and Development Institute, Agency for Defense Development) ;
  • Park, Joungsoo (The 6th Research and Development Institute, Agency for Defense Development)
  • 천민기 (해군사관학교 해양학과) ;
  • 김선효 (한양대학교 해양융합공학과) ;
  • 최지웅 (한양대학교 해양융합공학과) ;
  • 최철우 (해군본부) ;
  • 손수욱 (국방과학연구소 제6기술연구본부) ;
  • 박정수 (국방과학연구소 제6기술연구본부)
  • Received : 2017.01.10
  • Accepted : 2017.05.12
  • Published : 2017.06.05
Download PDF
⟨ Previous Next ⟩

Abstract

The goal of this study is simulation of optimal search pattern of ships based on performance surface which are reflected underwater environmental. The process is as follows. First, temporal and spatial environmental database are extracted in complex environment and input hull mounted SONAR system parameters. The environmental database and SONAR system parameters are substituted to SONAR equations, and calculate signal excess, detection probability, detection range. And then, the performance surface, which can be used to provide operational insight of SONAR detection performance, are pictorialized. Finally, optimal search pattern of ships are simulated using genetic algorithm based on performance surface. And then, we certify optimal search pattern in various ways.

Keywords

References

  1. P. Mcdowell, "Environmental and Statistical Performance Mapping Model for Underwater Acoustic Detection Systems," University of New Orleans Theses and Dissertations, 2010.
  2. S. H. Kim, et. al., "Optimal Deployment of Sensor Nodes based on Performance Surface of Acoustic Detection," Journal of the Korea Institute of Military Science and Technology, Vol. 18, No. 5, pp. 538-547, 2015. https://doi.org/10.9766/KIMST.2015.18.5.538
  3. J. H. Cho, et. al., "Measure of Effectiveness for Detection and Cumulative Detection Probability," Journal of the Korea Institute of Military Science and Technology, Vol. 15, No. 5, pp. 601-614, 2012. https://doi.org/10.9766/KIMST.2012.15.5.601
  4. C. Amante and B. W. Eakins, "ETOPO1 Arc-Minute Global Relief Model: Procedures, Data Source and Analysis," NOAA Technical Memorandum, NGDC (National Geophysical Data Center), 2009.
  5. M. R. Carnes, "Description and Evaluation of GDEM-V 3.0," Naval Research Laboratory, 2009.
  6. Korea Institute of Geology, Mining and Materials Rep. NP2007-010, 2007.
  7. R. J. Urick, "Principles of Underwater Sound," 3rd edition, McGraw-Hill Book Company, USA, pp. 17-29, 1983.
  8. A. D. Waite, "Sonar for Practising Engineers, 3rd edition," WILEY and SONS, UK, pp. 119-124, 2002.
  9. B. P. Michael, "Gaussian Beam Tracing for Computing Ocean Acoustic Fields," Journal of the Acoustical Society of America, Vol. 82, No. 4, pp. 1349-1359, 1987. https://doi.org/10.1121/1.395269
  10. M. D. Collins, "User's Guide for RAM Versions 1.0 and 1.0p," Technical report, Naval Research Laboratory, Washington, pp. 1-14, 1995.
  11. R. J. Urick, "Principles of Underwater Sound," 3rd edition, McGraw-Hill Book Company, USA, pp. 386-390, 1983.
  12. C. W. Choi, "Optimal Deployment of Variable Depth Sonar Systems using Performance Surface and Genetic Algorithm," 2016.
  13. K. P. Hemsteter and Donald R. DelBalzo, "Acoustic Benchmark Validation of GRASP ASW Search Plans," MTS/IEEE Conference on Ocean, Vol. 1, pp. 60-64, 2002.
  14. D. P. Kierstead, D. R. DelBalzo: "A Genetic Algorithm Applied to Planning Search Paths in Complicated Environments," Military Operations Research 8, No. 2: pp. 45-49, 2003. https://doi.org/10.5711/morj.8.2.45