Searching for seafloor massive sulfides: a quantitative review of high-resolution methods in deep sea sonar bathymetry for mining applications

详细信息    查看全文

• 作者：Michael Mitchley (1)
  Michael Sears (2)
  
• 关键词：Beamforming ; Multibeam systems ; Seafloor massive sulphides ; Signal enumeration
• 刊名：Marine Geophysical Researches
• 出版年：2014
• 出版时间：June 2014
• 年：2014
• 卷：35
• 期：2
• 页码：157-174
• 全文大小：
• 参考文献：1. Barabell AJ (1983) Improving the resolution performance of eigenstructure-based direction-finding algorithms. In: Proceedings ICASSP, pp 336鈥?39
  2. Bienvenu G, Kopp L (1980) Adaptivity to background noise spatial coherence for high resolution passive methods. In: Internatinal conference on acoustics, speech and signal processing, pp 307鈥?10
  3. Bienvenu G, Kopp L (1983) Optimality of high resolution array processing using the eigensystem approach. IEEE Trans Acoust 31:1235鈥?248 CrossRef
  4. Birney K, Griffin A, Gwiazda J, Kefauver J, Nagai T, Varchol D (2008) Potential deep-sea mining of seafloor massive sulfides: a case study in Papua New Guinea. University of California at Santa Barbara, Tech. rep
  5. Capon J (1969) High-resolution frequency-wavenumber spectrum analysis. Proc IEEE 57(8):1408鈥?418 CrossRef
  6. Diederen A (2009) http://europe.theoildrum.com/node/5239
  7. Goddard RP (1989) The sonar simulation toolset. In: OCEANS鈥?9. Proceedings, IEEE, vol 4, pp 1217鈥?222
  8. Kotanchek ME, Dzielski JE (1996) Subspace stability in high resolution direction finding and signal enumeration. In: Proceedings of the 1996 symposium on autonomous underwater vehicle technology, pp 192鈥?99
  9. Krim H, Viberg M (1996), Two decades of array signal processing: the parametric approach. IEEE Signal Process Mag 13(4):67鈥?4
  10. Kritchman S, Nadler B (2008) Determining the number of components in a factor model from limited noisy data. Chemometr Intell Lab Syst 94(1):19鈥?2 CrossRef
  11. La Cour B, Collins C, Landry J (2006) Multi-everything sonar simulator (mess). In: Information fusion, 2006 9th international conference on, IEEE, pp 1鈥?
  12. Li J, Wang Z, Stoica P (2005) Robust capon beamforming. Wiley, London CrossRef
  13. Lipton I (2008) Mineral resource estimate solwara 1 project Bismarck Sea Papua New Guinea. Tech. rep, golder associates
  14. Moses R (2005) http://www2.ece.ohio-state.edu/~andy/SAtext/
  15. Ondr茅as H, Cannat M, Fouquet Y, Normand A, Sarradin P-M, Sarrazin J (2009) Recent volcanic events and the distribution of hydrothermal venting at the lucky strike hydrothermal field. Mid-Atlantic Ridge. Geochem Geophys Geosyst 10(2):1鈥?8 CrossRef
  16. Pantartzis D, de Moustier C, Alexandrou D (1993) Application of high-resolution beamforming to multibeam swath bathymetry. In: OCEANS 93, pp II/77 - II/82
  17. Pujol GL (2007) Improvement of the spatial resolution for multibeam echosounders. PhD thesis, Universite de Rennes I
  18. Ronhovde A (1999) High resolution beamforming of Simrad EM3000 bathymetric multibeam sonar data. PhD thesis, University of Oslo
  19. Roy R, Kailath T (1989) ESPRIT-estimation of signal parameters via rotational invariance techniques. IEEE Trans Acoust 37(7):984鈥?95 CrossRef
  20. Schmidt RO (1981) A signal subspace approach to multiple emitter location and spectral estimation. PhD thesis, Stanford University
  21. Stoica P, Sharman K (1990) A novel eigenanalysis method for direction estimation. Proc IEEE pp 19鈥?6
  22. Tarlet O, Loussert A, Sintes C (2007) Sonar images from well-known simulated raw data. In: IEEE international conference on signal processing and communications, pp 1423鈥?426
  23. Viberg M, Ottersten B, Kailath T (1991) Detection and estimation in sensor arrays using weighted subspace fitting. IEEE Trans Signal Process 39:2436鈥?449 CrossRef
  24. Waite AD (2002) Sonar for practising engineers, 3rd edn. Wiley, London
  25. Zhu Y, Sala-Diakanda S (2007) Integration of underwater sonar simulation with a geografical information system. In: Proceedings of the 2007 winter simulation conference, pp 1378鈥?386
  26. Zhu Y, Bull M, Akin H (2008) Information fusion in underwater sonar simulation. In: Proceedings of the 2008 winter simulation conference, pp 1250鈥?258
  
• 作者单位：Michael Mitchley (1)
  Michael Sears (2)
  
  1. School of Computational and Applied Mathematics, University of the Witwatersrand, Johannesburg, South Africa
  2. School of Computer Science, University of the Witwatersrand, Johannesburg, South Africa
  
• ISSN：1573-0581

文摘

Seafloor massive sulphides are deep sea mineral deposits currently being examined as a potential mining resource. Conventional sonar bathymetry products gathered by sea surface platforms do not achieve adequate spatial resolution to detect these resources. High-resolution beamforming methods (such as multiple signal classification and estimation of signal parameters via rotational invariance techniques) improve the resolution of sonar bathymetry. We perform a quantitative review of these high-resolution methods using a novel simulator, showing results in the absence of platform motion for a single ping cycle. It was found that high-resolution methods achieved greater bathymetric accuracy and higher resolution than conventional beamforming and that these methods may be adequate for this style of marine exploration. These methods were also robust in the presence of unwanted persistent signals and low signal to noise ratios.