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Ferromagnetic Underwater Target Detection Based on a Magnetic Anomaly Map
Corresponding Author(s) : Izabela Bodus-Olkowska
Geomatics and Environmental Engineering,
Vol. 14 No. 1 (2020): Geomatics and Environmental Engineering
Abstract
A magnetic anomaly map of an underwater area indicates the places where the distortion of a magnetic field has occurred. Through the interpretation procedures, a hydrographer can easily indicate the places where the ferromagnetic objects are, then calculate the level of each distortion ‑ by the value of total anomaly ‑ and initially, based on their own knowledge, try to classify the sources of distortion. Objects that induce micro anomaly changes (>30 nT) ‑ like industrial infrastructure, such as pipelines and cables; to unintendingly located targets with ferromagnetic characteristics: wrecks (vessels, planes, cars), military mines, UXO, lost anchors and chains. Interpretation of such a map with the attempt to identify the source of magnetic field distortion, requires a specific knowledge as well as experience.
In this article the author presents the research results of dimensioning and location of potential ferromagnetic underwater objects based on a magnetic anomaly map. For further consideration an anchor of buoyage system is taken into account. Geolocation of ferromagnetic sources, contours extraction and dimensioning algorithms of ferromagnetic targets have been carried out in Matlab software. The map of magnetic anomaly enhanced with extracted information was developed in ArcGIS. The analysis was carried out for the purpose of the dissertation thesis and the results are used in further research.
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- Hrvoic D., Pozza M.: High‑resolution Magnetic Target Survey. Hydro Interna- tional, July/ August 2004, https://www.academia.edu/3079232/High_Resolution_Magnetic_Target_Survey [access: 30.12.2019].
- Rivas J.: Gravity and Magnetic Methods. Paper presented at conference: Short Course on Surface Exploration for Geothermal Resources, UNU-GTP and LaGeo, Ahuachapan and Santa Tecla, El Salvador, 17–30 October, 2009, https://orku- stofnun.is/gogn/unu-gtp-sc/UNU-GTP-SC-09-13a.pdf [access: 30.12.2019].
- Tchernychev M., Kulpa J., Johnson R.: Using A Transverse Marine Gradiom‑ eter (TVG) as submarine pipeline location tool. [in:] 2013 OCEANS – San Di‑ ego, San Diego, CA, 2013, pp. 1–6, https://ieeexplore.ieee.org/abstract/document/6740986 [access: 30.12.2019].
- Plets R., Dix J., Bates R.: Marine Geophysics Data Acquisition, Processing and In‑ terpretation. Guidance Notes. English Heritage, 2013, https://historicengland.org.uk/imagesbooks/publications/marine-geophysics-data-acquisition-processing-interpretation/ [access: 30.12.2019].
- Bright J. C., Conlin D., Wall S.: Marine Magnetic Survey Modeling: Custom Geo‑ spatial Processing Tools for Visualizing and Assessing Marine Magnetic Surveys for Archeological Resources. OCS Study BOEM 2014-615, Bureau of Ocean En- ergy Management, 2014.
- Bodus-Olkowska I., Uriasz J.: Segmentacja obrazu mapy anomalii magnetycznej akwenu dla celów detekcji i lokalizacji podwodnych obiektów ferromagnetycznych [Segmentation of an image of a magnetic anomaly map for the detection and location of the ferromagnetic underwater objects]. Roczniki Geomatyki – Annals of Geomatics, t. 17, z. 1(84), 2019, pp. 27–40.
- Yuheng S., Hao Y.: Image Segmentation Algorithms Overview. Computer Vision and Pattern Recognition, arXiv:1707.020512017.
- Nida M.Z., Musbah J.A.: Survey on Image Segmentation Techniques. Procedia Computer Science, vol. 65, 2015, pp. 797–806 [International Conference on Communication, Management and Information Technology (ICCMIT 2015)].
- Umaa Mageswari S, Sridevi M., Mala C.: An Experimental Study and Analysis of Different Image Segmentation Techniques. Procedia Engineering, vol. 64, 2013, pp. 36–45.
- Boustani B., Javaherian A., Nabi-Bidhendi M., Torabi S., Amindavar H.R.: Mapping channel edges in seismic data using curvelet transform and morphological filter. Journal of Applied Geophysics, vol. 160, 2019, pp. 57–68.
- Nowicki M., Szewczyk R.: Determination of the Location and Magnetic Moment of Ferromagnetic Objects Based on the Analysis of Magnetovision Measurements. Sensors, vol. 19(2), 2019, 337, https://doi.org/10.3390/s19020337.
- Grabowska T.: Magnetometria stosowana w badaniach środowiska. Tom I: Podstawy fizyczne, magnetyzm ziemski, magnetyzm środowiska. Wydawnictwa AGH, Kraków 2012.
References
Hrvoic D., Pozza M.: High‑resolution Magnetic Target Survey. Hydro Interna- tional, July/ August 2004, https://www.academia.edu/3079232/High_Resolution_Magnetic_Target_Survey [access: 30.12.2019].
Rivas J.: Gravity and Magnetic Methods. Paper presented at conference: Short Course on Surface Exploration for Geothermal Resources, UNU-GTP and LaGeo, Ahuachapan and Santa Tecla, El Salvador, 17–30 October, 2009, https://orku- stofnun.is/gogn/unu-gtp-sc/UNU-GTP-SC-09-13a.pdf [access: 30.12.2019].
Tchernychev M., Kulpa J., Johnson R.: Using A Transverse Marine Gradiom‑ eter (TVG) as submarine pipeline location tool. [in:] 2013 OCEANS – San Di‑ ego, San Diego, CA, 2013, pp. 1–6, https://ieeexplore.ieee.org/abstract/document/6740986 [access: 30.12.2019].
Plets R., Dix J., Bates R.: Marine Geophysics Data Acquisition, Processing and In‑ terpretation. Guidance Notes. English Heritage, 2013, https://historicengland.org.uk/imagesbooks/publications/marine-geophysics-data-acquisition-processing-interpretation/ [access: 30.12.2019].
Bright J. C., Conlin D., Wall S.: Marine Magnetic Survey Modeling: Custom Geo‑ spatial Processing Tools for Visualizing and Assessing Marine Magnetic Surveys for Archeological Resources. OCS Study BOEM 2014-615, Bureau of Ocean En- ergy Management, 2014.
Bodus-Olkowska I., Uriasz J.: Segmentacja obrazu mapy anomalii magnetycznej akwenu dla celów detekcji i lokalizacji podwodnych obiektów ferromagnetycznych [Segmentation of an image of a magnetic anomaly map for the detection and location of the ferromagnetic underwater objects]. Roczniki Geomatyki – Annals of Geomatics, t. 17, z. 1(84), 2019, pp. 27–40.
Yuheng S., Hao Y.: Image Segmentation Algorithms Overview. Computer Vision and Pattern Recognition, arXiv:1707.020512017.
Nida M.Z., Musbah J.A.: Survey on Image Segmentation Techniques. Procedia Computer Science, vol. 65, 2015, pp. 797–806 [International Conference on Communication, Management and Information Technology (ICCMIT 2015)].
Umaa Mageswari S, Sridevi M., Mala C.: An Experimental Study and Analysis of Different Image Segmentation Techniques. Procedia Engineering, vol. 64, 2013, pp. 36–45.
Boustani B., Javaherian A., Nabi-Bidhendi M., Torabi S., Amindavar H.R.: Mapping channel edges in seismic data using curvelet transform and morphological filter. Journal of Applied Geophysics, vol. 160, 2019, pp. 57–68.
Nowicki M., Szewczyk R.: Determination of the Location and Magnetic Moment of Ferromagnetic Objects Based on the Analysis of Magnetovision Measurements. Sensors, vol. 19(2), 2019, 337, https://doi.org/10.3390/s19020337.
Grabowska T.: Magnetometria stosowana w badaniach środowiska. Tom I: Podstawy fizyczne, magnetyzm ziemski, magnetyzm środowiska. Wydawnictwa AGH, Kraków 2012.