Seabed Detection Using Application Of Image Side Scan Sonar Instrument (Acoustic Signal)
The importance of knowing the method for seabed detection using side-scan sonar images with sonar instrument is a much-needed requirement right now. This kind of threat also requires frequent sonar surveys in such areas. These survey operations need specific procedures and special equipment to ensure survey correctness. In this paper describes the method of observation and retrieval of marine imagery data using an acoustic signal method, to determine a target based on the sea. Side scan sonar is an instrument consisting of single beam transducer on both sides. Side scan sonar (SSS) is a sonar development that is able to show in two-dimensional images of the seabed surface with seawater conditions and target targets simultaneously. The side scan sonar data processing is performed through geometric correction to establish the actual position of the image pixel, which consists of bottom tracking, slant-range correction, layback correction and radiometric correction performed for the backscatter intensity of the digital number assigned to each pixel including the Beam Angle Correction (BAC), Automatic Gain Control (AGC), Time Varied Gain (TVG), and Empirical Gain Normalization (EGN).
Burczynski J. 2002. Bottom classification. BioSonics, Inc. www.BioSonics.com.
Burguera, A., & Oliver, G. 2016. High-resolution underwater mapping using side-scan sonar. PloS one, 11(1), e0146396.
Chang, R., Wang, Y., Hou, J., Qiu, S., Nian, R., He, B., & Lendasse, A. 2016, April. Underwater object detection with efficient shadow-removal for side scan sonar images. In OCEANS 2016-Shanghai (pp. 1-5). IEEE.
Chavez P S Jr., J Isbrecht, P Galanis, G L Gabel, S C Sides, D L Soltesz, S L Ross,M G Velasco. 2002. Processing,mosaicking and management of the Monterey Bay digital sidescan-sonar images. Marine Geology, 181: 305-315.
Dzieciuch, I., Gebhardt, D., Barngrover, C., & Parikh, K. 2016. Non-linear Convolutional Neural Network for Automatic Detection of Mine-Like Objects in Sonar Imagery. In International Conference on Applications in Nonlinear Dynamics (pp. 309-314). Springer, Cham.
Hsueh, D. Y. Development of Sidescan Sonar Image Mosaicing Software. Diss. Master Thesis, Institute Of Applied Marine Physics and Undersea Technology, National Sun Yat-sen University, Kaohsiung, Taiwan, 2007.
Kenny, A. J., Cato, I., Desprez, M., Fader, G., Schüttenhelm, R. T. E., & Side, J. 2003. An overview of seabed-mapping technologies in the context of marine habitat classification☆. ICES Journal of Marine Science, 60(2), 411-418.
Lubis, M. Z., & Anurogo, W. 2016. Fish stock estimation in Sikka Regency Waters, Indonesia using Single Beam Echosounder (CruzPro fish finder PcFF-80) with hydroacoustic survey method. Aceh Journal of Animal Science, 1(2).
Lubis, M. Z., & Manik, H. M. 2017. Acoustic systems (split beam echo sounder) to determine abundance of fish in marine fisheries. Journal of Geoscience, Engineering, Environment, and Technology, 2(1), 76-83.
Lubis, M. Z., & Pujiyati, S. 2016. Detection backscatter value of mangrove crab (Scylla sp.) using Cruzpro Fishfinder Pcff-80 hydroacoustic instrument. J Biosens Bioelectron, 7(205), 2.
Lubis, M. Z., Anggraini, K., Kausarian, H., & Pujiyati, S. 2017. Marine Seismic And Side-Scan Sonar Investigations For Seabed Identification With Sonar System. Journal of Geoscience, Engineering, Environment, and Technology, 2(2), 166-170.
Lubis, M. Z., Anurogo, W., Khoirunnisa, H., Irawan, S., Gustin, O., & Roziqin, A. 2017. Using Side-Scan Sonar instrument to Characterize and map of seabed identification target in punggur sea of the Riau Islands, Indonesia. Journal of Geoscience, Engineering, Environment, and Technology, 2(1), 1-8.
Lubis, M. Z., Wulandari, P. D., Mujahid, M., Hargreaves, J., & Pant, V. 2016. Echo Processing and Identifying Surface and Bottom Layer with Simrad Ek/Ey 500. Journal of Biosensors and Bioelectronics, 7(3), 1000212.
Lurton X. 2002. An Introduction to Underwater Acoustic. Springer, Praxis.Chichester. UK
Milkert, D., & Fiedler, H. M. (2002). Processing and mosaicking digital side scan sonar images: two examples from the western Baltic Sea. Baltica, 15, 40-48.
Rhinelander, J. 2016. Feature extraction and target classification of side-scan sonar images. In Computational Intelligence (SSCI), 2016 IEEE Symposium Series on (pp. 1-6). IEEE.
Urick, R. J. 1967. Principles of underwater sound for engineers. Tata McGraw-Hill Education.
Wentworth, C K. 1922. A Scale of Grade And Class Terms For Clastic Sediments. Journal of Geology 30: 377–392.
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Copyright @2016. This is an open-access article distributed under the terms of the Creative Commons Attribution-ShareAlike 4.0 International License which permits unrestricted use, distribution, and reproduction in any medium. Copyrights of all materials published in JGEET are freely available without charge to users or / institution. Users are allowed to read, download, copy, distribute, search, or link to full-text articles in this journal without asking by giving appropriate credit, provide a link to the license, and indicate if changes were made. All of the remix, transform, or build upon the material must distribute the contributions under the same license as the original.