Acoustic Signal Processing for Seabed Layer Identification
V. Sunanthini1, Gunaselvi Manohar2, R. Sudha3, Pearley Stanley4, Lakshmi R5
1V Sunanthini, Department of Electronics and Instrumentation Engineering, Easwari Engineering College, (Tamil Nadu), India.
2Gunaselvi Manohar, Department of Electronics and Instrumentation Engineering, Easwari Engineering College, (Tamil Nadu), India.
3Sudha R, Department of Electronics and Instrumentation Engineering, Easwari Engineering College, (Tamil Nadu), India.
4Pearley Stanley, Department of Electronics and Instrumentation Engineering, Easwari Engineering College, (Tamil Nadu), India.
5Lakshmi R, Department of Electronics and Instrumentation Engineering, Easwari Engineering College, (Tamil Nadu), India.
Manuscript received on 04 October 2019 | Revised Manuscript received on 18 October 2019 | Manuscript Published on 26 December 2019 | PP: 77-80 | Volume-8 Issue-12S October 2019 | Retrieval Number: L102410812S19/2019©BEIESP | DOI: 10.35940/ijitee.L1024.10812S19
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this critique, chirp sonar signals are processed to classify the bottom sediments. Composed sonar data are sorted and reported. Reproduced and imitated data obtained by sonar parametric analysis is done for target categorization. This paper presents the functions of the duration made by echoes are qualified and separated. Hilbert transform is related with the spreader resound signals to estimate the degree of the underneath desire reactions.
Keywords: Seabed Categorization, Hilbert Transforms Chirp Signals, Beam Echo Sounders (SBES), Echo Duration.
Scope of the Article: Digital Signal Processing Theory