Sonar Data Classification Using a New Algorithm Inspired from Black Holes Phenomenon

Sonar Data Classification Using a New Algorithm Inspired from Black Holes Phenomenon

Mohamed Elhadi Rahmani (GeCoDe Laboratory, Dr. Tahar Moulay University of Saida, Saida, Algeria), Abdelmalek Amine (GeCoDe Laboratory, Department of Computer Science, Tahar Moulay University of Saida, Algeria) and Reda Mohamed Hamou (GeCoDe Laboratory, Department of computer Science, Tahar Moulay University of Saida, Algeria)
Copyright: © 2018 |Pages: 15
DOI: 10.4018/IJIRR.2018040102
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Abstract

Sound Navigation and Ranging (Sonar) is underwater sound detection used in boats or submarines to navigate, communicate with or detect objects under the surface of water based on sound propagation. It is helpful for exploring and mapping the ocean because sound waves travel farther in the water than do radar and light waves. Based on signal data obtained from sonar, this article presents a new heuristic approach inspired from black holes' phenomenon proposed by Schwarzschild, it has been applied to the classification sonar returns from two undersea targets, a metal cylinder and a similarly-shaped rock. Results are very satisfied (almost 83% of accuracy) compared to original works. in manner that encourage to keep working on paper, the main idea of this article is to benefit from the power of nature to solve complex problems in computer science
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Introduction

The increased use of sonar and its difficulties motivated the researcher to produce cost effective and automated process for classification. The recent development of learning algorithm Gorman (Jade, 2013) and al. Networks were trained to classify sonar returns from an undersea metal cylinder and a cylindrically shaped rock. In this paper, we present a new heuristic approach inspired from black holes’ phenomenon based on distance calculation to classify these data.

Active sonar uses a sound transmitter and a receiver. When the two are in the same place, it is monostatic operation. When the transmitter and receiver are separated, it is biostatic operation. When more transmitters (or more receivers) are used, again spatially separated, it is multi-static operation. A beam former is usually employed to concentrate the acoustic power into a beam, which may be swept to cover the required search angles. Figure 1 shows the transmission and receiving process of sonar signals. (Tan, 2004)

Figure 1.

Principle of active sonar

Nature is considered as one of the most important, great and immense source of inspiration for solving hard and complex problems in computer science since it exhibits extremely diverse, dynamic, robust, complex and fascinating phenomenon. Over the last few decades, it has stimulated many successful algorithms and computational tools for dealing with complex and optimization problems. Scientist has gone long away inspiring algorithms from some space phenomenon.

This paper presents a new heuristic algorithm for underwater objects identification, it is inspired from the black hole phenomenon. The outlined of this paper is given as follow: section 2 gives a stat of the art to illustrate the relation between machine learning, heuristics and our study before giving an idea about related works in sonar data classification and black holes inspired algorithms. Section 3 presents the black hole phenomenon as Schwarzschild gave. Section 4 details the proposed approach. Finally, section 5 illustrates the used dataset and obtained results compared with other approaches.

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