Tracking Underwater Noise Sources with the Use of a Passive Method

Abstract

It is possible to track a source of noise by determining the intensity of sound that informs about the sound energy ow direction. One of the methods of determining the sound intensity of acoustic signals is the so-called gradient method in which the pressure is measured with the use of two hydrophones placed close to each other. Tetrahedral antenna consists of four hydrophones spaced at regular tetrahedron vertices so that distances between hydrophones are the same. The tetrahedral antenna determines six virtual points in the middle of each edge and allows using sound intensity calculation algorithm to determine the noise source bearing. In our experiment, the antenna was located 23 meters below the sea surface and a source of noise was moving over it. The object that was moving along a straight line with a specic course was equipped with a GPS receiver. This allowed comparison of the obtained targeting results with the real track of moving object. The paper presents the object tracking algorithm which was implemented in the MATLAB environment as well as some of the results of research carried out on passive source noise tracking.

Analysing the Impact on Underwater Noise of Changes to the Parameters of a Ship’s Machinery

“…An underwater noise analysis was carried out based on measurements of a particular ship using a bottom measuring system [6,7]. The measuring circuit included a hydrophone that received signals in the range 5-120 kHz.…”

An Application of Fractional Brownian Motion to Vessel Identification Based on its Sound Spectrum

“…Obviously, by definition of fBm, both sequences determine the Hurst parameter for ideal fractional Brownian motion. It should be admitted that ship sounds may not be ideal fBm signals and consequently, the increments of v n may change their distribution, fail to satisfy (1), and not give constant H; similarly, σ k may not be constant and differ for different k. However, it is assumed that sequences given by (4) and (6) provide information essential for the vessels identification. One can observe the similarity of first-order increments sequences for three vessels presented in Fig.…”

“…On the other hand, vessel recognition is very important, particularly from the military point of view. In the literature, different methods are presented, from traditional line spectrum and average spectrum analysis, through wavelet analysis, Bayesian analysis, and neural networks, to fractal analysis [3][4][5][6]. Among a number of studies, those concerned with detection of objects buried in the sea bottom or source localization in water are important and challenging [7][8][9][10][11].…”

“…The recorded vessels sailed directly over the measuring module or close to it. The vessels' routes were recorded via AIS (Automatic Identification System) which contained information about the current position of the vessel [6].…”