The Influence of Positional Parameters on the Effect of a Noise-Jammer Based on Broadband Acoustic Propagation Model

2013 ◽  
Vol 791-793 ◽  
pp. 2043-2047
Author(s):  
Kang Le Miao ◽  
Ri Jie Yang ◽  
Xiong Xiong ◽  
Jian Hui Han
Keyword(s):  
Normal Mode ◽  
Fourier Transformation ◽  
Accurate Result ◽  
Transmission Loss ◽  
Spherical Wave ◽  
Acoustic Propagation ◽  
Propagation Model ◽  
Discrete Fourier Transformation ◽  
Approximate Evaluation ◽  
Long Time

In a long time, the specialists in underwater acoustic countermeasure field were used to get an approximate evaluation of the transmission loss of noise signals by spreading loss equation of spherical wave, which led to results with a low accurateness. Based on normal mode theories and discrete Fourier transformation (DFT), derived the composition and process of the broadband acoustic propagation model. Then the transmission loss could be calculated via this propagation model, which could get a relatively more accurate result. The influence of three key positional parameters, the orientation, distance and depth of the noise-jammer were studied in this paper. The method and conclusions in this paper can provide a reliable foundation for tactical research on noise-jammers.

Flow-dependent modeling of acoustic propagation based on DG-FEM method

2021 ◽  
Author(s):  
Zichen Wang ◽  
Jian Xu ◽  
Xuefeng Zhang ◽  
Can Lu ◽  
Kangkang Jin ◽  
...  
Keyword(s):  
Sound Propagation ◽  
Transmission Loss ◽  
Acoustic Propagation ◽  
Water Area ◽  
Current Speed ◽  
Propagation Model ◽  
Propagation Loss ◽  
Two Dimensional ◽  
Underwater Sound ◽  
Ocean Environment

AbstractThis paper proposes a two-dimensional underwater sound propagation model using the Discontinuous Galerkin Finite Element Method (DG-FEM) to investigate the influence of current on sound propagation. The acoustic field is calculated by the convected wave equation with the current speed parameter. Based on the current speed data from an assimilation model, a two-dimensional coupled acoustic propagation model in the Fram Strait water area is established to observe the variability in propagation loss under different seasonal velocities in the real ocean environment. The transmission loss and signal time structure are examined. The results obtained in different source frequencies are also compared. It appears that the current velocity, time and range variation all have an effect on underwater sound propagation.

Modeled acoustic propagation through a measured large-amplitude nonlinear internal wave in northern South China Sea

2020 ◽  
Author(s):  
Peng Qi
Keyword(s):  
South China Sea ◽  
Internal Waves ◽  
South China ◽  
Large Amplitude ◽  
Sound Propagation ◽  
Transmission Loss ◽  
Northern South China Sea ◽  
Acoustic Propagation ◽  
Propagation Model ◽  
China Sea

<p>Preliminary results are presented from an analysis of modeled mid-frequency sound propagation through a measured large-amplitude nonlinear internal solitary wave, and in-situ measurements of trains of nonlinear internal waves in northern South China Sea (SCS) as well. An acoustic propagation model based on ray theory was utilized to compute the transmission loss (TL) associated with passing the large depression measured internal waves. The TL was computed using the model considering (1) range-dependent and range-independent environmental scenario and (2) for different source and receiver depth configurations. This presentation will propose several interesting aspects of influence of internal waves on acoustic propagation, including "shadow zones", with or without eddy, etc.</p>

scholarly journals Optimal Perturbations of an Oceanic Vortex Lens

Fluids ◽  
2018 ◽  
Vol 3 (3) ◽  
pp. 63 ◽  
Author(s):  
Thomas Meunier ◽  
Claire Ménesguen ◽  
Xavier Carton ◽  
Sylvie Le Gentil ◽  
Richard Schopp
Keyword(s):  
Normal Mode ◽  
Growth Rates ◽  
Time Interval ◽  
Time Intervals ◽  
Horizontal Structure ◽  
Azimuthal Wave ◽  
Wave Numbers ◽  
Non Linear ◽  
Long Time ◽  
Short Time

The stability properties of a vortex lens are studied in the quasi geostrophic (QG) framework using the generalized stability theory. Optimal perturbations are obtained using a tangent linear QG model and its adjoint. Their fine-scale spatial structures are studied in details. Growth rates of optimal perturbations are shown to be extremely sensitive to the time interval of optimization: The most unstable perturbations are found for time intervals of about 3 days, while the growth rates continuously decrease towards the most unstable normal mode, which is reached after about 170 days. The horizontal structure of the optimal perturbations consists of an intense counter-shear spiralling. It is also extremely sensitive to time interval: for short time intervals, the optimal perturbations are made of a broad spectrum of high azimuthal wave numbers. As the time interval increases, only low azimuthal wave numbers are found. The vertical structures of optimal perturbations exhibit strong layering associated with high vertical wave numbers whatever the time interval. However, the latter parameter plays an important role in the width of the vertical spectrum of the perturbation: short time interval perturbations have a narrow vertical spectrum while long time interval perturbations show a broad range of vertical scales. Optimal perturbations were set as initial perturbations of the vortex lens in a fully non linear QG model. It appears that for short time intervals, the perturbations decay after an initial transient growth, while for longer time intervals, the optimal perturbation keeps on growing, quickly leading to a non-linear regime or exciting lower azimuthal modes, consistent with normal mode instability. Very long time intervals simply behave like the most unstable normal mode. The possible impact of optimal perturbations on layering is also discussed.

Generation of Wave-Field Time Histories by the Modulated Discrete Fourier Transformation

2003 ◽  
Author(s):  
Yousun Li
Keyword(s):  
Wave Field ◽  
Fourier Transformation ◽  
Time Instant ◽  
Discrete Fourier Transformation ◽  
Fast Fourier Transformation ◽  
Structural Members ◽  
Random Waves ◽  
Offshore Structure ◽  
Time Histories ◽  
The Time Domain

In the time domain simulation of the response of an offshore structure under random waves, the time histories of the wave field should be generated as the input to the dynamic equations. Herein the wave field is the wave surface elevation, the water particle velocities and accelerations at structural members. The generated time histories should be able to match the given wave-field spectral descriptions, to trace the structural member motions if it is a compliant offshore structure, and be numerically efficient. Most frequently used generation methods are the direct summation of a limited number of cosine functions, the Fast Fourier Transformation, and the digital filtering model. However, none of them can really satisfy all the above requirements. A novel technique, called the Modulated Discrete Fourier Transformation, has been developed. Under this method, the wave time histories at each time instant is a summation of a few time-varying complex functions. The simulated time histories have continuous spectral density functions, and the motions of the structural members are well included. This method seems to be superior to all the conventional methods in terms of the above mentioned three requirements.

scholarly journals Comparison of delayless digital filtering algorithms and their application to multi-sensor signal processing

2018 ◽  
Vol 41 (8) ◽  
pp. 2338-2351 ◽  
Author(s):  
Anna Swider ◽  
Eilif Pedersen
Keyword(s):  
Signal Processing ◽  
Fourier Transformation ◽  
Filter Design ◽  
Real Life ◽  
Digital Filtering ◽  
Data Preprocessing ◽  
Sensor Data ◽  
Discrete Fourier Transformation ◽  
Filtering Algorithms ◽  
Multiple Sensors

In the phase of industry digitalization, data are collected from many sensors and signal processing techniques play a crucial role. Data preprocessing is a fundamental step in the analysis of measurements, and a first step before applying machine learning. To reduce the influence of distortions from signals, selective digital filtering is applied to minimize or remove unwanted components. Standard software and hardware digital filtering algorithms introduce a delay, which has to be compensated for to avoid destroying signal associations. The delay from filtering becomes more crucial when the analysis involves measurements from multiple sensors, therefore in this paper we provide an overview and comparison of existing digital filtering methods with an application based on real-life marine examples. In addition, the design of special-purpose filters is a complex process and for preprocessing data from many sources, the application of digital filtering in the time domain can have a high numerical cost. For this reason we describe discrete Fourier transformation digital filtering as a tool for efficient sensor data preprocessing, which does not introduce a time delay and has low numerical cost. The discrete Fourier transformation digital filtering has a simpler implementation and does not require expert-level filter design knowledge, which is beneficial for practitioners from various disciplines. Finally, we exemplify and show the application of the methods on real signals from marine systems.

scholarly journals Multiplication of Polynomials using Discrete Fourier Transformation

2006 ◽  
Vol 14 (4) ◽  
pp. 121-128
Author(s):  
Krzysztof Treyderowski ◽  
Christoph Schwarzweller
Keyword(s):  
Fourier Transformation ◽  
Discrete Fourier Transformation ◽  
Vandermonde Matrices ◽  
Univariate Polynomials

Multiplication of Polynomials using Discrete Fourier Transformation In this article we define the Discrete Fourier Transformation for univariate polynomials and show that multiplication of polynomials can be carried out by two Fourier Transformations with a vector multiplication in-between. Our proof follows the standard one found in the literature and uses Vandermonde matrices, see e.g. [27].

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