Scattering of Sound

Björnö, L.

doi:10.1016/b978-0-12-811240-3.00005-9

Cited by 10 publications

(9 citation statements)

References 62 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To understand the sound scattering phenomenon in this experiment one should keep in mind that the rough surface is insonified not only by the direct arrival, but by the sound waves, propagating by various paths with surface and bottom reflections. Though sophisticated methods of computing reverberation in a shallow water waveguide exist [36,37], in practice we may still relay on the sonar equation for overall estimates [23,38,39]. The model is the following.…”

Section: Theory Backgroundmentioning

confidence: 99%

“…Since all properties, that define propagation, remain stable during the experiment, all changes in scattering levels due to weather conditions should be linked to the scattering strength (SS) parameter [38]. Chapman and Harris provided an empirical law for SS as a function of a wind speed, a frequency and other parameters [23,38]. A strong contribution of bottom scattering is expected in shallow water, so a level of Doppler side lobes in the spectrum of the scattering signal (i.e.…”

Section: Theory Backgroundmentioning

confidence: 99%

“…Small perturbation theory (SPT) gives a rather straightforward relation between the power spectral density (PSD) of the scattered signal and surface waves PSD due to Bragg resonance of sound waves with surface waves [22,23]. A measurement method was proposed by [24], directly based on this effect, but the were no report that it had ever been realized.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Surface waves prediction based on long-range acoustic backscattering in a mid-frequency range

Ermoshkin,

Kosteev,

Ponomarenko

et al. 2022

Preprint

View full text Add to dashboard Cite

New data was obtained for a frequency band that had not been so well-studied for sea surface probing applications before. During the described 2-weeks sea experiment 1-3 kHz tonal pulses were emitted from a platform, located on the northern Black Sea shelf, and Doppler spectrum of reverberation was studied. We believe that this band is worth further studying due the sound propagation range is large enough to meet practical needs in coastal zone while the angle-distance resolution is quite moderate. However it is quite difficult to interpret the obtained data since backscattering spectrum shape is influenced by a series of effects and has a complicated link to wind waves and currents parameters. Backscattering of acoustical signals was received for distances around 2 nautical miles. Significant wave height, dominant wave frequency were estimated as the result of such signals processing with the use of machine learning tools. A decision-tree-based mathematical regression model was trained to solve the inverse problem. Wind waves prediction is in a good agreement with direct measurements, made on the platform, and machine learning results allow physical interpretation.

show abstract

Section: Theory Backgroundmentioning

confidence: 99%

Section: Theory Backgroundmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Surface waves prediction based on long-range acoustic backscattering in a mid-frequency range

Ermoshkin,

Kosteev,

Ponomarenko

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…The suggested T S values for sonar system design and performance calculations are listed Table 2 [49] and the variation of the T S of a submarine with respect to the aspect direction is illustrated in Fig. 4 [50]. [24] Finding optimal solutions allowing resource control while preserving and maximizing performance for multistatic active sonobuoys in simulated non-homogeneous areas Area Coverage 2D Sonar detection Updated SCOUT program with genetic algorithm solutions [32] Determining the optimum number and placement of multistatic sonar sensors to achieve maximum coverage while minimizing the number of sensors required with a PSO-based model Area Coverage 2D Cassini oval Sequential PSO Algorithm [33] Performing analyses with sensor detection models in order to show the differences of multistatic systems compared to monostatic systems Area Coverage 2D Cassini oval Analytical model based on Cassini ovals-monostatic and multistatic detection model [34] Obtaining the best placement geometry of bistatic sonobuoys when searching for stationary and moving targets for maximizing the target detection probability Area Coverage 2D Cassini oval Analytical model based on Cassini ovals and Poisson Fields [35] To achieve maximum coverage, placement of a single source sensor for sensors with known receiver placements and investigating the effect of random and polygonal placement of receivers for different conditions.…”

Section: Preliminariesmentioning

confidence: 99%

Three Dimensional Volume Coverage in Multistatic Sonar Sensor Networks

2022

View full text Add to dashboard Cite

Recent changes in the design of enemy threats such as submarines and the technological achievements in sensor development have paved the way for multistatic sonar applications, which increase security and situational awareness in underwater tactical operations. Previously, coverage in multistatic sonar sensor networks (MSSN) was studied using Cassini ovals and the traditional sonar detection model in two dimensions without any discussion of the practicability and feasibility in terms of conditions related to the underwater acoustic propagation environment. In this study, a practical three-dimensional MSSN channel model is proposed. The proposed model covers a spectral variation of absorption loss, ambient noise, sound speed profile, and shadow zones. The realistic effects of sound propagation and environmental conditions are modeled and evaluated using Lybin, which is a well-known sonar performance prediction tool. Using the practical MSSN channel model, the number of source-receiver pairs required to cover a three-dimensional MSSN volume is calculated. The impacts of frequency, source-to-receiver distance, and source level are investigated. The results are compared to the Cassini oval and traditional sonar detection models via an error expression derived according to our verified practical model. The results reveal that the inclusion of ambient conditions and sound propagation characteristics in the channel model leads to huge error levels of 4700000% in the Cassini oval model and 170000% in the traditional sonar detection model, depending on frequency. Thus, the applicability of these models in realistic MSSN deployment scenarios is limited.

show abstract

“…Acoustic monitoring of sea areas, observation of the underwater situation, control of underwater vehicles, including of unmanned-type and a number of other applied problems require highly sensitive means of registering weak hydroacoustic signals [1,2]. Such problems are usually solved by using both classical hydroacoustic sensors based on electrical transducers (piezoelectric, electrodynamic, capacitive, etc) and currently developing fiber-optic sensors [3,4]. Using interferometry principles the for fiber-optic sensors signal processing makes it possible to detecting ultraweak signals due to potentially high sensitivity of optical * Author to whom any correspondence should be addressed.…”

Section: Introductionmentioning

confidence: 99%

Fiber-optic vector acoustic receiver based on adaptive holographic interferometer

Romashko¹,

Storozhenko²,

Bezruk³

et al. 2022

Laser Phys.

View full text Add to dashboard Cite

A mobile scalar–vector acoustic receiver is proposed, experimentally implemented and investigated. The key components of the receiver are (a) the six-channel fiber-optic coil-type sensor configured as to detect three projections of acoustic intensity vector, (b) the six-channel optical phase demodulator based on six-channel adaptive holographic interferometer configured with use of dynamic holograms multiplexed in a photorefractive crystal of cadmium telluride and (c) the signals recording ADC-based system combined with software package for data processing. Field tests of the developed receiver applied for obtaining scalar and vector parameters of acoustic waves generated by a stationary and moving acoustic source in open air and water area are carried out. Experimental results show perceptiveness of use of the fiber-optical adaptive interferometry system for bearing of weak acoustic sources in real conditions.

show abstract

Scattering of Sound

Cited by 10 publications

References 62 publications

Surface waves prediction based on long-range acoustic backscattering in a mid-frequency range

Surface waves prediction based on long-range acoustic backscattering in a mid-frequency range

Three Dimensional Volume Coverage in Multistatic Sonar Sensor Networks

Fiber-optic vector acoustic receiver based on adaptive holographic interferometer

Contact Info

Product

Resources

About