A simple relationship between frequency and range averages for broadband sonar

Harrison, Chris H.; Harrison, Joel A.

doi:10.1121/1.412172

Cited by 50 publications

(23 citation statements)

References 4 publications

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“…The beam then interacts with the surface and bottom a few times before stripped away by the shoaling bathymetry. Note that the "intermediate modes" (10)(11)(12)(13)(14)(15)(16)(17)(18)(19) are not excited initially and, at this calm instant, mode couplings are activated primarily by the range-dependent bathymetry. The two relatively abrupt changes in the bathymetry, one close to the source and one at the shelfbreak, tend to transfer energy from higher to lower modes.…”

Section: Modeling Resultsmentioning

confidence: 99%

“…To quickly synthesize the effects of the signal bandwidth, the SIL displayed in Fig. 15 was computed from local range averages of the squared pressures modeled at the carrier frequency [15]. Similarly, these model results show that right before 08:00 (a period of calm), the acoustic energy is trapped in the lower layer (below 70 m), but right after the entrance of solitons, the infusions of low-and high-mode energy into the intermediate modes that span the entire water column begin.…”

Section: Modeling Resultsmentioning

confidence: 99%

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Acoustic Intensity Fluctuations Induced by South China Sea Internal Tides and Solitons

Chiu

Ramp

Miller

et al. 2004

IEEE J. Oceanic Eng.

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Abstract-Between late April and May 23, 2001, a suite of acoustic and oceanographic sensors was deployed by a team of U.S., Taiwan, and Singapore scientists in the northeastern South China Sea to study the effects of ocean variability on low-frequency sound propagation in a shelfbreak environment. The primary acoustic receiver was an L-shaped hydrophone array moored on the continental shelf that monitored a variety of signals transmitted along and across the shelfbreak by moored sources. This paper discusses and contrasts the fluctuations in the 400-Hz signals transmitted across the shelfbreak and measured by the vertical segment of the listening array on two different days, one with the passage of several huge solitons that depressed the shallow isotherms to near the sea bottom and one with a much less energetic internal wavefield. In addition to exhibiting large and rapid temporal changes, the acoustic data show a much more vertically diffused sound intensity field as the huge solitons occupied and passed through the transmission path. Using a space-time continuous empirical sound-speed model based on the moored temperature records, the observed acoustic intensity fluctuations are explained using coupled-mode physics.

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Section: Modeling Resultsmentioning

confidence: 99%

Section: Modeling Resultsmentioning

confidence: 99%

Acoustic Intensity Fluctuations Induced by South China Sea Internal Tides and Solitons

Chiu

Ramp

Miller

et al. 2004

IEEE J. Oceanic Eng.

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show abstract

“…In essence, the level of a broadband signal at a receiver can be viewed as if it were sampled at a number of points over some distance interval relative to its distance from the source. As stated by Harrison & Harrison (1995), a broadband signal of mean frequency (ƒ 0 ) and bandwidth (W) can be viewed as if its RL were sampled at a number of points over a distance interval (R INT ) relative to a distance (R 0 ) such that…”

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confidence: 99%

Acoustic masking in marine ecosystems: intuitions, analysis, and implication

Clark¹,

Ellison²,

Southall³

et al. 2009

Mar. Ecol. Prog. Ser.

499

369

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Acoustic masking from anthropogenic noise is increasingly being considered as a threat to marine mammals, particularly low-frequency specialists such as baleen whales. Low-frequency ocean noise has increased in recent decades, often in habitats with seasonally resident populations of marine mammals, raising concerns that noise chronically influences life histories of individuals and populations. In contrast to physical harm from intense anthropogenic sources, which can have acute impacts on individuals, masking from chronic noise sources has been difficult to quantify at individual or population levels, and resulting effects have been even more difficult to assess. This paper presents an analytical paradigm to quantify changes in an animal's acoustic communication space as a result of spatial, spectral, and temporal changes in background noise, providing a functional definition of communication masking for free-ranging animals and a metric to quantify the potential for communication masking. We use the sonar equation, a combination of modeling and analytical techniques, and measurements from empirical data to calculate time-varying spatial maps of potential communication space for singing fin (Balaenoptera physalus), singing humpback (Megoptera novaeangliae), and calling right (Eubalaena glacialis) whales. These illustrate how the measured loss of communication space as a result of differing levels of noise is converted into a time-varying measure of communication masking. The proposed paradigm and mechanisms for measuring levels of communication masking can be applied to different species, contexts, acoustic habitats and ocean noise scenes to estimate the potential impacts of masking at the individual and population levels.

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“…The images show power difference features over a broad range of scale lengths. Sometimes range-averaging algorithms are applied to fields, such as in Figures 1 and 2, to give results that are representative of what one would expect for a broadband acoustic signal (Harrison and Harrison 1995). Acoustic systems with broadfrequency bandwidth will show variation in the field spatial structure over the band, a fact that must be taken into account.…”

Section: Illustrative Example: Sound In Internal Tidal Wavesmentioning

confidence: 99%

Modeling and Forecasting Ocean Acoustic Conditions

Duda¹

2017

j mar res

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Modeling acoustic conditions in an oceanic environment is a multiple-step process. The environmental conditions (features) in the area first must be measured or estimated; relevant features include seabed geometry, seabed composition, and four-dimensionally (4D) variable sound-speed and density variations related to evolving or wave motions. Often the dynamical wave modeling depends on first obtaining correct seabed and mean stratification conditions (for example, nonlinear internal wave modeling). Next, this information must be included in sound propagation modeling. A selection of the many methods and tools available for these tasks are described, with a focus on modeling sounds of 20 to 1000 Hz propagating through water-column features that are time-dependent and variable in three dimensions (i.e., 4D variable). An example of a 3D parabolic equation acoustic calculation shows how variability caused by evolving internal tidal waves affects sound propagation. Different propagation and scattering regimes are discussed, including the theoretically delineated weak scattering and strong scattering regimes, as well as the empirically examined regime found in nonlinear internal waves. The histories and the current state of our oceanographic knowledge (the input to acoustic modeling) and of our ability to effectively model complex acoustic conditions are discussed. Example acoustic simulation applications are also discussed; these are ocean acoustic tomography, coherence prediction, and signal-to-noise ratio prediction. Types of ocean models and acoustic models and how they are interfaced are also examined. These include deterministic, statistical analytic feature models.

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A simple relationship between frequency and range averages for broadband sonar

Cited by 50 publications

References 4 publications

Acoustic Intensity Fluctuations Induced by South China Sea Internal Tides and Solitons

Acoustic Intensity Fluctuations Induced by South China Sea Internal Tides and Solitons

Acoustic masking in marine ecosystems: intuitions, analysis, and implication

Modeling and Forecasting Ocean Acoustic Conditions

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