On whether azimuthal isotropy and alongshelf translational invariance are present in low-frequency acoustic propagation along the New Jersey shelfbreak

Lynch, James F.; Emerson, Chris; Abbot, Philip; Gawarkiewicz, Glen; Newhall, Arthur E.; Lin, Ying‐Tsong; Duda, Timothy F.

doi:10.1121/1.3672644

Cited by 6 publications

(2 citation statements)

References 27 publications

(23 reference statements)

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“…This follows up an earlier experimentally-based QPE paper on acoustic TL variability in a different canyon (Chiu et al, 2011). The second article (Emerson et al, 2013), shows that 800-1000 Hz acoustic signals traveling up to 10 km were measured to have short-term TL variability of 1.5 to 2 dB, which is perhaps a bit less than measured in SW06 (Lynch et al, 2012). Combined with noise variability in the area of up to 6 dB rms, the signal excess for underwater sound in the area is expected to have a greater than 6 dB rms variability.…”

Section: Shallow-water Effort Qpesupporting

confidence: 66%

Experimentally-Based Ocean Acoustic Propagation and Coherence Studies

Duda¹

2013

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The goal is to better understand fluctuating sound propagation in two distinct ocean acoustic regimes: Stratified shallow water, where sound is highly bottom interacting, and the temperate deep-ocean sound channel. Acoustic field fluctuations have time scales varying from less than a minute to hours, and horizontal spatial scales from tens of meters to kilometers, comparable to processing time scales and system spatial scales, and thus impact exploitation of underwater sound. With proper understanding, reliable predictions of temporal and spatial variability of received underwater sound may be possible, thus improving processing and handling of signals of interest. Processing could include remediation of signal degradation and/or exploitation of available sonic information. OBJECTIVES An objective is to quantify and explain underwater sound fluctuation behavior that has been observed in both shallow and deep regimes, for the purpose of meeting the stated goals. For shallow water, transmission loss and phase data are available at frequencies from 50 to 3000 Hz. For the deep-ocean sound channel, data are in hand for propagation at 50 to 100 Hz over 100's to 1000's of kilometers. Propagation and forward scattering models, both theoretical and computational, will be used to test hypotheses regarding the origin of signal variations. Therefore, making better models is a second (enabling) objective. APPROACH The approach toward understanding the fundamentals of ocean sound propagation variability in numerous environmental regimes is to study the propagation together with the local environmental conditions. First, acoustically important features, such as nonlinear internal waves in the shallow seas and quasi-homogeneous internal waves in the deep seas, must be identified in the coupled studies. Next, the acoustic phenomena caused by those features are studied in detail, to identify the feature properties that are relevant to acoustics. Next, those properties are investigated, with a purpose of extrapolating (predicting) acoustic behavior in parameter regimes that may not have been encountered. The investigations of physical ocean phenomena that are critical to this approach are likely to differ from studies of the features motivated by other branches of ocean science, such as studies of biogeochemical/physical cycling, fisheries, or climate.

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Section: Shallow-water Effort Qpesupporting

confidence: 66%

Experimentally-Based Ocean Acoustic Propagation and Coherence Studies

Duda¹

2013

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“…The directionality of the waves was also measured from satellite images of surface-roughness internalwave signatures [18]. The background environment through which the internal waves propagated featured the shelf/slope water front [19] which can heavily influence sound propagation by placing warm salty near the seabed, thereby refracting sound away from the seabed and causing soundchannel ducting.…”

Section: A Environmental Measurementsmentioning

confidence: 99%

Time-evolving acoustic propagation modeling in a complex ocean environment

Colin

Duda

Raa

et al. 2013

2013 MTS/IEEE OCEANS - Bergen

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Abstract-During naval operations, sonar performance estimates often need to be computed in-situ with limited environmental information. This calls for the use of fast acoustic propagation models. Many naval operations are carried out in challenging and dynamic environments. This makes acoustic propagation and sonar performance behavior particularly complex and variable, and complicates prediction. Using data from a field experiment, we have investigated the accuracy with which acoustic propagation loss (PL) can be predicted, using only limited modeling capabilities. Environmental input parameters came from various sources that may be available in a typical naval operation.The outer continental shelf shallow-water experimental area featured internal tides, packets of nonlinear internal waves, and a meandering water mass front. For a moored source/receiver pair separated by 19.6 km, the acoustic propagation loss for 800 Hz pulses was computed using the peak amplitude. The variations in sound speed translated into considerable PL variability of order 15 dB. Acoustic loss modeling was carried out using a data-driven regional ocean model as well as measured sound speed profile data for comparison. The acoustic model used a two-dimensional parabolic approximation (vertical and radial outward wavenumbers only). The variance of modeled propagation loss was less than that measured. The effect of the internal tides and sub-tidal features was reasonably well modeled; these made use of measured sound speed data. The effects of nonlinear waves were not well modeled, consistent with their known three-dimensional effects but also with the lack of measurements to initialize and constrain them.

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