Scattering from extended targets in range-dependent fluctuating ocean-waveguides with clutter from theory and experiments

Abstract

Bistatic, long-range measurements of acoustic scattered returns from vertically extended, air-filled tubular targets were made during three distinct field experiments in fluctuating continental shelf waveguides. It is shown that Sonar Equation estimates of mean target-scattered intensity lead to large errors, differing by an order of magnitude from both the measurements and waveguide scattering theory. The use of the Ingenito scattering model is also shown to lead to significant errors in estimating mean target-scattered intensity in the field experiments because they were conducted in range-dependent ocean environments with large variations in sound speed structure over the depth of the targets, scenarios that violate basic assumptions of the Ingenito model. Green's theorem based full-field modeling that describes scattering from vertically extended tubular targets in range-dependent ocean waveguides by taking into account nonuniform sound speed structure over the target's depth extent is shown to accurately describe the statistics of the targets' scattered field in all three field experiments. Returns from the man-made targets are also shown to have a very different spectral dependence from the natural target-like clutter of the dominant fish schools observed, suggesting that judicious multi-frequency sensing may often provide a useful means of distinguishing fish from man-made targets.

Maximum Likelihood Deconvolution of Beamformed Images with Signal-Dependent Speckle Fluctuations from Gaussian Random Fields: With Application to Ocean Acoustic Waveguide Remote Sensing (OAWRS)

“…Given these statistics, the ML estimator is then derived to resolve the angular distribution of incident plane waves from coherent array measurements. We focus on OAWRS applications [4][5][6]11,13,14] where side lobes are sufficiently low such that distinct beams are statistically independent of each other and far field signal and noise sources dominate. Many past statistical models for beamforming in the ocean [16][17][18][19][20][21] are less well suited to OAWRS applications, because they assume deterministic signals that are inconsistent with observations and additive noise with spatial correlations that are inconsistent with nonuniform far field origins.…”

“…We take advantage of the relatively pervasive circular complex Gaussian random (CCGR) statistics of acoustic fields in the ocean that follow from the central limit theorem for many typical scenarios of propagation, radiation or scattering [4][5][6][8][9][10][11][12][13][14]. Instantaneous intensity then follows a negative exponential distribution with a standard deviation proportional to the mean [9].…”

Vocalization Source Level Distributions and Pulse Compression Gains of Diverse Baleen Whale Species in the Gulf of Maine

“…It is also verified by roughly one hundred two-way transmission loss measurements made from calibrated targets with known scattering properties [59] during the same experiment at the same time and location, indicating that our transmission loss measurements did not create a bias. Therefore, the observed difference between this study and previous ones is not likely caused by biased transmission loss measurements.…”

“…The water-column temperature and salinity were measured using Expendable Bathythermographs (XBTs) and Conductivity-Temperature-Depth (CTD) sensors. Other details about the measurement geometry and oceanographic properties of the environment are provided in Section II of [16] and also in [1,2,17,22,23,41,59,64].…”

Feasibility of Acoustic Remote Sensing of Large Herring Shoals and Seafloor by Baleen Whales

“…Parabolic equation transmission loss modeling [32] was calibrated and verified with roughly one hundred two-way transmission loss measurements made from calibrated targets with known scattering properties [37] and thousands of one-way transmission loss measurements [24,36] during the same experiment. Herring target strength was determined by empirical fit to a resonance model [31] over multi-frequencies in ranges relevant to this study [24].…”