A computational Bayesian approach for localizing an acoustic scatterer in a stratified ocean environment.

A computational Bayesian method is presented for inference regarding the state of a submerged mobile object. The approach addresses the challenge of closely spaced multipath arrivals in refractive environments with uncertainty in ambient acoustic noise power. Vertical angles and Doppler frequencies of the arrival returns are jointly inferred and their posterior density is mapped to the object's range, depth, and speed through acoustic ray interpolation. The object is localized under the challenging constraint of a small receive vertical aperture. A case study with the classic Munk sound speed profile is presented to lend credence to the approach.

Demonstration of a quasi-monostatic autonomous underwater vehicle based high duty cycle active sonar.

The feasibility of resolving target returns within receive signals collected by a continuously transmitting quasi-monostatic, broadband, autonomous underwater vehicle (AUV) based sonar is explored. Theoretical studies supported by experimental results suggest that it is possible to capture the source-to-receiver coupling response and target scattering with sufficient fidelity during the continuous transmission to enable detection and (potentially) classification processing. Demonstrations focused upon the detection of a bottomed target object at sea using transmit signals with duty cycles of 60% and 100% indicate that such an approach is feasible for a representative AUV-based side looking sonar system operating in shallow water.

Introduction to the Special Issue on Acoustic Source Localization.

Spatial localization based on acoustic observations is a rich field of interest in acoustic signal analysis. This special issue takes a close look at the diverse and growing range of problems in this area and the broad perspectives and methodologies that are presently being developed to solve them. The collection of articles presents recent advances in localization in complex and uncertain environments across a wide range of acoustic disciplines, from animal bioacoustics and acoustic signal processing in underwater environments to in air environments, architectural acoustics, and acoustic transduction.

Sparse broadband time varying acoustic response modeling and estimation from an undersampled vertical array with application to underwater communications.

Sparse broadband time varying acoustic response functions associated with horizontally stratified environments can be well estimated from an undersampled vertical array. The sparsity of the arrivals here is captured by means of a two component Gaussian mixture model. The implied posterior expectation of the bifrequency function serves to attenuate low amplitude non-coherent arrivals while leaving coherent arrivals at the array unchanged. This estimate of the acoustic response specifies a time varying increment operator that unravels the time varying motion between the source and receiver array allowing for a further sparsification of the response. This additional improved sparsity allows for improved coherent multipath combining at the receiver. The model is applied to a three element vertical array during a set of broadband acoustic observations in the shallow waters of Buzzard's Bay, MA. M-ary orthogonal spread spectrum acoustic transmissions at 32.5 kHz center frequency and 25 kHz bandwidth are considered. With M = 4, throughput rates of 95 bps are tested. At 2 km and at a receive signal-to-noise ratio per element of -15.5 dB, a 3 element undersampled vertical array achieved bit error rates less than 10-5.

Detection of an undersea acoustic communications network by an energy detector.

A theory is presented for the upper bound on the mean time τ to the detection of an undersea acoustic communications network by an energy detector whose initial position and heading are uniformly distributed random variables. The network is an infinite square grid of omnidirectional transmit-receive nodes on a flat bottom. Each node transmits to one nearest neighbor at a bit-rate R equal to Shannon's capacity, maximizing τ. The network sets a signaling bandwidth W and node-spacing D. The detector sets a false-alarm rate, integration time, height above the bottom, and speed. For W = 5 kHz and D = 1 km, τ is computed as a function of R in 200 -m water with propagation varying from spherical to cylindrical spreading, volume absorption of 2 dB per km (corresponding approximately to 15 kHz), and illustrative values for other parameters.

Evidence in support of Gaussian mixture models for sparse time varying ocean acoustic response functions.

A hierarchical Gaussian mixture model has been proposed to characterize sparse space-time varying shallow water acoustic response functions [Gendron, J. Acoust. Soc. Am. 139, 1923-1937 (2016)]. Considered here is an extension of this model to a uniform linear vertical array in order to provide an empirical validation of the mixture model for receivers of small aperture. An acoustic environment between source and moving receiver is predicated on a small proportion of relatively coherent paths obeying an ensemble frequency-angle-Doppler distribution. Provided are quantile-quantile plots of the discrete mixture model versus the empirical channel coefficients that lend credence to its use as a sparse model for acoustic response functions.

Shallow water acoustic response and platform motion modeling via a hierarchical Gaussian mixture model.

A hierarchical Gaussian mixture model is proposed to characterize shallow water acoustic response functions that are time-varying and sparse. The mixture model is based on the assumption that acoustic paths can be partitioned into two sets. The first is a relatively coherent set of arrivals that on average exhibit Doppler spreading about a mean Doppler and the remaining set is of multiple surface scattered paths that exhibit a spectrally flat Doppler. The hierarchy establishes constraints on the parameters of each of these Gaussian models such that coherent components of the response are both sparse and in the ensemble obey the Doppler spread profile. This is accomplished with a Bernoulli model that indicates the ensonification state of each element in the bi-frequency representation of the acoustic response function. Estimators of the time-varying acoustic response for the full duration of a broadband transmission are developed and employed to compensate for the shared time-varying dilation process among the coherent arrivals. The approach ameliorates response coherence degradation and can be employed to enhance coherent multi-path combining and is a useful alternative to time recursive estimation. The model is tested with acoustic communication recordings taken in shallow water at low signal-to-noise ratios.