Multipath Sound Propagation Research Articles

Bayesian passive acoustic tracking of a cooperative moving source in shallow water

This study addresses the problem of tracking acoustically a moving source in shallow water, which is challenged by multi-path sound propagation. A specific source of interest is an autonomous underwater vehicle with periodic sound transmissions. Given a simple horizontal linear receiving array, the authors develop a Bayesian tracking method based on measurements of signal arriving angle and difference of respective sonar transmission and receiving time intervals. To counter the multi-path effect and thus improve estimation accuracy of time differences, passive time reversal processing is exploited. Further, the unscented Kalman filter is adopted in tracking to handle nonlinearity in measurements. The proposed method is tested in simulations as well as an at-sea experiment, and the results validate the effectiveness of the developed approach.

Broadband sparse-array blind deconvolution using frequency-difference beamforming

Synthetic time reversal (STR) is a technique for blind deconvolution of receiving-array recordings of sound from an unknown source in an unknown multipath environment. It relies on generic features of multipath sound propagation. In prior studies, the pivotal ingredient for STR, an estimate of the source-signal's phase (as a function of frequency ω), was generated from conventional beamforming of the received-signal Fourier transforms, P(j)(ω), 1 ≤ j ≤ N, where N is the number of array elements. This paper describes how STR is implemented even when the receiving-array elements are many wavelengths apart and conventional beamforming is inadequate. Here, the source-signal's phase is estimated by beamforming P(j)(*)(ω(1))P(j)(ω(2)) at the difference frequency ω(2) - ω(1). This extension of STR is tested with broadband signal pulses (11-19 kHz) and a vertical 16-element receiving array having a 3.75-m-spacing between elements using simple propagation simulations and measured results from the FAF06 experiment involving 2.2 km of down slope propagation from 46 to 92 m water depth. The cross-correlation coefficient between the source-broadcast and STR-reconstructed-signal waveforms for the simulations and experiments are 98% and 91%-92%, respectively. In addition, frequency-difference beamforming can be used to determine signal-path-arrival angles that conventional beamforming cannot.

Blind deconvolution for robust signal estimation and approximate source localization

Synthetic time reversal (STR) is a technique for blind deconvolution in an unknown multipath environment that relies on generic features (rays or modes) of multipath sound propagation. This paper describes how ray-based STR signal estimates may be improved and how ray-based STR sound-channel impulse-response estimates may be exploited for approximate source localization in underwater environments. Findings are based on simulations and underwater experiments involving source-array ranges from 100 m to 1 km in 60 -m-deep water and chirp signals with a bandwidth of 1.5-4.0 kHz. Signal estimation performance is quantified by the correlation coefficient between the source-broadcast and the STR-estimated signals for a variable number N of array elements, 2 ≤ N ≤ 32, and a range of signal-to-noise ratio (SNR), -5 dB ≤ SNR ≤ 30 dB. At high SNR, STR-estimated signals are found to have cross-correlation coefficients of ∼90% with as few as four array elements, and similar performance may be achieved at a SNR of nearly 0 dB with 32 array elements. When the broadband STR-estimated impulse response is used for source localization via a simple ray-based backpropagation scheme, the results are less ambiguous than those obtained from conventional broadband matched field processing.

Refraction corrections in source localization with an elevated acoustic sensor array in the 2007 Yuma experiment.

Performance of ground based acoustic sensor arrays for source detection is limited by several factors, including sound reflections by obstacles, irregular terrain, multipath sound propagation, absorption of sound waves in the ground, and formation of an acoustic shadow zone in the upwind direction. These shortcomings can be overcome by suspending acoustic sensor arrays below tethered aerostats. A comprehensive experiment in source localization was carried out in October of 2007 near Yuma, AZ. A sensor array was suspended below an aerostat, and ray refraction corrections were calculated for the apparent source coordinates. Significant bias errors in the source coordinates were found if a straight‐line approximation for sound propagation in the atmosphere is used. However, by taking into account refraction of sound signals due to vertical profiles of temperature and wind velocity, it is possible to significantly reduce the localization errors even with a rough approximation of these meteorological profiles. If actual profiles were used in refraction corrections, localization errors would probably be further reduced.

Estimation of wavefront arrival delay for acoustical signals using the cross-power spectrum phase technique

In order to provide spatially selective sound capture in a teleconferencing environment, microphone array systems require accurate determination of the location of the desired source. Sound source location in turn relies on estimating time delay of arrival (TDOA) of a sound wavefront across a given microphone sensor pair. The cross-power spectrum phase (CPSP) method [M. Omologo and P. Svaizer, ICASSP 94] may be used for TDOA estimation. It is desirable to operate microphone array systems in untreated acoustical environments. Such an environment may produce multipath sound propagation and may contain moderate sources of interfering noise. The TDOA estimates computed using CPSP may become unreliable in such an environment. A strategy is presented to extract reliable TDOA information from the CPSP algorithm. The following measures are included: spectral weighting of the CPSP function based on knowledge of noise and sound source statistics, measuring the accuracy of the CPSP function by examining its shape, and evaluating the CPSP only when the captured signal has appropriate energy and spectral characteristics. This strategy enables less error-prone performance, and allows more effective utilization of computing resources in a constrained real-time system. Simulation and real-time results are presented to demonstrate system improvement.

Ｍ系列信号音波を用いた相模湾の多経路伝搬音波の観測

In monitoring of water mass structure in mid-deep water using multipath sound propagation, high accuracy measurement of the travel time of rays which propagate reflecting at surface and bottom is required. M-sequence signal with correlation technique, which is one of the pseudorandom sequence, is useful to obtain signal-to-noise enhancement and high temporal resolution. In this paper, we examine travel time estimation error and the stability of multipath propagation using M-sequence signal from sound transmission experiment data at Sagami Bay. Using the carrier frequency of 5 kHz, multipath arrivals up to the range of 25 km are successfully detected and identifiable. Travel time estimation results are stable and high accuracy measurement is achieved. It is considered that from bottom and/or surface reflected rays measurement of the perturbation of travel time corresponding to the ocean fluctuations can be accomplished.

Analysis of multipath sound propagation in the ocean near 49° N, 128° W

Downslope sound propagation data collected off the west coast of Vancouver Island, British Columbia for a shallow source and a deep receiver are examined. The approach used in our analysis was, first, to identify ray paths from the source to the receiver and then to model the variation in measured pressure amplitude with range. The bottom interacting rays, bottom penetrating rays, and channel rays with bottom interaction were identified by the travel time differences between different bottom-bounce paths. Travel times were computed by ray tracing with an algorithm in which the time step along the ray is the independent parameter. Different propagation paths could be identified in different bathymetric regions viz., continental shelf, continental slope, and deep ocean. A ridge at a range of 79 km shadowed some of the propagating rays; ray tracing from the apex of the ridge was used to calculate travel time curves for some of the diffracted arrivals; however, these diffracted arrivals were difficult to identify in the data. Data collected in the range of 1–52 km were modeled by computing synthetic sonograms using a reflectivity technique modified to remove phase from the vertical wavefunctions. These synthetics were used to constrain the velocity, velocity gradient, sediment thickness, and the absorption coefficient in the upper part of the sediment.

The effect of Doppler on long-range sound propagation

In this sound propagation study of the effect of Doppler on source and/or receiver motion has been developed. It is based on modifying the inputs to existing normal-mode software so that the source and/or receiver trajectory and consequent Doppler effects of the given ocean experiment are properly modeled without requiring direct changes in the static softward. From this the effects of the received signal after long-range, multipath sound propagation from a moving source can be modeled and interpreted.

Effect of Doppler on long-range sound propagation

In this sound propagation study of the effect of Doppler on long-range acoustic tracking, a method of modeling the effects of source and/or receiver motion has been developed. It is based on modifying the inputs to existing normal mode software so that the source and/or receiver trajectory and consequent Doppler effects of the given ocean experiment are properly modeled without requiring direct changes in the static software. From this the effects of the received signal after long range, multipath sound propagation from a moving source can be modeled and interpreted.

An application of Poisson process models to multipath sound propagation of sinusoidal signals

A theory of multipath sound propagation is developed in which the number of rays between a source and receiver is modeled as a Poisson distributed random variable. Using probability distributions obtainable from environmental measurements and acoustic ray tracing programs, moments of the received sound field are derived as functions of space and time. An example is presented in which spatial and temporal coherence are estimated for a horizontal line array. It is shown that spatial coherence decreases with increasing angle from broadside, with increasing frequency, with increasing source speed, and with increasing ray vertical arrival angle at the receiver. Temporal coherence decreases with increasing source speed, with increasing ray vertical angle at the source, and with increasing frequency.Subject Classification: 20.20; 30.20; 60.20.

Numerical model of sound propagation in urban areas

A numerical technique has been developed for estimating the outdoor sound levels due to transportation noise sources moving through urban areas. A Monte Carlo method is used to account for the effects of reflection and scattering at building facades on the sound propagation. Inputs to the model are the geometry of the area, fitted to a rectangular grid, the source location and sound power level, and the absorption and scattering coefficients of the building facades. The user can then request the sound pressure level at any location in the area. This research has two objectives. The first is to develop a useful tool to assist in transportation planning in urban areas. The second is to further our basic understanding of multipath sound propagation in complex urban areas as part of a general program of noise propagation research at MIT.