Ray-based blind deconvolution in ocean sound channels
13 Jan 2010-Journal of the Acoustical Society of America (Acoustical Society of America)-Vol. 127, Iss: 2
TL;DR: This technique successfully decoded underwater telecommunication sequences in the bandwidth 3-4 kHz that were broadcast 4 km in a 120-m-deep ocean sound channel without a-priori knowledge of sound channel characteristics.
Abstract: This letter describes a ray-based blind deconvolution technique for ocean sound channels that produces broadband estimates of the source-to-array impulse response and the original source waveform from array-measured signals corrupted by (unknown) multipath propagation. The technique merely requires elementary knowledge of array geometry and sound speed at the array location. It is based on identifying a ray arrival direction to separate source waveform and acoustic-propagation phase contributions to the received signals. This technique successfully decoded underwater telecommunication sequences in the bandwidth 3–4 kHz that were broadcast 4 km in a 120-m-deep ocean sound channel without a-priori knowledge of sound channel characteristics.
Citations
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TL;DR: Passive time reversal communications is described which enables multiple users to send information simultaneously to the time reversal array over a common bandwidth channel.
Abstract: A recent paper [Song et al., IEEE J. Ocean. Eng. 31, 165–173 (2006)] demonstrated multipleinput/multiple‐output (MIMO) multi user communications in shallow water using active time reversal where the time reversal array (i.e., base station) sent different messages to multiple users simultaneously over a common bandwidth channel. Passive time reversal essentially is equivalent to active time reversal with the communications link being in the opposite direction. This paper describes MIMO passive time reversal communications, which enables multiple users to send information simultaneously to the time reversal array. Experimental results at 3.5 kHz with a 1‐kHz bandwidth demonstrate that as many as six users can transmit information over a 4‐km range in 120‐m‐deep shallow water using QPSK modulation, achieving an aggregate data rate of 6 kbits/s. Moreover, the same data rate has been achieved at 20 km range by three users using 16‐QAM modulation.
45 citations
TL;DR: How ray-based STR signal estimates may be improved and how ray- based STR sound-channel impulse-response estimates may been exploited for approximate source localization in underwater environments are described.
Abstract: 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 15–40 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 near
45 citations
Cites background or methods from "Ray-based blind deconvolution in oc..."
...…the additional information used in STR to uniquely estimate the source signal and the environment’s impulse response is drawn from the generic characteristics of the acoustic modes (Sabra and Dowling 2004) or the acoustic rays (Sabra et al. 2010) that convey sound from the source to the array....
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...The mathematical formulation of propagating-mode-based STR is presented in Sabra and Dowling (2004) and its extension to acoustic rays is outlined in Sabra et al. (2010)....
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TL;DR: This paper describes how STR is implemented even when the receiving-array elements are many wavelengths apart and conventional beamforming is inadequate, and frequency-difference beamforming can be used to determine signal-path-arrival angles that conventionalbeamforming cannot.
Abstract: 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, Pj(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 Pj*(ω1)Pj(ω2) at the difference frequency ω2 − ω1. 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...
40 citations
Cites background or methods from "Ray-based blind deconvolution in oc..."
...In particular in underwater applications, blind deconvolution involves using N receiving-array recordings to estimate Nþ 1 waveforms: N source-to-receiver transfer-function waveforms, and one source-signal waveform....
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...STR [also known as artificial time reversal (ATR) (Sabra and Dowling, 2004; Sabra et al., 2010)] is a fully passive technique for blind deconvolution that does not involve iterative procedures, parameter searches, or optimizations....
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...…propagation is well described by a ray-path sum in a mid-frequency region (1–4 kHz) and the receiving array is vertical with sufficient element density so that conventional delay-and-sum beamforming can be used to distinguish ray-path-arrival directions (Sabra et al., 2010; Abadi et al., 2012)....
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...The development of STR with conventional beamforming for isolating the signal phase via a mode-shape weighting or ray-path weighting of the array measurements is described elsewhere (Sabra and Dowling, 2004; Sabra et al. 2010; Abadi et al., 2012)....
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TL;DR: This article reviews how these information-carrying and -collecting features of acoustic waves that travel through fluids can be exploited for remote sensing.
Abstract: Acoustic waves carry information about their source and collect information about their environment as they propagate. This article reviews how these information-carrying and -collecting features of acoustic waves that travel through fluids can be exploited for remote sensing. In nearly all cases, modern acoustic remote sensing involves array-recorded sounds and array signal processing to recover multidimensional results. The application realm for acoustic remote sensing spans an impressive range of signal frequencies (10−2 to 107 Hz) and distances (10−2 to 107 m) and involves biomedical ultrasound imaging, nondestructive evaluation, oil and gas exploration, military systems, and Nuclear Test Ban Treaty monitoring. In the past two decades, approaches have been developed to robustly localize remote sources; remove noise and multipath distortion from recorded signals; and determine the acoustic characteristics of the environment through which the sound waves have traveled, even when the recorded sounds orig...
39 citations
TL;DR: The results indicate that the vertical array can range calls over larger ranges and with greater precision than the particular distributed array discussed here, whenever the call locations are beyond the distributed array boundaries.
Abstract: This paper presents the performance of three methods for estimating the range of broadband (50–500 Hz) bowhead whale calls in a nominally 55-m-deep waveguide: Conventional mode filtering (CMF), synthetic time reversal (STR), and triangulation. The first two methods use a linear vertical array to exploit dispersive propagation effects in the underwater sound channel. The triangulation technique used here, while requiring no knowledge about the propagation environment, relies on a distributed array of directional autonomous seafloor acoustics recorders (DASARs) arranged in triangular grid with 7 km spacing. This study uses simulations and acoustic data collected in 2010 from coastal waters near Kaktovik, Alaska. At that time, a 12-element vertical array, spanning the bottom 63% of the water column, was deployed alongside a distributed array of seven DASARs. The estimated call location-to-array ranges determined from CMF and STR are compared with DASAR triangulation results for 19 whale calls. The vertical-array ranging results are generally within ±10% of the DASAR results with the STR results providing slightly better agreement. The results also indicate that the vertical array can range calls over larger ranges and with greater precision than the particular distributed array discussed here, whenever the call locations are beyond the distributed array boundaries.
24 citations
Cites methods from "Ray-based blind deconvolution in oc..."
...Two techniques require the use of a vertical array: Conventional mode-filtering (CMF) and synthetic time reversal (STR), a blind deconvolution technique (Sabra and Dowling, 2004; Sabra et al., 2010; Abadi et al., 2012)....
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References
More filters
TL;DR: In this article, the authors present state-of-the-art numerical techniques to solve the wave equation in heterogeneous fluid-solid media and present a comprehensive and modern introduction to computational ocean acoustics accessible to students.
Abstract: Senior level/graduate level text/reference presenting state-of-the- art numerical techniques to solve the wave equation in heterogeneous fluid-solid media. Numerical models have become standard research tools in acoustic laboratories, and thus computational acoustics is becoming an increasingly important branch of ocean acoustic science. The first edition of this successful book, written by the recognized leaders of the field, was the first to present a comprehensive and modern introduction to computational ocean acoustics accessible to students. This revision, with 100 additional pages, completely updates the material in the first edition and includes new models based on current research. It includes problems and solutions in every chapter, making the book more useful in teaching (the first edition had a separate solutions manual). The book is intended for graduate and advanced undergraduate students of acoustics, geology and geophysics, applied mathematics, ocean engineering or as a reference in computational methods courses, as well as professionals in these fields, particularly those working in government (especially Navy) and industry labs engaged in the development or use of propagating models.
1,344 citations
Book•
07 May 1997
TL;DR: This revision, with 100 additional pages, completely updates the material in the first edition and includes new models based on current research and includes problems and solutions in every chapter, making the book more useful in teaching.
Abstract: Senior level/graduate level text/reference presenting state-of-the- art numerical techniques to solve the wave equation in heterogeneous fluid-solid media. Numerical models have become standard research tools in acoustic laboratories, and thus computational acoustics is becoming an increasingly important branch of ocean acoustic science. The first edition of this successful book, written by the recognized leaders of the field, was the first to present a comprehensive and modern introduction to computational ocean acoustics accessible to students. This revision, with 100 additional pages, completely updates the material in the first edition and includes new models based on current research. It includes problems and solutions in every chapter, making the book more useful in teaching (the first edition had a separate solutions manual). The book is intended for graduate and advanced undergraduate students of acoustics, geology and geophysics, applied mathematics, ocean engineering or as a reference in computational methods courses, as well as professionals in these fields, particularly those working in government (especially Navy) and industry labs engaged in the development or use of propagating models.
523 citations
"Ray-based blind deconvolution in oc..." refers background in this paper
...…exp − i T ;N + i s , 2 where the time-delay ,r j at the jth array element can be computed from plane-wave or more sophisticated beamforming, and T is approximately constant with respect to frequency and depends on the ray-travel time between the source and the receive array (Jensen et al., 2000)....
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TL;DR: In this article, the temporal resolution of a time-reversal or passive-phase conjugation process as applied to underwater acoustic communications is studied. And the effect of temporal focusing as measured by the peak-to-sidelobe ratio of the back-propagated or phase-conjugated pulse (both pulse elongation and sidelobe leakages are causes of intersymbol interference and bit errors for communications).
Abstract: In this paper, we study the temporal resolution of a time-reversal or passive-phase conjugation process as applied to underwater acoustic communications. Specifically, we address 1) the time resolution or the pulse width of a back-propagated time-compressed pulse as compared with the original transmitted pulse; 2) the effectiveness of temporal focusing as measured by the peak-to-sidelobe ratio of the back-propagated or phase-conjugated pulse (both pulse elongation and sidelobe leakages are causes of intersymbol interference and bit errors for communications); 3) the duration of temporal focusing or the temporal coherence time of the underwater acoustic channel; and 4) the stability of temporal focusing as measured by the phase fluctuations of successive pulses (symbols). Binary phase-shift keying signals collected at sea from a fixed source to a fixed receiver are used to extract the above four parameters and are compared with simulated results. Mid-frequency (3-4-kHz) data were collected in a dynamic shallow-water environment, exhibiting high temporal fluctuations over a scale of minutes. Despite this, the channel is found to be highly coherent over a length of 17 s. As a result, only one probe signal is used for 17 s of data. The bit error rate and variance of the symbol phase fluctuations are measured as a function of the number of receivers. They are of the same order as that calculated from the simulated data. The agreement suggests that these two quantities could be modeled for a communication channel with high coherence time. The phase variance can be used to determine the maximum data rate for a phase-shift keying signal for a given signal bandwidth and a given number of receivers.
139 citations
"Ray-based blind deconvolution in oc..." refers background in this paper
...The term in the right bracket, denoted QE t ; ;N , corresponds to the q function representing the summation of the cross-correlations between the measured and estimated Green’s function Ge r j ,r s , t ; ;N (Yang, 2003; Song et al., 2007) [see Fig....
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TL;DR: Passive phase conjugate (PPC) processing as mentioned in this paper uses the first arrival, from a stream of pulses that have traversed a complex refractive medium, as a filter for later pulse arrivals.
Abstract: Passive phase‐conjugate (PPC) processing consists of using the first arrival, from a stream of pulses that have traversed a complex refractive medium, as a filter for later pulse arrivals. Its connection with true ‘‘active’’ phase conjugation lies in invoking reciprocity for the backpropagation. When the intervening acoustic medium changes slowly, the PPC processor creates an unambiguous temporal peak even when a complex multipath environment separates the acoustic source and receiver. Temporal sidelobes in the PPC processor output can be suppressed by increasing the number of receivers and coherently summing their output. Recent deep‐ocean acoustic propagation measurements (IWAC ’90) are used to assess PPC processing in a fading multipath acoustic channel. For a range of 272.3 km at 460 Hz, the compressed peak persists on average for about half an hour. Fading of the PPC processor peak is found to be consistent with parabolic‐equation second‐moment theory for wave propagation in a random medium.
112 citations
"Ray-based blind deconvolution in oc..." refers methods in this paper
...…of the Green’s function estimates Ge r j ,r s , t ; ,N was further quantified by using them for passive time-reversal (or passive phase conjugation, Dowling, 1994) of the received signal Pj t in order to construct an estimate, SE t ; , of the broadcast QPSK sequence S t : SE t; ;N = j=1 M Pj t Ge…...
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TL;DR: Passive time reversal communications is described which enables multiple users to send information simultaneously to the time reversal array over a common bandwidth channel.
Abstract: A recent paper (Song , IEEE Journal of Oceanic Engineering, vol. 31, no. 2, pp. 170-178, 2006) demonstrated multiple-input-multiple-output (MIMO) communications in shallow water using active time reversal where the time reversal array (i.e., base station) sent different messages to multiple users simultaneously over a common bandwidth channel. Passive time reversal essentially is equivalent to active time reversal with the communications link being in the opposite direction. This paper describes passive time reversal communications which enables multiple users to send information simultaneously to the time reversal array. Experimental results at 3.5 kHz with a 1-kHz bandwidth demonstrate that as many as six users can transmit information over a 4-km range in a 120-m-deep water using quaternary phase-shift keying (QPSK) modulation, achieving an aggregate data rate of 6 kb/s. Moreover, the same data rate has been achieved at 20-km range by three users using 16 quadrature amplitude modulation (16-QAM).
86 citations