scholarly journals Low-frequency 3D ultrasound tomography: dual-frequency method

2018 ◽  
pp. 479-495
Author(s):  
А.В. Гончарский ◽  
С.Ю. Романов ◽  
С.Ю. Серёжников
Keyword(s):  
Inverse Problem ◽  
Sound Speed ◽  
Soft Tissues ◽  
Dimensional Space ◽  
Low Frequency ◽  
Initial Approximation ◽  
3D Ultrasound ◽  
Acoustic Tomography ◽  
Dual Frequency ◽  
Frequency Method

Статья посвящена разработке эффективных методов 3D акустической томографии. Обратная задача рассматривается как коэффициентная обратная задача для уравнения гиперболического типа относительно неизвестных функций скорости звука и коэффициента поглощения в трехмерном пространстве. Математическая модель описывает такие явления, как дифракция, рефракция, переотражение и поглощение ультразвука. Трудности решения обратной задачи связаны с ее нелинейностью. Предложен метод низкочастотной 3D акустической томографии, который основан на использовании коротких зондирующих импульсов двух центральных частот~$f_1$ и $f_2>f_1$, не превосходящих 500 кГц. В качестве алгоритма решения обратной задачи используется итерационный градиентный метод на частоте $f_2$, в котором в качестве начального приближения используются распределения скорости звука и коэффициента поглощения, полученные как результат решения обратной задачи на частоте $f_1$. Эффективность предложенного метода акустической томографии проиллюстрирована решением модельных задач при параметрах, близких к задачам ультразвукового зондирования мягких тканей в медицине. Предложенный метод низкочастотной 3D акустической томографии позволяет получить пространственное разрешение порядка 2--3 мм при контрасте скорости не более 10%. Разработанные алгоритмы легко распараллеливаются на GPU-кластерах. This paper is devoted to the development of efficient methods for 3D acoustic tomography. The inverse problem of acoustic tomography is formulated as a coefficient inverse problem for a hyperbolic equation where the sound speed and the absorption factor are unknown in three-dimensional space. The mathematical model describes the effects of diffraction, refraction, multiple scattering, and the ultrasound absorption. Substantial difficulties in solving this inverse problem are due to its nonlinear nature. A method of low-frequency 3D acoustic tomography based on using short sounding pulses of two different central frequencies not exceeding 500 kHz is proposed. The method employs an iterative gradient-based minimization algorithm at the higher frequency with the initial approximation of unknown coefficients obtained by solving the inverse problem at the lower frequency. The efficiency of the proposed method is illustrated by solving a model problem with acoustic parameters close to those of soft tissues. The proposed method makes it possible to obtain a spatial resolution of 2--3 mm while the sound speed contrast does not exceed 10%. The developed algorithms can be efficiently parallelized using GPU clusters.

scholarly journals An Acoustic Tomography Technique for Concurrently Observing the Structure of the Atmosphere and Water Bodies

2017 ◽  
Vol 34 (3) ◽  
pp. 617-629 ◽  
Author(s):  
Anthony Finn ◽  
Kevin Rogers
Keyword(s):  
Theoretical Analysis ◽  
Sound Speed ◽  
Water Surface ◽  
Low Frequency ◽  
Sound Field ◽  
Acoustic Signals ◽  
Acoustic Tomography ◽  
Radio Waves ◽  
Surface Errors ◽  
Underwater Sensors

AbstractThe opacity of water to radio waves means there are few, if any, techniques for remotely sensing it and the atmosphere concurrently. However, both these media are transparent to low-frequency sound (<300 Hz), which makes it possible to contemplate systems that take advantage of the natural integration along acoustic paths of signals propagating through both media. This paper proposes—and examines with theoretical analysis—a method that exploits the harmonics generated by the natural signature of a propeller-driven aircraft as it overflies an array of surface and underwater sensors. Correspondence of the projected and observed narrowband acoustic signals, which are monitored synchronously on board the aircraft and by both sensor sets, allows the exact travel time of detected rays to be related to a linear model of the constituent terms of sound speed. These observations may then be inverted using tomography to determine the inhomogeneous structures of both regions. As the signature of the aircraft comprises a series of harmonics between 50 Hz and 1 kHz, the horizontal detection limits of such a system may be up to a few hundred meters, depending on the depth of the sensors, roughness of the water surface, errors due to refraction, and magnitude of the sound field generated by the source aircraft. The approach would permit temperature, wind, and current velocity profiles to be observed both above and below the water’s surface.

scholarly journals Inverse problems of experimental data interpretation in 3D ultrasound tomography

2019 ◽  
pp. 254-269
Author(s):  
А.В. Гончарский ◽  
В.А. Кубышкин ◽  
С.Ю. Романов ◽  
С.Ю. Серёжников
Keyword(s):  
Experimental Data ◽  
Mathematical Model ◽  
Inverse Problem ◽  
Acoustic Waves ◽  
Soft Tissues ◽  
Nonlinear Coefficient ◽  
3D Ultrasound ◽  
Acoustic Properties ◽  
Ultrasound Wave ◽  
Ultrasound Tomography

Обратная задача 3D ультразвуковой томографии рассматривается в статье как нелинейная коэффициентная обратная задача для уравнения гиперболического типа. Используемая математическая модель хорошо описывает как дифракционные эффекты, так и поглощение ультразвука в неоднородной среде. В рассматриваемой постановке реконструируется скорость распространения акустической волны как функция трех координат. Количество неизвестных в нелинейной обратной задаче составляет порядка 50 миллионов. Разработанные итерационные алгоритмы решения обратной задачи ориентированы на использование GPUкластеров. Основным результатом работы является апробация алгоритмов на экспериментальных данных. В эксперименте использовался стенд для 3D ультразвуковых томографических исследований, разработанный в МГУ имени М.В. Ломоносова. Акустические параметры фантомов близки к акустическим параметрам мягких тканей человека. Объем экспериментальных данных составляет порядка 3 ГБ. Интерпретация данных эксперимента позволила не только продемонстрировать эффективность разработанных алгоритмов, но и подтвердила адекватность математической модели реальности. Для реализации разработанных численных алгоритмов использовался графический кластер суперкомпьютера Ломоносов-2. The inverse problem of 3D ultrasound tomography is considered in this paper as a nonlinear coefficient inverse problem for a hyperbolic equation. The employed mathematical model accurately describes the effects of ultrasound wave diffraction and absorption in inhomogeneous media. The velocity of acoustic waves inside the test sample is reconstructed as an unknown function of three spatial coordinates. The number of unknowns in the nonlinear inverse problem reaches 50 million. The developed iterative algorithms for solving the inverse problem are designed for GPU clusters. The main result of this study is testing the developed algorithms on experimental data. The experiments were carried out using a 3D ultrasound tomographic setup developed at Lomonosov Moscow State University. Acoustic properties of the test samples were close to those of human soft tissues. The volume of data collected in experiments is up to 3 GB. Experimental results show the efficiency of the proposed algorithms and confirm that the mathematical model is adequate to reality. The proposed algorithms were tested on the GPU partition of Lomonosov2 supercomputer.

scholarly journals The problem of choosing initial approximations in inverse problems of ultrasound tomography

2017 ◽  
pp. 312-321
Author(s):  
А.В. Гончарский ◽  
С.Ю. Романов ◽  
С.Ю. Серёжников
Keyword(s):  
Inverse Problem ◽  
Inverse Problems ◽  
Soft Tissues ◽  
Iterative Algorithms ◽  
Initial Approximation ◽  
Explicit Representation ◽  
Nonlinear Inverse Problem ◽  
Ultrasound Tomography ◽  
Residual Functional ◽  
Wave Tomography

Статья посвящена разработке эффективных итерационных методов решения нелинейных обратных задач волновой томографии. Итерационные алгоритмы приближенного решения обратной задачи используют явное представление для градиента функционала невязки между экспериментально измеренным и расcчитанным волновым полем. Большое значение для сходимости итерационного процесса в нелинейной обратной задаче имеет выбор начального приближения. В статье исследована возможность использования в качестве начального приближения скоростного разреза, полученного из решения обратной задачи в лучевом приближении. Эффективность такого подхода проиллюстрирована решением модельных обратных задач на суперЭВМ. Модельные задачи ориентированы на томографическую ультразвуковую диагностику мягких тканей в медицине. This paper is devoted to developing efficient iterative methods to solve nonlinear inverse problems of wave tomography. The iterative algorithms used to obtain an approximate solution of the inverse problem are based on an explicit representation of the gradient of the residual functional between the measured and computed wave fields. The choice of the initial approximation is of great importance for the convergence of the iterative process in a nonlinear inverse problem. The possibility of using an initial approximation to the sound speed obtained via solving the inverse problem in the ray approximation is studied. The efficiency of this approach is illustrated by solving model problems using a supercomputer. These model problems are designed for the ultrasound tomographic imaging of soft tissues in medicine.

INVESTIGATION OF THE DUAL-FREQUENCY METHOD FOR REMOTE SENSING OF SOLID AEROSOLS

2010 ◽  
Vol 69 (13) ◽  
pp. 1205-1219
Author(s):  
O. A. Voitovych ◽  
A. M. Linkova ◽  
G. I. Khlopov
Keyword(s):  
Remote Sensing ◽  
Dual Frequency ◽  
Frequency Method

Acoustic Inversion Method for Profiling Suspended Sediment Concentration

2014 ◽  
Vol 687-691 ◽  
pp. 3980-3983
Author(s):  
Jun Xi Shi ◽  
Min Zhu ◽  
Yan Bo Wu ◽  
Xing Tao Sun
Keyword(s):  
Suspended Sediment ◽  
Suspended Sediment Concentration ◽  
Sediment Concentration ◽  
Acoustic Backscatter ◽  
Inversion Method ◽  
Dual Frequency ◽  
Frequency Method ◽  
Backscatter Signal ◽  
Size Profile ◽  
Acoustic Inversion

The concentration of suspended sediment is an important parameter for the research of sediment transport. Acoustic backscatter technique has been employed to measure the concentration of suspended sediment recently. It is an inversion problem to measure the concentration from the backscatter signal. In this paper, an improved dual-frequency method is proposed for the concentration inversion of suspension sediment. It is an explicit solution with much lower computational complexity than the commonly used iterative method and with no requirement of known and constant particle size profile compared to the basic dual-frequency method.

An inverse problem in low-frequency scattering by an ellipsoidally embossed surface

Wave Motion ◽  
1994 ◽  
Vol 20 (1) ◽  
pp. 33-39 ◽  
Author(s):  
George Dassios ◽  
R.J. Lucas
Keyword(s):  
Inverse Problem ◽  
Low Frequency

scholarly journals Depth Discrimination for Low-Frequency Sources Using a Horizontal Line Array of Acoustic Vector Sensors Based on Mode Extraction

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3692 ◽  
Author(s):  
Guolong Liang ◽  
Yifeng Zhang ◽  
Guangpu Zhang ◽  
Jia Feng ◽  
Ce Zheng
Keyword(s):  
Sound Speed ◽  
Linear Equations ◽  
Robustness Analysis ◽  
Low Frequency ◽  
Horizontal Line ◽  
Testing Hypotheses ◽  
Depth Discrimination ◽  
Line Array ◽  
Vector Sensors ◽  
Mode Extraction

Depth discrimination is a key procedure in acoustic detection or target classification for low-frequency underwater sources. Conventional depth-discrimination methods use a vertical line array, which has disadvantage of poor mobility due to the size of the sensor array. In this paper, we propose a depth-discrimination method for low-frequency sources using a horizontal line array (HLA) of acoustic vector sensors based on mode extraction. First, we establish linear equations related to the modal amplitudes based on modal beamforming in the vector mode space. Second, we solve the linear equations by introducing the total least square algorithm and estimate modal amplitudes. Third, we select the power percentage of the low-order modes as the decision metric and construct testing hypotheses based on the modal amplitude estimation. Compared with a scalar sensor, a vector sensor improves the depth discrimination, because the mode weights are more appropriate for doing so. The presented linear equations and the solution algorithm allow the method to maintain good performance even using a relatively short HLA. The constructed testing hypotheses are highly robust against mismatched environments. Note that the method is not appropriate for the winter typical sound speed waveguide, because the characteristics of the modes differ from those in downward-refracting sound speed waveguide. Robustness analysis and simulation results validate the effectiveness of the proposed method.

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