Time-angle ocean acoustic tomography using sensitivity kernels: Numerical and experimental inversion results

Wave theoretic modeling is applied to obtain travel-time sensitivity kernels representing the amount by which travel times are affected by localized sound-speed variations anywhere in the medium. In the ray approximation travel times are sensitive to medium changes only along the corresponding eigenrays. In the wave-theoretic approach the perturbations of peak arrival times are expressed in terms of pressure perturbations, which are further related with the underlying sound-speed perturbations using the first Born approximation. In this way, an integral representation of travel-time perturbations is obtained in terms of sound-speed perturbations; the associated kernel represents the spatial sensitivity of travel times to sound-speed perturbations. The application of the travel-time sensitivity kernel to an ocean acoustic waveguide gives a picture close to the ray-theoretic one in the high-frequency case but significantly differs at lower frequencies. Low-frequency travel times are sensitive to sound-speed changes in areas surrounding the eigenrays, but not on the eigenrays themselves, where the sensitivity is zero. Further, there are areas of positive sensitivity, where, e.g., a sound-speed increase results in a counter-intuitive increase of arrival times. These findings are confirmed by independent forward calculations.

The inference of internal properties of the Sun from surface measurements of wave travel times is the goal of time–distance helioseismology. A critical step toward the accurate interpretation of shifts in travel time is the computation of sensitivity functions linking seismic measurements to internal structure. Here we calculate finite-frequency sensitivity kernels in spherical geometry for two-point measurements of travel time. We numerically build Green’s function by solving for it at each frequency and each degree of spherical harmonic and summing over all these pieces. These computations are performed in parallel (“embarrassingly”), thereby achieving significant speedup in wall-clock time. Kernels are calculated by invoking the first-order Born approximation connecting deviations in the wave field to perturbations in the operator. Validated flow kernels are shown to produce travel times within 0.47% of the true value for uniform flows up to . We find that travel time can be obtained with errors of 1 ms or less for flows having magnitudes similar to meridional circulation. Alongside flows, we also compute and validate a sensitivity kernel for perturbations in sound speed. These accurate sensitivity kernels might improve the current inferences of subsurface flows significantly.

We propose a Taylor expansion multiple signal classification (TE MUSIC) method for joint direction of departure (DOD) and direction of arrival (DOA) estimation in a bistatic multiple-input multiple-output (MIMO) array. First, using a Taylor expansion of the steering vector, a two-dimensional (2D) search in the conventional MUSIC method for MIMO arrays is reduced to a two-step one-dimensional (ID) search in the proposed TE MUSIC method. Second, DOAs of the targets can be achieved via Lagrange multiplier by a ID search. Finally, substituting the DOA estimates into the 2D MUSIC spectrum function, DODs of the targets are obtained by another ID search. Thus, the DOD and DOA estimates can be automatically paired. The performance of the proposed method is better than that of the MIMO ESPRIT method, and is similar to that of the 2D MUSIC method. Furthermore, due to the ID search, the TE MUSIC method avoids the high computational complexity of the 2D MUSIC method. Simulation results are presented to show the effectiveness of the proposed method.

Ocean Acoustic Tomography (OAT) is an efficient and economical marine acoustic observation technique. Targeted observation is an appealing procedure to reduce the uncertainty of ocean environment prediction through additional observation. This study aimed to assess the validity of OAT as an observation method for targeted observation. OAT based on Niche Genetic Algorithm was employed to extract sound speed and temperature profiles from acoustic transmission time, utilizing data from the 2019 Yellow Sea experiment. The inversion results were compared with measurement data, which are found to be accurate and reliable. To further evaluate OAT as targeted observation method, the vertical bias structure of OAT was added on synchronous measurement data in the sensitive area of targeted observation to simulate OAT observation in sensitive area. This simulated data was then incorporated into a 3D-Var assimilation system to improve the short-term prediction of the target region. Comparing the predictions derived with the measurement data at the verification time, it shows that the simulated OAT observation improved the quality of target region prediction, indicating that OAT can be an effective observation method for targeted observation. An Observing System Simulation Experiment was conducted to assess the impact of OAT characteristics on prediction improvement. The results show that both adding observation nodes and extending the observation duration have positive effects, while extending the observation duration performs better.

The problem of tracking the direction of arrivals (DOA) and the direction of departure (DOD) of multiple moving targets is considered in bistatic multiple input multiple output (MIMO) radar. A low complexity angle tracking algorithm in bistatic MIMO radar is proposed. The proposed algorithm derived the difference between previous and current covariance matrices. And the relationship between the different of covariance matrices and the different of target angle is derived. The performance of the proposed algorithm is improved by averaging the covariance matrix elements. Last DOD and DOA are got by least square method. This algorithm avoids the decomposition of the covariance matrix and reduces the computational complexity, which realizes DOA and DOD of the adjacent moment automatic association. The simulation results demonstrate effectiveness of the proposed algorithm. The algorithm provides the technical support for the practical application of MIMO radar.

An improved algorithm for joint direction of departure (DOD) and direction of arrival (DOA) estimation in bistatic MIMO radar based on fourth order cumulants is presented. Firstly, the data of receiver is reset and divided to acquire the rotational invariance property of transmitter and receiver, respectively. The fourth order cumulants matrixes in twain are constructed which are based on the basic definition of the cumulant. Then we use the propagator method (PM), which only requires linear operation but does not involve any eigendecomposition of the cumulant matrix, to estimate the DODs and DOAs, respectively. Finally, the maximum likelihood method is used to solve the pairing problem. The proposed method is effective in prohibiting the Gaussian colored noise and improves the performance of the angle estimation slightly. It does not need two-dimensional spectrum peak searching and eigenvalue decomposition on the cumulant matrix, thus the computation complexity is reduced. At the same time, it has no exceptive claim on the number of receive arrays or receive arrays. Simulation results verify the effectiveness and feasibility of the proposed method.

Precise modelling of the Direction of Arrival (DoA) and Direction of Departure (DoD) of multipath components (MPCs) in a Multiple-Input Multiple-Output (MIMO) channel based on correlation properties and joint distributions have not been investigated properly. This paper examines the correlation between DoAs and DoDs, and presents a modelling approach particularly for the `general trend' of these dual-spatial domains, based on statistical results obtained from several indoor MIMO measurement campaigns. We show that the Laplacian distribution provides better fits for the directional parameters than the normal and Von Mises distributions. The `general trend' of DoA/DoD joint distribution and power density are modelled using a modified Gumbel's bivariate exponential approach. Results show that the proposed bivariate distribution provides a good match to the real data, and offers an alternative approach to generate realistic directional-based stochastic MIMO channel responses in different environments.

Variation in Patients' Travel Times among Imaging Examination Types at a Large Academic Health System

Ray-based acoustical tomography typically provides estimates of local ocean sound speed fluctuations from precise measurements of acoustic travel times fluctuations (with respect to a reference environment) between multiple sources and receiver arrays along with a model of the ray propagation in the reference (i.e., fluctuation-free) environment. Traditionally, this is achieved using a sensitivity kernel, a Born–Frechet linearization of the non-linear relationship between ray arrival-times and sound speeds fluctuations. However, computing the full sensitivity kernel can be computationally intensive and is restricted to only small sound-speed fluctuations (due to the linearization procedure) and does not inherently leverage any available history of the arrival time or sound speed fluctuations which may have been collected prior to performing the inversion procedure. As an alternative solution for ray-based acoustical tomography, we investigated the use of data-driven methods, such as linear regression, nearest neighbors, neural networks, and kernel (ridge) regression, to directly learn the non-linear relationship between sound speed fluctuations and ray arrival time variations using previously collected measurements. Additionally, the experimental training data set is augmented by generating synthetic SSPs based on empirical orthogonal function analysis of the historical SSP data. This approach is demonstrated for short vertical bottom-mounted arrays deployed in littoral environments.

Coastal acoustic tomography (CAT) which was proposed by Hiroshima University in 1990s as a shallow-sea application of ocean acoustic tomography (OAT) is developed as a mirror-type CAT (MCAT) for measuring deep strait throughflows in Indonesian archipelago seas in real time. MCAT system is composed of a land station (M0) connected to a 100 m submarine cable edged by a 5 kHz subsurface transceiver and triangular-arrayed bottom-moored stations (M1, M2, and M3). Reciprocal data are first obtained among three station pairs (M1M2, M2M3, and M3M1). Data received at M1 from M2 and M3 are transferred to the land station (M0) by the first mirror reflection, resulting in travel time summations (t21 + t10, t31 + t10) (t21: travel time from M2 to M1). Data obtained at the offshore stations M2 and M3 are transferred to the nearshore station M1 by the first mirror reflection, resulting in travel time summations (t12 + t21, t13 + t31, t23 + t31, and t32 + t21). All the first mirror data at M1 are also transferred to M0 by the second mirror reflection, adding a travel time by t10 for the above four travel time summations. Finally, travel time differences are calculated for M0M1, M1M2, M2M3, and M3M1 by subtracting the summation data at M0. They are converted to path-average currents along the four transmission lines, succeeding in strait throughflow estimate. The mirror reflection function of MCAT can develop in an underwater transfer system of sound from moving sources by adding a hydrophone.

This letter discusses the problem of direction of departure (DOD) and direction of arrival (DOA) estimation for multi-input multi-output (MIMO) radar, and derives a reduced-dimension multiple signal classification (MUSIC) algorithm therein. The proposed algorithm, which only requires one-dimension search, can avoid the high computational cost within two-dimension MUSIC (2D-MUSIC) algorithm. We illustrate that the algorithm has better performance ESPRIT algorithm, and has very close performance to 2D-MUSIC algorithm. Further our algorithm requires no pair matching. Simulation results verify the usefulness of our algorithm.

Water temperature, salinity concentration, current velocity distribution, etc. in the ocean, are very important physical properties to understand the thermal structure of the ocean. The monitoring of these physical properties could be achieved by either of two kinds of measurement schemes, i.e., one the direct measurements using instruments such as ARGO floats and the other the indirect method using some other parameters such as the sound speed. Ocean acoustic tomography (OAT) was invented to verify the possibility of the latter. Although analysis based on the travel time of sound inversion using the inversion technique (TTI) has been attempted based on the ray theory, it is expected to improve both the resolution and the accuracy of the measurements. In the ocean, sound waves travel through complex structure where the contrast in the velocity could be of the order of less than a percent. Therefore, the application of TTI may not produce satisfactory results. We first state the following two hypotheses to propose a method to improve OAT: 1) full waveform inversion (FWI) could improve the resolution, 2) attenuation is likely to be considered in the velocity inversion. The application of FWI to synthetic examples to test these hypothesis provided us pretty satisfactory results and the validity of our hypothesis have been verified.

Preface. I: Theories of Solar Convection, Rotation, and Activity. Towards Understanding Solar Convection and Activity D. Gough. Fluid Dynamics and MHD of the Solar Convection Zone and Tachocline: Current Understanding and Unsolved Problems P.A. Gilman. Can We Get the Bottom B? A. Ruzmaikin. The Coupling of Solar Convection and Rotation M.S. Miesch. Realistic Solar Convection Simulations R.F. Stein, A. Nordlund. Solar Magnetoconvection N.E. Hurlburt, et al. The Solar Dynamo and Emerging Flux G.H. Fisher, et al. On the Twist of Emerging Flux Loops in the Solar Convection Zone Y. Fan, D. Gong. II: Helioseismic Tomography. Time-Distance Inversion Methods and Results A.G. Kosovichev, et al. Time-Distance Helioseismology with f Modes as a Method for Measurement of Near-Surface Flows T.S. Duvall Jr., L. Gizon. Travel Time Sensitivity Kernels A.C. Birch, A.G. Kosovichev. Calculation of the Sun's Acoustic Impulse Response by Multi-Dimensional Spectral Factorization J.E. Rickett, J.F. Claerbout. Ray Travel Time and Distance for the Planar Polytrope G.H. Price. Sensitivity Kernels for Time-Distance Inversion J.M. Jensen, et al. III: Acoustic Imaging and Holography. Acoustic Imaging of Solar Active Regions D.-Y. Chou. Basic Principles of Solar Acoustic Holography C. Lindsey, D.C. Braun. Helioseismic Holography of Active-Region Subphotospheres D.C. Braun, C. Lindsey. Phase-Sensitive Holography of Solar Activity D.C. Braun, C. Lindsey. Stochastic Seismic Emission from Acoustic Glories and the Quiet Sun A.-C. Donea, et al. IV: Ring-Diagram Analysis. Solar Shear Flow Deduced from Helioseismic Dense-Pack Samplings of RingDiagrams D.A. Haber, et al. Near-Surface Flow Fields Deduced Using Correlation Tracking and Time-Distance Analyses M. de Rosa, et al. Local Fractional Frequency Shifts Used as Tracers of Magnetic Activity B. Hindman, et al. V: Magnetic Fields and Oscillations. Sunspot Oscillations: A Review T.J. Bogdan. Modelling p-Mode Interaction with a Spreading Sunspot Field P.S. Cally. Measuring Magnetic Oscillations in the Solar Photosphere: Coordinated Observations with MDI, ASP and MWO A.A. Norton, R.K. Ulrich. Interaction between Network and Intranetwork Magnetic Fields J. Zhang, et al. VI: Solar-Cycle Variations of the Internal Structure and Rotation. Variations in Solar Sub-Surface Rotation from Gong. Data 1995-1998 R. Howe, et al. Time Variability of Rotation in Solar Convection Zone from SOI-MDI J. Toomre, et al. Possible Solar Cycle Variations in the Convection Zone S. Basu, H.M. Antia. Solar Cycle Variation in Solar f-Mode Frequencies and Radius H.M. Antia, et al. Solar Cycle Variations of Large-Scale Flows in the Sun S. Basu, H.M. Antia. Does the Tachocline Show Solar Cycle Related Changes? S. Basu, J. Schou. Empirical Estimate of p-Mode Frequency Shift for Solar Cycle 23 K. Jain, et al.

We study the problem of angle estimation for non-circular sources in bistatic multiple-input multiple-output (MIMO) radar system and propose a low-complexity ESPRIT---Root-MUSIC algorithm for joint direction of departure (DOD) and direction of arrival (DOA) estimation. By taking the non-circularity characteristics of the impinging signals, the received data can be extended, which corresponds to double the number of elements in MIMO radar. Then a novel signal subspace, based on the multistage wiener filter, can be determined directly from the extended data, which does not involve the estimation of covariance matrix and its eigenvalue decomposition (EVD), thus implying that the proposed method is computationally efficient. Finally, the DOD and DOA are estimated by ESPRIT and Root-MUSIC, respectively. Compared with EVD-based algorithms, the proposed method provides the comparable angle estimation performance with lower computational complexity. Some simulation results verify the validity of the proposed method.

In bistatic multiple input multiple output (MIMO) radar, more number of detectable incident signals and a higher angle estimation performance can be obtained by using conjugate estimation of signal parameters via rotational invariance techniques (ESPRITs) with the characteristic of noncircularity. The result is achieved under the assumption that all the received signals are noncircular. When the incident signals are the coexistence of noncircular and circular signals, the conjugate ESPRIT will not valuable. Therefore, this paper proposes a method of the joint of direction of departure (DOD) and direction of arrival (DOA) estimation, which is appropriate for the coexistence of noncircular and circular signals in bistatic MIMO radar. First, the received data model of the bistatic MIMO radar is given. Second, we modify the received signal model by the use of noncircularity characteristic. Third, we derive out the equation of spatially rotational invariant containing the DOD and DOA information. Last, we solve the equation to obtain the DOD and DOA by means of total least squares technology. The proposed algorithm has the three advantages. One is that it has better angle estimation accuracy than that of method which does not use the noncircularity characteristic. Another one is that it has more number of detectable incident signals. The last one is that the more number of noncircular signals, the higher angle estimation accuracy will be. Results from numerical experiments are used to show the effectiveness of our proposed algorithm.