Sound Speed Profile Research Articles

Passive source depth estimation in shallow water using two horizontally separated hydrophones

A solution to the problem of acoustic source depth estimation in shallow water is presented for the case of two horizontally separated hydrophones or arrays. The solution is based on that the smooth-averaged cross-correlation function (SCF) of signals changes regularly with the source depth and is approximately independent of the source range, allowing that the source depth can be estimated independently without knowing the source range. Using different cost functions, three methods are proposed to estimate source depth by matching the normalized cross-spectral density, temporal envelope and time delay of the SCF. Then, the performance of the proposed methods are evaluated with simulations and two experiments conducted off the coast of China at water depths not exceeding 100m. The mean absolute errors in source depth of the proposed methods are in 2.8–12.8m. Finally, the effect of noise, frequency band, range span, horizontal spacing, sound speed profile, and parameter mismatch are numerically studied. The results show that the methods are more suitable for the case of a low-frequency band and an environment with large negative sound speed gradient.

The Effects of Sound Speed Profile to the Convergence Zone in Deep Water

The structure of a sound speed profile (SSP) in deep water causes refraction of sound rays and Convergence Zones (CZs) of high intensity where the rays focus at shallow depth. Study of sound field characteristics in the CZs has always been the focus of deep-water acoustics research. Many studies have been conducted on sound propagation in different parts of the oceans with different environments and, in this paper, the range and width of CZ is analyzed in the East Indian Ocean (EIO) and the South China Sea (SCS). Through the experimental data collected in different seasons with the propagation conditions change in the EIO and the SCS, we observe that the SSPs in different marine environments have a significant impact on the CZs of deep water. The sound channel mixing layer and isothermal layer have great effect on the CZ ranges. The water depths in the two experimental areas are similar, the range of the first CZ in the EIO is 7–8 km farther than that in the SCS, and the width of the CZs in the EIO is about 2–3 km narrower than that in the SCS. The surface mixed layer and the thermocline affect the CZ width but has little effect on the CZ range when the sound speed at the source and the bottom are practically the same. As the propagation conditions change along the seasons in the EIO, the range of the first CZ is almost the same, but the width of the CZs in the summer is about 2 km narrower than that in the spring. The water depth affects the CZ width but has little effect on the CZ range if the CZs can be formed. The different CZ characteristics between EIO and SCS are explained by both theoretical calculation and numerical simulation. The influence of the SSP structure and water depth on the CZ range are analyzed and the corresponding mechanism is explained. The research results are of great significance for underwater acoustic detection in deep sea.

Prediction of the ocean water sound speeds via attribute-guided seismic waveform inversion

Oceanic temperature and salinity are important for studying ocean dynamics and marine ecosystems, and for developing climate prediction models. Physical oceanographers measure these properties using expendable instruments, providing accurate measurements at high vertical resolution at sparse lateral locations. Accuracy of these temperature and salinity data when laterally interpolated and used for ocean dynamics, marine biology, and weather-related studies is questionable. Marine seismic data indicate visible reflections within the water columns, which, in turn, are primarily controlled by the vertical and lateral variations of the ocean water sound speeds. Because these sound-speed variations are functions of temperature and salinity, water-column seismic reflection data have been inverted for sound speeds and used to estimate temperature and salinity. These seismically derived temperature and salinity data have lower vertical, but much finer lateral resolution than those measured by expendable instruments, and therefore are useful for physical oceanography, marine biology, and climate research. However, quality of the seismic inversion relies on a good initial model, which requires generating models at sparse locations over 2D or 3D seismic data volumes and interpolating them over the horizon, manually picked from the stacked seismic data. Because horizon picking is subject to human error and bias, replacing it with an automated process is desirable. We outline a new attribute-guided methodology for initial model generation where no horizon picking is necessary. Starting with this initial model, we run prestack waveform inversion based on genetic algorithm optimization and demonstrate that our method can predict reliable sound-speed profiles. We conclude that our method is a good way for estimating ocean water sound speeds and relating them to the temperature and salinity.

SSP based underwater CIR estimation with S-BiFPN

In underwater sensor networks (USN), channel impulse response (CIR) estimation based on sound speed profile (SSP) ensures link reliability. We propose a separate bi-directional feature pyramid network (S-BiFPN) that estimates the CIR using deep learning based on SSP. The proposed method enlarges the small variation of SSP by converting 1-dimension into 2-dimension, extracts various features using a fused feature map obtained from the separate paths, and estimates the CIR. Simulations are performed using the practically measured SSPs and CIRs, and the results show that the proposed method has the lowest mean square error (MSE) and a reasonable running time compared to conventional methods.

Modeling methods for dispersive sound speed profiles of the Martian atmosphere and their effects on sound propagation paths

At present, Mars acoustic detection is gradually becoming an important new tool for the knowledge and exploration of Mars. To explore the sources of Mars sound, it is necessary to study the sound speed and the sound attenuation in the thin and low-temperature Martian atmosphere, and to model the sound propagation in the stratified atmosphere. Based on the extremely low pressure of Mars and the large variation of gas composition with altitude, we proposed a simulation method based on the Navier-Stokes (NS) equation and the mixed-gas model to calculate the vertical profiles of sound speed and attenuation in the Martian atmosphere at 0~250 km altitude in this paper. By comparing sound-speed profiles at different frequencies, there is notably sound dispersion in the Martian atmosphere, especially at high altitudes and in the high frequency range. It is also verified through sound speed measurement experiments verify that significant sound dispersion does exist in low-pressure carbon dioxide, illustrating the need to consider sound dispersion in the modelling of Martian sound speed profiles. The scope of application of the NS equation in modelling the sound speed of the Martian atmosphere is also discussed, as the NS equation may fail in a too rarefied gas. Next, the non-dispersive ideal-gas sound speed profiles and the dispersive NS sound speed at different frequencies (0.01 Hz, 0.1 Hz, 1 Hz) were applied to simulate the sound propagation paths in the multilayered Martian atmosphere. And both cases of the Martian ground-based and high-altitude sources were compared respectively. It is found that the dispersive sound speed has a significant effect on the sound propagation path on Mars. The main impact is that the first fold back height and the first return distance of the sound ray to the surface are shortened, which directly changes the area and location of the acoustic quiet zone. The effect of dispersion on the sound propagation path becomes more notable with both the increasing frequency and the elevation of the acoustic source, confirming that consideration of dispersion has a significant effect on the calculation of the sound propagation path.

Methods of modelling dispersive sound speed profiles of Martian atmosphere and their effects on sound propagation paths

At present, Mars acoustic detection is gradually becoming an important new tool for understanding and exploring Mars. To explore the sources of Mars sound, it is necessary to study the sound speed and the sound attenuation in the thin and low-temperature Martian atmosphere, and to model the sound propagation in the stratified atmosphere. According to the extremely low pressure of Mars and the large variation of gas composition with altitude, we propose a simulation method based on the Navier-Stokes (NS) equation and the mixed-gas model to calculate the vertical profiles of sound speed and attenuation in the Martian atmosphere at 0–250 km altitude in this work. A comparison among sound-speed profiles at different frequencies shows that there is a notable sound dispersion in the Martian atmosphere, especially at high altitudes and in the high frequency range. It is also verified through sound speed measurement experiments that significant sound dispersion does exist in low-pressure carbon dioxide, implying the need to consider sound dispersion in the modelling of Martian sound speed profiles. The scope of application of the NS equation in modelling the sound speed of the Martian atmosphere is also discussed, as the NS equation may fail in a too rarefied gas. Next, the non-dispersive ideal-gas sound speed profiles and the dispersive NS sound speed at different frequencies (0.01, 0.1, 1 Hz) are used to simulate the sound propagation paths in the multilayered Martian atmosphere. And both cases of the Martian ground-based and high-altitude sources are compared with each other. It is found that the dispersive sound speed has a significant effect on the sound propagation path on Mars. The main influence is that the first fold back height and the first return distance of the sound ray to the surface are both shortened, which directly changes the area and location of the acoustic quiet zone. The effect of dispersion on the sound propagation path becomes more notable with both the frequency and the elevation of the acoustic source increasing, confirming that consideration of dispersion has a significant effect on the calculation of the sound propagation path.

RIEMANNIAN MATCHED FIELD PROCESSING

As far as underwater source localization is concerned the Matched Field Processing (MFP) is an effective method. Floating ship localization, submarine localization in military section and fish finding in civilization are considered as the main application of MFP. Besides, determining environmental parameters such as sound speed profile, bottom topography and array tilt are also developed. Some methods such as empirical mode decomposition, adaptive MFP, compressive MFP and especially stochastic MFP using Riemannian geometry (RMFP) have been introduced recently in order to increase MFP’s reliability and resolution. It seems that the RMFP is the strongest candidate for the future development of MFP since it is inherited the strong foundation of both MFP and Riemannian Geometry. Surprisingly, not only the nature of curvature of sound wave but also the nature of MFP are exploited in RMFP. The aim of this monograph is introduce RMFP by considering the Riemannian distance instead of Euclidean distance. Two approaches of RMFP construction, i.e., isometric mappings and direct Riemannian distance calculation are introduced. The organization of this monograph is as follows. Two first chapters of this monograph revised the reader about the essential meaning of Gauss Curvature, Geodesic equation, iso-metric mapping in Riemannian Geometry and the state of the art of MFP. Chapter 3 presents Riemannian MFP. Chapter 4 concludes the monograph with discussions about the performance of MFP. This monograph is designed for graduated students, scientists and senior engineers who working in the field of underwater acoustic engineering. We would like to thanks SACLANTC for providing access of SONAR array data. We also express our gratitude to University of Engineering and Technology (VNUH) for partial financial support this monograph. Finally, I deeply express my appreciate to my family, especially my father for their patient and love to me.

Three Dimensional Volume Coverage in Multistatic Sonar Sensor Networks

Recent changes in the design of enemy threats such as submarines and the technological achievements in sensor development have paved the way for multistatic sonar applications, which increase security and situational awareness in underwater tactical operations. Previously, coverage in multistatic sonar sensor networks (MSSN) was studied using Cassini ovals and the traditional sonar detection model in two dimensions without any discussion of the practicability and feasibility in terms of conditions related to the underwater acoustic propagation environment. In this study, a practical three-dimensional MSSN channel model is proposed. The proposed model covers a spectral variation of absorption loss, ambient noise, sound speed profile, and shadow zones. The realistic effects of sound propagation and environmental conditions are modeled and evaluated using Lybin, which is a well-known sonar performance prediction tool. Using the practical MSSN channel model, the number of source-receiver pairs required to cover a three-dimensional MSSN volume is calculated. The impacts of frequency, source-to-receiver distance, and source level are investigated. The results are compared to the Cassini oval and traditional sonar detection models via an error expression derived according to our verified practical model. The results reveal that the inclusion of ambient conditions and sound propagation characteristics in the channel model leads to huge error levels of 4700000% in the Cassini oval model and 170000% in the traditional sonar detection model, depending on frequency. Thus, the applicability of these models in realistic MSSN deployment scenarios is limited.

Characteristics of long-range sound propagation in western Pacific

Acoustic signals can travel thousands of kilometers in seawater, and the characteristics of long-range sound propagation are different from short range propagation. This paper is based on a long-range underwater acoustic experimental data obtained from the western Pacific Ocean, where the farthest propagation distance is nearly 2000 km. The ocean environment information and vertical line array information are carefully processed. We analyze the attenuation of long-distance acoustic propagation in seawater and multi-path arrival structure characteristics under the complete acoustic channel environment of the ocean. In terms of the attenuation law of long-distance propagation energy, with the increase of propagation distance, the effect of seawater absorption on the attenuation of sound energy becomes prominent, and the selection of absorption coefficient is very important for the accurate prediction of sound field energy. Absorption in seawater of low frequency signals is small, and the transmission loss of acoustic signal with 100 Hz center frequency increases only by about 6 dB when the propagation distance increases from 1000 km to 2000 km. In terms of multi-path arrival structure characteristics of deep-sea acoustic channel for long-distance sound propagation, the thermocline sound velocity profile in the experimental sea area has a higher sound speed, making the number of eigenrays reaching the receiving point more and the multi-path arrival structure more complex. The arrival structure formed by sea surface reflected eigenrays is at the earlier position of the overall arrival structure and has relatively strong energy. Owing to the influence of subtropical water over the northwest Pacific Ocean on the sound speed profile, the time of some eigenrays arriving at the receiving point is earlier, and the length of multi-way arrival structure on the time axis is prolonged.

Modal intensity fluctuation during dynamic propagation of internal solitary waves in shallow water

Internal solitary wave (ISW) is a kind of nonlinear internal wave commonly observed in the shallow water, which has the characteristics of large amplitude, short period and strong current velocity. With the distribution of the temperature and the salinity in the water column perturbed by ISWs, the sound speed profile becomes range-dependent, and thus affecting the characteristics of the underwater acoustic propagation. The ISWs usually propagate at a speed of the order of 1 m/s , and moving internal waves cause the energy in each acoustic mode to fluctuate dramatically. In this paper, the modal intensity is defined as the squared modulus of the modal coefficient, and is used to measure the sound energy in each mode. Based on the coupled mode theory, the expression of the acoustic modal intensity during the propagation of internal waves is derived in this paper, and the modal intensity is taken as the linear superposition of the oscillating term and the trend term. Most of previous researches were limited to the study of the time-varying characteristics of the acoustic modal intensity during the propagation of internal waves in the time domain or frequency domain. In this paper, the mechanism of modal intensity fluctuations is studied simultaneously in the time domain and the frequency domain with the aid of the short-time Fourier transform. Both the theoretical derivation and the numerical simulation show that the internal solitary wave gives rise to the energy transfer among acoustic modes, i.e., the mode coupling. The dynamic propagation of internal waves further leads to the modal interference, which behaves as an oscillating term in the modal intensity, and causes the modal intensity to fluctuate rapidly with time. The amplitude of the trend term changes with time due to the mode stripping (the difference in attenuation coefficients between different modes), which in turn adds a time-varying offset to the oscillations induced by the modal interference. The trend of the modal intensity and the time-varying characteristics of the amplitude of each frequency component in the oscillating term are closely associated with the modal attenuation. Meanwhile, the depth-integrated intensity is chosen as the measure of the total received acoustic intensity, and the influences of modal intensity fluctuations on the acoustic energy at the receivers during the propagation of internal waves are studied. It is demonstrated that the modal intensity with high energy which oscillates most dramatically will dominate the temporal variation of the received acoustic energy.

Characteristics of long-range sound propagation in western Pacific

Acoustic signals can travel thousands of kilometers in seawater, and the characteristics of long-range sound propagation are different from short range propagation. This paper is based on a long-range underwater acoustic experiment data carried in the western Pacific Ocean, whose farthest propagation distance is nearly 2000km. The ocean environment information and vertical line array information are carefully processed. We analyze the attenuation in the seawater of long-distance acoustic propagation and multi-path arrival structure characteristics under the complete acoustic channel environment of the ocean. In terms of the attenuation law of long-distance propagation energy, with the increase of propagation distance, the effect of seawater absorption on the attenuation of sound energy becomes prominent, and the selection of absorption coefficient is very important for accurate prediction of sound field energy. Absorption in seawater of low frequency signals is small, and the transmission loss of acoustic signal with 100Hz center frequency only increases by about 6dB when the propagation distance is from 1000km to 2000km. In terms of multi-path arrival structure characteristics of deep-sea acoustic channel for long-distance sound propagation, the thermocline sound velocity profile in the experimental sea area has higher sound speed, which makes the number of eigenrays reaching the receiving point more and the multi-path arrival structure more complex. The arrival structure formed by sea surface reflected eigenrays is in the earlier position of the overall arrival structure and has relatively strong energy. Due to the influence of subtropical water over the northwest Pacific Ocean on the sound speed profile, the time of some eigenrays arriving at the receiving point is earlier, and the length of multi-way arrival structure on the time axis is prolonged.

A Universal Method to Eliminate the Effect of Sounding Velocity Errors on Multibeam Sounding Data

The presence of sound velocity errors (SVEs) is common in multibeam sounding. Existing methods are good at eliminating these errors in the area with flatter seabed terrains but are not suitable for deep and complex seabed terrains. Therefore, a universal method is proposed in this paper to eliminate these errors in various depth and terrain areas with a regression model and the equivalent sound speed profile (ESSP). The vertical biases are calculated at these homonymy points of the main survey line and the inner swaths of the auxiliary survey line firstly. Then, a regression model is built by associating the vertical bias with the initial incident angle and travel time, and the regression coefficients are estimated with the help of the partial least squares (PLS) method. On the basis of the determined regression model and ESSP, the effects of sound errors for multibeam sounding data are eliminated. The proposed method was verified by the multibeam sounding data measured in the medium-shallow and deep water areas, and the standard deviations of the absolute values of depth differences (AVDDs) after correction were both about 2 times lower than those before correction.

Fast and Accurate Underwater Acoustic Horizontal Ranging Algorithm for an Arbitrary Sound-Speed Profile in the Deep Sea

Pairwise ranging between nodes plays a crucial role in Internet-of-Underwater-Things (IoUT) networks, and it typically impacts the overall performance of such networks. As the sound speed depends on several parameters, time-of-flight-based techniques cannot work well under varying sound speeds in actual underwater conditions. Pairwise ranging algorithms that consider stratification should be studied to improve ranging accuracy. However, there is a tradeoff between underwater acoustic ranging accuracy and number of calculations. This makes it challenging to implement underwater acoustic ranging algorithms in IoUT networks. In this article, we propose an underwater acoustic horizontal ranging algorithm that rapidly and accurately estimates the horizontal range from a sender to a receiver under an arbitrary sound-speed profile in the deep sea. Simulation results show that the proposed algorithm accurately calculates the horizontal range with a low computational complexity. We validate the performance of the proposed algorithm using the data collected during an ultrashort baseline precision test in the South China Sea.

Data driven source localization using a library of nearby shipping sources of opportunity.

A library of broadband (100-1000 Hz) channel impulse responses (CIRs) estimated between a short bottom-mounted vertical line array (VLA) in the Santa Barbara channel and selected locations along the tracks of 27 isolated transiting ships, cumulated over nine days, is constructed using the ray-based blind deconvolution algorithm. Treating this CIR library either as data-derived replica for broadband matched-field processing (MFP) or training data for machine learning yields comparable ranging accuracy (∼50 m) for nearby vessels up to 3.2 km for both methods. Using model-based replica of the direct path only computed for an average sound-speed profile comparatively yields∼110 m ranging accuracy.

Ocean Front Reconstruction Method Based on K-Means Algorithm Iterative Hierarchical Clustering Sound Speed Profile

As one of the most common mesoscale phenomena in the ocean, the ocean front is defined as a narrow transition zone between two water masses with obviously different properties. In this study, we proposed an ocean front reconstruction method based on the K-means algorithm iterative hierarchical clustering sound speed profile (SSP). This method constructed the frontal zone from the perspective of SSP. Meanwhile, considering that acoustic ray tracing is a very sensitive tool for detecting the location of ocean fronts because of the strong dependence of the transmission loss (TL) on SSP structure, this paper verified the feasibility of the method from the perspective of the TL calculation. Compared with other existing methods, this method has the key step of iterative hierarchical clustering according to the accuracy of clustering results. The results of iterative hierarchical clustering of the SSP can reconstruct the ocean front. Using this method, we reconstructed the ocean front in the Gulf Stream-related sea area and obtained the three-dimensional structure of the Gulf Stream front (GSF). The three-dimensional structure was divided into seven layers in the depth range of 0–1000 m. Iterative hierarchical clustering SSP by K-means algorithm provides a new method for judging the frontal zone and reconstructing the geometric model of the ocean front in different depth ranges.

Impact of data augmentation on supervised learning for a moving mid-frequency source

Two residual networks are implemented to perform regression for the source localization and environment classification using a moving mid-frequency source, recorded during the Seabed Characterization Experiment in 2017. The first model implements only the classification for inferring the seabed type, and the second model uses regression to estimate the source localization parameters. The training is performed using synthetic data generated by the ORCA normal mode model. The architectures are tested on both the measured field and simulated data with variations in the sound speed profile and seabed mismatch. Additionally, nine data augmentation techniques are implemented to study their effect on the network predictions. The metrics used to quantify the network performance are the root mean square error for regression and accuracy for seabed classification. The models report consistent results for the source localization estimation and accuracy above 65% in the worst-case scenario for the seabed classification. From the data augmentation study, the results show that the more complex transformations, such as time warping, time masking, frequency masking, and a combination of these techniques, yield significant improvement of the results using both the simulated and measured data.

Three-dimensional modeling of T-wave generation and propagation from a South Mid-Atlantic Ridge earthquake.

A three-dimensional (3D) hybrid modeling method is used to study the generation and propagation of T waves in the ocean triggered by a Southern Mid-Atlantic Ridge earthquake. First, a finite-element method model named SPECFEM3D is used to propagate seismic waves in the crust and acoustic waves in the ocean for the T-wave generation in a 200 × 50 km area near the epicenter. A 3D parabolic equation (PE) method is then used to propagate the T waves in the ocean for about 850 km further to the hydrophone stations deployed by the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) near Ascension Island. All of the simulations considered the realistic bathymetry and water sound speed profile. The SPECFEM3D results suggest that T waves with clear modal features could be generated by the concentration of reflected head waves in two depressions 40 km away from the epicenter. To compare with the hybrid modeling method for calculating T-wave propagation losses and arrival azimuths at the CTBTO hydrophones, point source simulations using the 3D PE model from the T waves source locations, identified with SPECFEM3D, were also implemented. The advantages and limitations of each approach are discussed.

Joint Tracking of Source and Environment Using Improved Particle Filtering in Shallow Water

Shallow water is a complex sound propagation medium, which is affected by the varying spatial–temporal ocean environment. Taking this complexity into account, the classical processing techniques of source localization and environmental inversion may be improved. In this work, a joint tracking approach for the moving source and environmental parameters of the range-dependent and time-evolving environment in shallow water is presented. The tracking scheme treats both the source parameters (e.g., source depth, range, and speed) and the environmental parameters (e.g., water column sound speed profile (SSP) and sediment parameters) at the source location as unknown variables that evolve as the source moves. To counter sample impoverishment and robustly characterize the evolution of the parameters, an improved particle filter (PF), which is an extension of the standard PF, is proposed. Two examples with simulated data in a slowly changing environment and experimental data collected during the ASIAEX experiment are utilized to demonstrate the effectiveness of the joint approach. The results show that we were able to track the source and environmental parameters simultaneously, and the uncertainties were evaluated in the form of time-evolving posterior probability densities (PPDs). The performance comparison confirms that the improved PF is superior to the standard PF, as it can reduce the parameter uncertainties. The tracking capabilities of the improved PF were verified with high accuracy in real-time source localization and well-estimated rapidly varying parameters. Moreover, the influence of different particle numbers on the improved PF tracking performance is also illustrated.

Influence of temperature-salinity-depth structure of the upper-ocean on the frequency shift of Brillouin LiDAR.

Brillouin-based LiDAR is an alternative remote sensing technique for measuring the distribution profiles of temperature, salinity, and sound speed in the upper ocean mixed layer. Its principle is based on the dependence of Brillouin frequency shift on the temperature, salinity, and depth of ocean. Therefore, it is necessary to investigate the effect of various seawater parameters on Brillouin frequency shift for ocean remote sensing by using the Brillouin LiDAR. Here we theoretically and experimentally investigate the influence of temperature, salinity, and pressure (depth) of seawater on Brillouin frequency shift in the upper ocean for the first time. Numerical simulations of the distribution profiles of temperature, salinity, and Brillouin frequency shift in the upper-ocean mixed layers of East China Sea and South China Sea were performed, respectively, by employing the Brillouin equations and the World Ocean Atlas 2018 (WOA18). A special ocean simulation system was designed to carry out the stimulated Brillouin scattering (SBS) experiments for validating the numerical simulations. The results show that the seawater temperature is the most important factor for the Brillouin frequency shift in the upper-ocean mixed layer compared with the salinity and pressure. At the same salinity and pressure, the frequency shift increases by more than 10 MHz for every 1 °C increase in temperature. Also, the differences of Brillouin frequency shift between experimental and theoretical values at the same parameter conditions were analyzed. The experimental results coincide well with the theoretical simulations. This work is essential to future applications of Brillouin LiDAR in remote sensing of the temperature, salinity, or sound velocity profiles of ocean.

Estimation of sound speed profiles in deep water using perturbative inversion

A method to invert for the local sound speed profile (SSP) using only acoustic wavenumbers is proposed. Ocean sounds can be treated as acoustic energy trapped as discrete modes within the water column. Using estimated Eigenvalues (wavenumbers) from one or more modes, a method to numerically invert for the SSP can be posed as a linear Fredholm integral equation of the first kind. Therefore, the vertical SSP can be estimated with a well-placed, sufficiently long, array at one or more frequencies. Though this inversion can be unstable and non-unique, recent improvements in sparse inversions can lead to robust estimates even without an accurate starting SSP. Using the perturbative difference between the estimated wavenumbers and those calculated from the acoustic kernel, both the SSP and kernel are updated each iteration. Careful consideration must be made of the acoustic frequency, number of modes, a priori environmental information (e.g., water depth), and array length. The method will be first demonstrated on simulated recordings based on the LIDDEX data set. [Work supported by ONR.]