Inversion In Shallow Water Research Articles

Extracting shallow water depth from the fusion of multi-temporal ICESat-2 data and multi-spectral imageries

With the development of satellite remote sensing and laser altimetry data, the fusion of laser altimetry data and multi-spectral images for shallow water depth inversion has become an economically convenient way. However, there are few methods that take into account the temporal dimension of data to integrate the results of water depth inversion in multiple temporal phases. In response to this issue, this article proposed a shallow water depth inversion method that integrates multi-source and multi-temporal remote sensing data. This method utilized the random forest (RF) algorithm to estimate the water depth values at different time, taking into account the contextual information of Sentinel-2 imagery and using the overall least squares as the theoretical model to fuse the multi-temporal water depth inversion results. This article took the Yongle Islands in the South China Sea as the research area and conducted the shallow water inversion experiments using ICESat-2 (Ice, Cloud and Land Elevation Satellite 2) data from 5 temporal phases and one Sentinel-2 imagery. The results show that the mean value of RMSE (root mean square error) and R2 (determination coefficient) of the proposed method using single temporal imagery was 1.53m and 0.7610, which outperformed the inversion accuracy of traditional methods that ignore image context information. The RMSE and R2 of the multi-temporal fusion model was 1.15m and 0.8622, which was 0.08m and 0.0199m higher than existing median filtering fusion method.

Bayesian geoacoustic inversion in shallow water with vertical coherence of ship-radiated noise

Spatial structure of underwater acoustic field depends strongly on the geoacoustic properties of the seabed. The geoacoustic parameters can be estimated using the spatial coherence dominated by a single broadband source. In this paper, geoacoustic inversion of a shallow water environment is carried out using the vertical coherence of ship-radiated noise at a close range. Data were measured in an experiment in the South China Sea, and the vertical coherence is extracted from a single hydrophone pair in the vertical line array. The closest point of the passing research ship approach is determined first, and then the broadband coherence curves are extracted as the input for the inversion algorithm. Due to the lack of an appropriate parametrization, the trans-dimensional inversion method combined with the auto-regressive error model is adopted in this paper. The inversion results show that the sound speed is the most sensitive, followed by the density, and then the attenuation coefficient is the least sensitive, which is consistent with previous works. The data error hypothesis is verified via a posterior examinations.

Monitoring Short-Term Morphobathymetric Change of Nearshore Seafloor Using Drone-Based Multispectral Imagery

Short-term changes in shallow bathymetry affect the coastal zone, and therefore their monitoring is an essential task in coastal planning projects. This study provides a novel approach for monitoring shallow bathymetry changes based on drone multispectral imagery. Particularly, we apply a shallow water inversion algorithm on two composite multispectral datasets, being acquired five months apart in a small Mediterranean sandy embayment (Chania, Greece). Initially, we perform radiometric corrections using proprietary software, and following that we combine the bands from standard and multispectral cameras, resulting in a six-band composite image suitable for applying the shallow water inversion algorithm. Bathymetry inversion results showed good correlation and low errors (<0.3 m) with sonar measurements collected with an uncrewed surface vehicle (USV). Bathymetry maps and true-color orthomosaics assist in identifying morphobathymetric features representing crescentic bars with rip channel systems. The temporal bathymetry and true-color data reveal important erosional and depositional patterns, which were developed under the impact of winter storms. Furthermore, bathymetric profiles show that the crescentic bar appears to migrate across and along-shore over the 5-months period. Drone-based multispectral imagery proves to be an important and cost-effective tool for shallow seafloor mapping and monitoring when it is combined with shallow water analytical models.

Study of the 24 September 2013 Oman Sea tsunami using linear shallow water inversion

Study of the 24 September 2013 Oman Sea tsunami using linear shallow water inversion

An Improved Particle Filtering Technique for Source Localization and Sound Speed Field Inversion in Shallow Water

Both source localization and environmental inversions are practical problems for long-standing applications in underwater acoustics. This paper presents an approach of the moving source localization and sound speed field (SSF) inversion in shallow water. The approach is formulated in a state-space model with a state equation for both the source parameters (e.g., source depth, range, and speed) and SSF parameters (first three empirical orthogonal function coefficients, EOFs) and a measurement equation that incorporates underwater acoustic information via a vertical line array (VLA). As a sequential processing algorithm that operates on nonlinear systems with non-Gaussian probability densities, an improved sequential importance resampling type particle filtering (SIR PF) is proposed to counter degeneracy. The improved PF performs tracking of source and SSF parameters simultaneously, and evaluates their uncertainties in the form of time-evolving posterior probability densities (PPDs). The performance of improved PF is illustrated with well-tracked simulations of real-time source localization and time-varying SSF inversion. Moreover, the influence of different particle numbers on PF tracking accuracy and computational cost is also demonstrated. Simulation results show that the high-particle-number PF has an outperform performance. For a given hardware system, the reasonable compromise between accuracy and computational cost is a matter of tradeoff.

Identification of interference normal mode pairs of low frequency sound in shallow water

The interference characteristics of normal modes in low-frequency broadband sound can be applied to source localization and environmental parameter inversion in shallow water. However, the identification ambiguity of interference normal mode pairs generally occurs in practical applications due to unknown source position, some weakly-excited normal modes, mismatched environmental model, etc. For the applications of a horizontal line array, a model-based processing approach is proposed to determine the orders of the interference normal mode pairs based on the intrinsic dispersion characteristics of interference normal mode pairs in the received signals and the range-independent properties of the array beam output angles. Firstly, the normal mode pair filtering is achieved by using the WARPING transform of the signal autocorrelation function in the element domain of the horizontal line array. Then, the arrival angles of the filtered interference normal mode pairs are estimated by using array beamforming. Finally, the estimated beam output angles are matched with the replica values computed by sound field model. The approach is verified by using the explosive pulse signals received by the seafloor-deployed 32-element horizontal line array at the North Yellow Sea in 2011. Furthermore, some simulations are involved to analyze the effects of environmental parameter mismatches including water sound speed profile, sea bottom parameters and water depth on the identification performance of interference normal mode pairs. The results show that the water depth is a major factor influencing the extracted values of the beam output angles of interference normal mode pairs. The approach might fail when the water depth mismatch exceeds 14% of the practical value. However, the effects of water sound speed profile mismatch and sea bottom parameters mismatch are negligible. The effect of signal-to-noise ratio in the element domain on a horizontal line array is also simulated in order to analyze the limitation of identification performance, which shows that the required signal-to-noise ratio in the element domain should be more than 2 dB.

Sequential inversion of self-noise using adaptive particle filter in shallow water.

The geoacoustic inversion based on a horizontal towed array sonar receiving tow-ship noise has demonstrated a promising technique for the parameter inversion in shallow water. In order to characterize the evolution of parameters in the time-varying environment, the adaptive particle filter for the sequential inversion is presented in this paper. The inversion problem is formulated as a dynamic and nonlinear process in the Bayesian framework, due to the fact that the self-noise is recorded sequentially in space and time. To deal with the interparameter correlations and time-varying noise process, the adaptive sequential importance sampling is carried out based on the estimated covariance matrix of parameters that is updated on-line. And the particles are proposed with an adaptive shift to handle the rapidly varying parameters. The tonal components at low frequencies of the self-noise are used in the inversion. The sequential inversion method is verified through the processing of both synthetic data and the sea-trial data in the shallow water environment. The results show that the adaptive particle filter method can achieve a more stable and accurate estimate than successively running global optimization algorithms and can do better than particle filter inversion in a rapidly varying environment.

Sediment sound speed inversion at low frequencies in shallow water

A direct method previously developed for shallow water inversion is presented here along with the assumptions for its convergence and improvements for the solution of a more complex inverse problem. The method estimates sediment sound speed and follows discontinuities as the sediment layer properties change. Sediment thickness is also calculated. The approach is fast in contrast to other techniques that navigate a multi-dimensional search space. Implementation requires low-frequency measurements at a horizontal array and a source anywhere in the water column with only the continuous spectrum available. Several assumptions are made which appear restrictive at first but can be eventually relaxed. Although the approach was first developed considering a constant density profile, we show how realistic density profiles can be considered. [Work supported by ONR.]

A semianalytical ocean color inversion algorithm with explicit water column depth and substrate reflectance parameterization

AbstractA semianalytical ocean color inversion algorithm was developed for improving retrievals of inherent optical properties (IOPs) in optically shallow waters. In clear, geometrically shallow waters, light reflected off the seafloor can contribute to the water‐leaving radiance signal. This can have a confounding effect on ocean color algorithms developed for optically deep waters, leading to an overestimation of IOPs. The algorithm described here, the Shallow Water Inversion Model (SWIM), uses pre‐existing knowledge of bathymetry and benthic substrate brightness to account for optically shallow effects. SWIM was incorporated into the NASA Ocean Biology Processing Group's L2GEN code and tested in waters of the Great Barrier Reef, Australia, using the Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua time series (2002–2013). SWIM‐derived values of the total non‐water absorption coefficient at 443 nm, at(443), the particulate backscattering coefficient at 443 nm, bbp(443), and the diffuse attenuation coefficient at 488 nm, Kd(488), were compared with values derived using the Generalized Inherent Optical Properties algorithm (GIOP) and the Quasi‐Analytical Algorithm (QAA). The results indicated that in clear, optically shallow waters SWIM‐derived values of at(443), bbp(443), and Kd(443) were realistically lower than values derived using GIOP and QAA, in agreement with radiative transfer modeling. This signified that the benthic reflectance correction was performing as expected. However, in more optically complex waters, SWIM had difficulty converging to a solution, a likely consequence of internal IOP parameterizations. Whilst a comprehensive study of the SWIM algorithm's behavior was conducted, further work is needed to validate the algorithm using in situ data.

Sound speed profile inversion using a horizontal line array in shallow water

It is better to use a simple configuration to enhance the applicability of ocean environment inversion in shallow water. A matched-field inversion method based on a horizontal line array (HLA) is used to retrieve the variation of sound speed profile. The performance of the inversion method is verified in the South China Sea in June, 2010. An HLA laid at bottom was used to receive signals from a bottom-mounted transducer. Inverted mean sound speed profiles from 9-hour long acoustic signals are in good agreement with measurements from two temperature chains at the sites of the source and receiver. The results show that an HLA can be used to monitor the variability of shallow-water sound speed profile.

Improving the optimization solution for a semi‐analytical shallow water inversion model in the presence of spectrally correlated noise

In coastal regions, shallow water semi‐analytical inversion algorithms may be used to derive geophysical parameters such as inherent optical properties (IOPs), water column depth, and bottom albedo coefficients by inverting sensor‐derived sub‐surface remote sensing reflectance, rrs. The uncertainties of these derived geophysical parameters due to instrumental and environmental noise can be estimated numerically via the addition of spectral noise to the sensor‐derived rrs before inversion. Repeating this process multiple times allows the calculation of the standard error and average for each derived parameter. Apart from spectral non‐uniqueness, the optimization algorithm employed in the inversion must converge onto a single minimum to obtain a true representation of the uncertainty for a given set of noise‐perturbed rrs. Failure to do so inflates the uncertainty and affects the average retrieved value (accuracy). We show that the standard approach of seeding the optimization with an arbitrary, fixed initial guess, can lead to the convergence to multiple minima, each having substantially different centroids in multi‐parameter solution space. We present the Update‐Repeat Levenberg‐Marquardt (UR‐LM) and Latin Hypercube Sampling (LHS) routines that dynamically search the solution space for an optimal initial guess, that when applied to the optimization allows convergence to the best local minimum. We apply the UR‐LM and LHS methods on HICO‐derived and simulated rrs and demonstrate the improved computational efficiency, precision, and accuracy afforded from these methods compared with the standard approach. Conceptually, these methods are applicable to remote sensing based, shallow water or oceanic semi‐analytical inversion algorithms requiring nonlinear least squares optimization.

Detecting trend and seasonal changes in bathymetry derived from HICO imagery: A case study of Shark Bay, Western Australia

The Hyperspectral Imager for the Coastal Ocean (HICO) aboard the International Space Station has offered for the first time a dedicated space-borne hyperspectral sensor specifically designed for remote sensing of the coastal environment. However, several processing steps are required to convert calibrated top-of-atmosphere radiances to the desired geophysical parameter(s). These steps add various amounts of uncertainty that can cumulatively render the geophysical parameter imprecise and potentially unusable if the objective is to analyze trends and/or seasonal variability. This research presented here has focused on: (1) atmospheric correction of HICO imagery; (2) retrieval of bathymetry using an improved implementation of a shallow water inversion algorithm; (3) propagation of uncertainty due to environmental noise through the bathymetry retrieval process; (4) issues relating to consistent geo-location of HICO imagery necessary for time series analysis, and; (5) tide height corrections of the retrieved bathymetric dataset. The underlying question of whether a temporal change in depth is detectable above uncertainty is also addressed. To this end, nine HICO images spanning November 2011 to August 2012, over the Shark Bay World Heritage Area, Western Australia, were examined. The results presented indicate that precision of the bathymetric retrievals is dependent on the shallow water inversion algorithm used. Within this study, an average of 70% of pixels for the entire HICO-derived bathymetry dataset achieved a relative uncertainty of less than ±20%. A per-pixel t-test analysis between derived bathymetry images at successive timestamps revealed observable changes in depth to as low as 0.4m. However, the present geolocation accuracy of HICO is relatively poor and needs further improvements before extensive time series analysis can be performed.

Simulation of time reversed acoustic inversion in shallow water

For simulation to time reversed acoustic inversion in any enclosure system as shallow water, we must know the impulse response of the system. Throughout this process we can reproduce an original signal at focal point by convolution of time reversed inversion. To apply this TRA simulation to shallow water environment, after extracting the impulse response about simple condition as shallow water, we analyze the acoustic focusing by TRA inversion. In result, the spatial focusing and time signal patterns can be built by TRA simulation for shallow water condition. [Supported by KORDI (Korea Ocean Research & Development Institute)]

Geoacoustic inversion in shallow water using broadband synthetic aperture and single hydrophone acoustic data

A majority of geoacoustic inversion experiments sample the acoustic field on long arrays. This paper uses a moving single hydrophone to create a large synthetic aperture array for geoacoustic inversion. Practically, this is operationally attractive compared to using long arrays. For example, one possible application is the use of autonomous underwater vehicles (AUVs) to perform acoustic field sampling and pre-processing for geoacoustic inversion. The approach comprises synthetic aperture formation and a directed Monte Carlo Bayesian broadband frequency coherent geoacoustic inversion. This is demonstrated with simulated and real data from the MAPEX2000 experiment conducted by the NATO Undersea Research Center, using only one hydrophone of a towed array and a moored source in the Mediterranean Sea. The method yielded similar results compared to an equivalent physical array.

Estimation of modal group velocities with a single receiver for geoacoustic inversion in shallow water

Due to the expense associated with at-sea sensor deployments, a challenge in underwater acoustics has been to develop methods requiring a minimal number of sensors. This paper introduces an adaptive time-frequency signal processing method designed for application to a single source-receiver sensor pair. The method involves the application of conjugate time-frequency warping transforms to improve the SNR and resolution of the time-frequency distribution (TFD) of the measured field. Such refined knowledge of the TFD facilitates efforts to extract tomographic information about the propagation medium. Here the method is applied to the case of modal propagation in a shallow ocean range independent environment to extract a refined TFD. Given knowledge of the source-receiver separation, the refined TFD is used to extract the frequency dependent group velocities of the individual modal components. The extracted group velocities are then incorporated into a computationally light tomographic inversion method. Simulated and experimental results are discussed.

A joint seismo-geoacoustic inversion in shallow water using a subsurface towed sound source

A single-hydrophone geoacoustic inversion procedure using a calibrated source is proposed and tested with experimental shallow water data. In a first step the number of sediment layers, their thicknesses and velocities are estimated using a conventional seismic approach. In a second step, the amplitude variations of each reflected arrival are used to estimate the reflection coefficients versus the incidence angle. The results are compared to numerical model solutions. With this second step, velocity estimations are refined in order to predict the observed critical angles. Attenuation and density are estimated from the absolute level of the reflection coefficient. Finally, experimental and synthetic data generated after inversion are compared.

Volumetric (tomographic) three-dimensional geoacoustic inversion in shallow water

Geoacoustic inversion is an important but difficult component for shallow water ocean acoustics. There are numerous methods in use to remotely determine bottom and geometric properties in both range-independent and range-dependent situations. While there have been some efforts to combine two-dimensional bottom estimates (range- and depth-dependent inversion slices) calculated around a receiving array into a three-dimensional (range, depth, and azimuthal) image of a region, there is only one approach in existence today, which attempts to determine consistent volumetric bottom properties using multiple arrays and multiple sources. This approach (geoacoustic tomography) will be discussed here (with final improvements via regularization).

On some possibilities and properties of matched-field geoacoustic inversion in shallow water

The aim of this paper is to estimate possibilities of matched-field geoacoustic inversion (MFI) in shallow water, and to recommend optimal arrangements of signal source and hydrophone array in variety of particular environments. We assumed ocean to be range independent with bottom consisting of homogeneous liquid layers. Sound fields were calculated as superposition of normal modes and continuous spectrum for tonal point source and vertical line array. MFI based on Bartlett processor was used. Possibilities of MFI were characterized by MFI penetration depth, sensitivity to various bottom parameters and non-uniqueness of inverted data. These characteristics were analysed as functions of frequency and the source depth and range for different values of sound attenuation in sediments and for various sound-speed profiles. To estimate possibilities of MFI in real ocean conditions, influence of array tilt and inadequacy of geoacoustic model were analysed. The influence of continuous spectrum was also discussed. Among the major results, optimal source ranges corresponding to the maximum penetration depth of MFI were calculated, and high influence of attenuation in sediments on possibilities of MFI was revealed.

Notes on broadband seabed geoacoustic inversion in shallow water

With increasing interest in shallow-water environments, where bottom interaction is a dominant effect, there is a need to acquire accurate information about seabed geoacoustic parameters. Due to the difficulties and high costs of directly measuring seabed parameters at low frequencies (LF) in shallow water (SW), seabed geoacoustic inversion from long-range propagation has become an active research area. Much progress on this subject, notably on inversion methods, has been made in the last two decades, mainly through the use of powerful numerical codes and data processing tools. Despite this, seabed geoacoustic inversion often fails to yield systematic LF seabed parameters in a broad band (such as speed/attenuation vs frequency) that are required for seabed geoacoustic modeling or for sonar performance prediction in the SW environment. This paper will discuss several basic concepts and technical issues related to SW geoacoustic inversion, including filter phase shifting, speed-attenuation coupling, hidden depth, and sea-surface effects. It shows that inverting the broadband seabed acoustic parameters is a delicate task that can often be subject to errors. These issues should be considered in designing experiments that test seabed geoacoustic inversion methods or in interpreting experimental results. [Work supported by ONR and NNSF of China.]

A numerical adjoint parabolic equation (PE) method for tomography and geoacoustic inversion in shallow water

Recently, an analytic adjoint-based method of optimal nonlocal boundary control has been proposed for inversion of a waveguide acoustic field using the wide-angle parabolic equation [Meyer and Hermand, J. Acoust. Soc. Am. 117, 2937–2948 (2005)]. In this paper a numerical extension of this approach is presented that allows the direct inversion for the geoacoustic parameters which are embedded in a spectral integral representation of the nonlocal boundary condition. The adjoint model is generated numerically and the inversion is carried out jointly across multiple frequencies. The paper further discusses the application of the numerical adjoint PE method for ocean acoustic tomography. To show the effectiveness of the implemented numerical adjoint, preliminary inversion results of water sound-speed profile and bottom acoustic properties will be shown for the YELLOW SHARK ’94 experimental conditions.