Shallow Water Experiment Research Articles

Frequency difference-wavenumber analysis for direction-of-arrival estimation in sparse vertical array

Frequency–wavenumber (f–k) analysis can determine the direction-of-arrival (DOA) for broadband signals captured by a vertical array [M. J. Hinich, J. Acoust. Soc. Am., 69, 732–737 (1981)]. The sparse vertical array generates numerous sidelobes in the f–k domain due to aliasing errors resulting from the spatial sampling. This presentation introduces the frequency difference-wavenumber (△f–k) analysis, expanding the application of f–k analysis to the sparse vertical array by adopting the concept of frequency difference. The relationship between the frequency difference beamforming and the △f–k analysis is also discussed. Experimental results verify the effectiveness of the proposed △f–k analysis in estimating the DOA of snapping shrimp clicks (11–24 kHz) recorded using a sparse vertical array in a shallow water experiment. During the experiment, a vertical array with an element spacing of 3.75 m (i.e., design frequency = 200 Hz) is utilized, which is extremely sparse because it corresponds to 27.5 wavelengths at the lowest frequency.

Experimental research on signal sensing of distributed acoustic sensing optical fiber based on Φ-OTDR in shallow water

The distributed acoustic sensing (DAS) technology based on phase-sensitive optical time domain reflectometry (Φ-OTDR) has been widely and well applied on land. Meanwhile, the distributed acoustic sensing optical fiber (DASF) based on Φ-OTDR, as a new type of sensor, is still in the initial stage of research, gets much attention in recent years because of its long-distance monitoring, high sensitivity, anti-electromagnetic interference, good concealment and so on. Performances of DASF in sensing different kinds of acoustic source signals were given by experiments in shallow water, which included single frequency pulse signal in the fixed position, the moving single frequency continuous pulse signal, the moving broadband signal, and the signal generated by the sailing surface target. Depth of the active sound source was changed to examine the performance of DASF in sensing signals in different depths. The specific experimental process was given, and the experimental results were processed and analyzed. Additionally, wave components of data generated from of the sailing surface vessel were explored with the time delay difference between the equivalent array elements of DASF. Results show that DASF can sense the above varieties of underwater acoustic signals well, and the physical field generated by the sailing surface vessel in shallow water include acoustic field and flow field, in which the propagation velocity of the former is faster than that of the latter.

Shallow Water Experiment of OFDM Underwater Acoustic Communications

The large variability of communication properties of underwater acoustic channels, and especially the strongly varying instantaneous conditions in shallow waters, is a challenge for the designers of underwater acoustic communication (UAC) systems. The use of phase modulated signals does not allow reliable data transmission through such a tough communication channel. However, orthogonal frequency-division multiplexing (OFDM), being a multi-carrier amplitude and phase modulation technique applied successfully in the latest standards of wireless communications, gives the chance of reliable communication with an acceptable error rate. This paper describes communication tests conducted with the use of a laboratory model of an OFDM data transmission system in a shallow water environment in Wdzydze Lake.

Interference Pattern Anomaly of an Acoustic Field Induced by Bottom Elasticity in Shallow Water

This paper reports the interference pattern of an acoustic field in the 100–300 Hz frequency band observed in a shallow water experiment. Assuming there is a conventional fluid sea bottom, the observed interference pattern is first demonstrated to potentially be abnormal, as a measured waveguide invariant of 1.03 corresponding to the 200–300 Hz frequency band could indicate that the bottom sound speed is relatively high, which is inconsistent with another observation from the interference pattern that the sound field is dominated by only one mode if the frequency is lower than 150 Hz. The numerical analysis shows that, owing to the high bottom sound speed, the third mode can still strongly interfere with the first mode at a frequency of 150 Hz, at least. Accordingly, a dual-layer sea bottom model consisting of a fluid sediment layer and an underlying half-space elastic substrate was proposed to interpret the observed anomaly. The results reveal that the acoustic leakage attenuation due to the elastic substrate plays a major role in the observed dominance of one mode in the sound field occurring below a frequency of 150 Hz. Therefore, the deep bottom’s elasticity may have a significant impact on the interference characteristics of low-frequency acoustic fields in shallow water under certain conditions.

Supervised Classification of Sound Speed Profiles via Dictionary Learning

Abstract The presence of internal waves (IWs) in the ocean alters the isotropic properties of sound speed profiles (SSPs) in the water column. Changes in the SSPs affect underwater acoustics since most of the energy is dissipated into the seabed due to the downward refraction of sound waves. In consequence, variations in the SSP must be considered when modeling acoustic propagation in the ocean. Empirical orthogonal functions (EOFs) are regularly employed to model and represent SSPs using a linear combination of basis functions that capture the sound speed variability. A different approach is to use dictionary learning to obtain a learned dictionary (LD) that generates a nonorthogonal set of basis functions (atoms) that generate a better sparse representation. In this paper, the performance of EOFs and LDs are evaluated for sparse representation of SSPs affected by the passing of IWs. In addition, an LD-based supervised framework is presented for SSP classification and is compared with classical learning models. The algorithms presented in this work are trained and tested on data collected from the Shallow Water Experiment 2006. Results show that LDs yield lower reconstruction error than EOFs when using the same number of bases. In addition, overcomplete LDs are demonstrated to be a robust method to classify SSPs during low, medium, and high IW activity, reporting accuracy that is comparable to and sometimes higher than that of standard supervised classification methods.

Direction-of-Arrival Estimation Based on Frequency Difference-Wavenumber Analysis for Sparse Vertical Array Configuration.

Frequency-wavenumber (f-k) analysis can estimate the direction of arrival (DOA) of broadband signals received on a vertical array. When the vertical array configuration is sparse, it results in an aliasing error due to spatial sampling; thus, several striation patterns can emerge in the f-k domain. This paper extends the f-k analysis to a sparse receiver-array, wherein a multitude of sidelobes prevent resolving the DOA estimates due to spatial aliasing. The frequency difference-wavenumber (Δf-k) analysis is developed by adopting the concept of frequency difference, and demonstrated its performance of DOA estimation to a sparse receiver array. Experimental results verify the robustness of the proposed Δf-k analysis in the estimation of the DOA of cracking sounds generated by the snapping shrimps, which were recorded by a sparse vertical array configuration during the shallow water experiment.

Dual parameters optimization [formula omitted]-LMS for estimating underwater acoustic channel with uncertain sparsity

The sparse norm constraint (l0,l1,l2 and lp) least mean square algorithm (LMS) is established technique for modeling sparse systems. However, when applied in target systems with uncertain sparsity, such as temporal-spatial-varying sparse underwater acoustic (UWA) channel, the parameters tuning (the step-size and parameter p) of lp-LMS faces significant challenges. In this paper, with the purpose to simplify the complicated dual-parameter selection problem via gradient strategy, a dual parameters optimization lp-LMS (DPO-lp-LMS) algorithm is derived by iteratively adjusting the step-size and the parameters p in parallel along the descent gradient. Convergence analysis of the proposed algorithm is given. A numerical simulation under varying sparsity systems exhibits that the proposed algorithm outperforms the lp-LMS algorithms driven by the existing optimization approaches in convergence speed and steady-state error. Meanwhile, a field shallow water experiment of UWA communication demonstrated that the proposed algorithm achieves superior performance under the framework of direct adaptation turbo equalization (DA-TEQ).

Vector Sensor Steering-Dependent Performance in an Underwater Acoustic Communication Field Experiment.

This paper shows the performance resulting from combining vector sensor directional components in an underwater acoustic communication experiment. The objective is to relate performance with transmission direction and range. Receiver structures based on beamforming and passive time-reversal are tested in order to quantify and compare the steerability impact of vector sensor directional components. A shallow water experiment is carried out with a bottom fixed two-axis pressure-gradient vector sensor. A ship suspended acoustic source transmits coherent modulated communication signals at various ranges and from several directions. Results show that one vector sensor can provide an up to 10 times smaller error bit rate than a pressure sensor, favoring communication robustness without size penalty.

Dictionary learning for classification of sound speed profile in the ocean

Internal waves (IWs) are waves that propagate along density gradients within the water column and alter the isotropic properties of sound speed profiles (SSPs). Changes in the SSPs modify the acoustic channel ducts and affect underwater acoustic propagation, causing most of the energy to be dissipated into the seabed due to the downward refraction of sound waves. Therefore, variations in the SSP must be considered when modeling acoustic propagation in the ocean. It has been proved that Dictionary learning (DL), an unsupervised machine learning method, succeeds in sparsely representing signals by employing a few non-orthogonal basis functions (atoms) learned from data. In this work, we use the ability of learned dictionaries (LDs) for data representation and thus train class-specific dictionaries to capture relevant features from labeled data within a supervised learning setting. We developed an LD-based supervised framework for SSP classification and compared it with state-of-the-art models. The algorithms presented in this work are trained and tested on data collected from the shallow water experiment 2006. Results show that overcomplete DL is a robust method to classify SSPs during IW activity, reporting comparable and higher accuracy than standard supervised classification methods. [Work supported by ONR, Grants No. N00014-21-1-2424 and N00014-21-1-2760.]

High-light inhibition of two submerged macrophytes in a shallow water experiment

The negative effects, caused by high light, on algae, terrestrial and marine aquatic plants are well documented; those negative effects on freshwater submerged plants are, however, not well known. We determined the negative effects of two common submerged species, Myriophyllum spicatum and Vallisneria natans, on their growth and reproduction in a shallow water experiment along an irradiance gradient. Our results highlighted that the plant mass, relative growth rate and shoot height of V. natans and M. spicatum, and root mass and root length:root mass of M. spicatum and leaf mass and shoot height:shoot mass of V. natans were significantly negatively affected in shallow water with high-light regime (>50 % of full light). While the ramet number of the two species was stimulated by from 20.0 to 36.4 %, and root length, root:shoot, chlorophyll (a:b), chlorophyll (a + b), leaf carbon, nitrogen and phosphorus contents of the two studied macrophytes were not significantly impacted by light. Our results indicated that the high-light inhibition of plant growth was greater on the shoots than on the roots of the plants, although these effects were significantly different between the two studied submerged species and among the measured traits. Accordingly, we should avoid negative effects caused by high light to improve the performance of submerged species when we conduct submerged aquatic vegetation restoration programmes in eutrophic lakes.

Passive acoustic tracking of an unmanned underwater vehicle using bearing-Doppler-speed measurements.

Tracking unmanned underwater vehicles (UUVs) in the presence of shipping traffic is a critical task for passive acoustic harbor security systems. In general, the vessels can be tracked by their unique acoustic signature caused by machinery vibration and cavitation noise. However, cavitation noise of UUVs is quiet relative to that of ships. Furthermore, tracking a target with bearing-only measurements requires the observing platform to maneuver. In this work, it is demonstrated that it is possible to passively track an UUV from its high-frequency motor noise using a stationary array in a shallow-water experiment with passing boats. The motor noise provides high signal-to-noise ratio measurements of the bearing, range rate, and speed, which we combined in an unscented Kalman filter to track the target. First, beamforming is applied to estimate the bearing. Next, the range rate is calculated from the Doppler effect on the motor noise. The propeller rotation rate can be estimated from the motor signature and converted to the speed using a pre-identified model of the robot. The bearing-Doppler-speed measurements outperformed the traditional bearing-Doppler target motion analysis: the bearing, bearing rate, range, and range rate accuracy improved by a factor of 2×, 16×, 3×, and 6×, respectively. Finally, the robustness of the tracking solution to an unknown vehicle model is evaluated.

Long-Term Effect of Barotropic Instability across the Moat in Double-Eyewall Tropical Cyclone–Like Vortices in Forced and Unforced Shallow-Water Models

Abstract Secondary eyewall formation and the ensuing eyewall replacement cycles may take place in mature tropical cyclones (TCs) during part of their lifetime. A better understanding of the underlying dynamics is beneficial to improving the prediction of TC intensity and structure. Previous studies suggested that the barotropic instability (BI) across the moat (aka type-2 BI) can make a substantial contribution to the inner-eyewall decay through the associated eddy radial transport of absolute angular momentum (AAM). Simultaneously, the type-2 BI can also increase the AAM of the outer eyewall. While the previous studies focused on the early stage of the type-2 BI, this paper explores the long-term effect of the type-2 BI and the underlying processes in forced and unforced shallow-water experiments. Under the long-term effect, it will be shown that the inner eyewalls repeatedly weaken and strengthen (while the order is reversed for the outer eyewalls). Sensitivity tests are conducted to examine the sensitivity of the long-term effect of the type-2 BI to different vortex parameters and the strength of the parameterized diabatic heating. Implication of the long-term effect for the intensity changes of the inner and outer eyewalls of real TCs are also discussed.

Array shape calibration with phase unwrapping techniques for highly deformed arrays

Flexible sensor arrays, such as towed and bottom-mounted arrays, typically suffer from large shape deformations, which seriously affect the results of array processing. In this article, an innovative array shape calibration method with phase unwrapping techniques for highly deformed arrays is proposed. The deformed array is divided into several subarrays, and the first subarray is assumed to suffer from slight shape deformations which can be pre-calibrated. With the consideration of highly deformed arrays, uncalibrated sensors in other subarrays would have serious position mismatches. The phase differences between uncalibrated and pre-calibrated sensors are probably larger than 2 π , which lead to phase ambiguity problems. A phase unwrapping technique is proposed to efficiently solve the phase ambiguity problem by considering the physical structure constraints of the deformed array, such as intersensor distance and bending angle. Then, sensor positions in highly deformed arrays are calibrated with multiple target directions. Simulation results evaluate the performance of the proposed calibration method, and the SwellEx-96 shallow water experiment data set is utilised to demonstrate the effectiveness of the proposed method.

Roles of Barotropic Instability across the Moat in Inner Eyewall Decay and Outer Eyewall Intensification: Essential Dynamics

AbstractIntense tropical cyclones (TCs) often experience secondary eyewall formations and the ensuing eyewall replacement cycles. Better understanding of the underlying dynamics is crucial to make improvements to the TC intensity and structure forecasting. Radar imagery of some double-eyewall TCs and a real-case simulation study indicated that the barotropic instability (BI) across the moat (aka type-2 BI) may play a role in inner eyewall decay. A three-dimensional numerical study accompanying this paper pointed out that type-2 BI is able to withdraw the inner eyewall absolute angular momentum (AAM) and increase the outer eyewall AAM through the eddy radial transport of eddy AAM. This paper explores the reason why the eddy radial transport of eddy AAM is intrinsically nonzero. Linear and nonlinear shallow water experiments are performed and they produce expected evolutions under type-2 BI. It will be shown that only nonlinear experiments have changes in AAM over the inner and outer eyewalls, and the changes solely originate from the eddy radial transport of eddy AAM. This result highlights the importance of nonlinearity of type-2 BI. Based on the distribution of vorticity perturbations and the balanced-waves arguments, it will be demonstrated that the nonzero eddy radial transport of eddy AAM is an essential outcome from the intrinsic interaction between the mutually growing vortex Rossby waves across the moat under type-2 BI. The analyses of the most unstable mode support the findings and will further attribute the inner eyewall decay and outer eyewall intensification to the divergence and convergence of the eddy angular momentum flux, respectively.

Design and Performance Study for Electrothermally Deep-Sea Drive Microunits Using a Paraffin Phase Change Material.

Considering the further exploration of the ocean, the requirements for deep-sea operation equipment have increased. Many problems existing in the widely used deep-sea hydraulic system have become increasingly prominent. Compared with the traditional deep-sea hydraulic system, actuators using a paraffin phase change material (PCM) have incomparable advantages, including lightweight structure, low energy consumption, high adaptability to the deep sea, and good biocompatibility. Thus, a deep-sea drive microunit (DDM) based on paraffin PCM is proposed in this paper. The device adopts a flexible shell, adapting to the high-pressure environment of the deep-sea based on the principle of pressure compensation. The device realizes the output of displacement and force through the electrothermal drive, which can be used as actuator or power source of other underwater operation equipment. The microunit successfully completes the functional verification experiments in air, shallow water, and hydrostatic pressure of 110 MPa. In accordance with experimental results, a reasonable control curve is fitted, highlighting its potential application in deep-sea micro electro mechanical systems, especially in underwater soft robot.

Passive acoustic detection and tracking of an unmanned underwater vehicle from motor noise

Using passive acoustics to distinguish unmanned underwater vehicles from other marine traffic in a complex environment and tracking a vehicle to understand its intent is critical for harbor security. Ships and boats can be classified by their unique acoustic signature due to machinery vibration and detection of envelope modulation on (cavitation) noise. However, cavitation noise of unmanned underwater vehicles is quieter than these vessels, and bearing-only measurements using a stationary array are insufficient for tracking. Tracking accuracy depends on the quality of acoustic measurements, such as high SNR, and observability, estimating vehicle state from the data available. In this work, we demonstrate that it is possible to passively track a vehicle from high-frequency motor noise using a stationary array in a shallow water experiment with passing boats. Motor noise provides high SNR measurements of bearing, bearing rate, propeller rotation, and range rate that are combined in an Unscented Kalman Filter to track the vehicle. First, receiver operating characteristic curves are generated to evaluate detection and false alarms. Conventional beamforming is applied to estimate bearing and bearing rate. Range rate is calculated from the Doppler effect of the motor noise. Propeller rotation is estimated from sideband spacings in the motor signature. [Work supported by Draper, ONR, and DARPA.]

Sequential Geoacoustic Inversion Using an Improved Kalman Particle Filter

Geoacoustic inversion is an efficient method to study the physical properties and structure of ocean bottom while sequential geoacoustic inversion is a challenging task due to the complexity and non-linearity of the underwater environment. In this paper, an ensemble Kalman Particle filter is described to address the sequential geoacoustic inversion problem of range-dependent environment in shallow water. This filter combines the advantages of Particle filter and ensemble Kalman filter so its ability of tracking dynamical geoacoustic parameters is improved. The proposed filtering method is demonstrated with simulated data in a changing oceanic environment and outperforms Particle filter and ensemble Kalman filter. This method is also tested in sea-trial data collected from a shallow-water experiment in the East China Sea. The inverted sound speed in sediment is consistent with in situ measurement and the error between transmission loss predicted by inverted parameters, and the experimental transmission loss is small.

Superimposed training low probability of detection underwater communications.

This paper proposes a superimposed training method for low probability of detection underwater acoustic communications. A long pilot sequence was superimposed to the message for equalization and synchronization purposes. A fast Hadamard transform (FHT) estimated the channel impulse response and compressed the pilot energy. A Wiener filter performed equalization. The interference signal was removed using hyperslice cancellation by coordinate zeroing. An inverse FHT decompressed the remaining sequence energy and the message was retrieved. Results from a shallow water experiment presented bit error rates <10-2 for signal-to-noise ratios <-8 dB.

Synchrosqueezing transform for geoacoustic inversion with air-gun source in the East China Sea

This paper presents a geoacoustic inversion method combining with warping transform and synchrosqueezing transform to improve the precision of extracting modal dispersion curves in shallow water waveguide. Dispersive characteristic is often used to invert geoacoustic parameters, while the dispersion curves are hard to be extracted in short range. Warping transform can compensate the nonlinearity of received signal but the frequency resolution is still inaccurate. Synchrosqueezing transform sharpens the frequency resolution of warped modes, which makes the extracted dispersion curves more accurate. The comparison of simulation shows that the result using combined method is closer to the preset value when implementing geoacoustic inversion of dispersion characteristics. Furthermore, this method is used to invert the sea bottom parameters of a shallow water experiment in the East China Sea. The Bayesian method and insitu measurement are used to verify the reliability of inversion results.

Wave packet focusing in shallow water

ABSTRACT In coastal engineering, as shoaling waves break in shallow water, most wave-breaking research has been focused on depth-induced wave breaking. However, violent wave breaking under storm conditions may be caused by superposition of many shoaling wave components. In order for simulating extreme waves in open ocean, theories to focus wave-packets, assuming that wave speed of each wave component is unchanged during propagation (i.e. deep water or shallower water without bathymetry changes), have been derived, while shoaling effects of the focusing process in shallower waters have not been considered in the previous studies. The extension to shoaling coastal wave-packets may aid in simulating extreme coastal wave breaking under violent storm conditions via laboratory experiments. Here, we derive the general wave-packet focusing conditions for arbitrary water depth. The proposed conditions were used to simulate shoaling wave-packet focusing on flat and sloped bottoms in shallow water experiments for validation purposes. The effects of depth-induced wave breaking in the focusing wave groups are discussed in this paper. The current focusing technique can fully control the focus location and time in wave experiments with an arbitrary bottom structure, which may be useful for further extreme wave research in coastal engineering.