Search Results (10)

In shallow-water environments, source localization often suffers from reduced performance in conventional array signal processing techniques for frequency bands above 1 kHz due to environmental mismatch. A recently proposed technique, called the steered frequency–wavenumber (SFK) analysis method, overcomes this limitation. By incorporating beam-steering techniques into frequency–wavenumber analysis, this method enables target localization even in sparse conditions where high-frequency signals are received. This study extends the SFK method by applying various adaptive signal processing techniques, with a particular focus on the minimum-variance distortionless response and white noise gain constraint methods. Using snapping shrimp sounds from the SAVEX15 experiment, we analyzed localization performance and compared it with the Bartlett SFK approach. The snapping shrimp signals have frequency components ranging from 5 to 24 kHz and exhibit impulsive characteristics with a duration of 0.2 ms. Signals recorded by a sparse vertical array of 16 sensors, with a 60-m aperture in 100-m shallow water, enabled the localization of a source at a range of 38 m and a depth of 99.8 m. Full article

Acoustic telemetry is a tool for tracking animals, but transmitted signals from tagged animals are not always detected. Detection efficiency declines with increasing background noise, which can have both abiotic and biotic sources. The abiotic noise present in reef environments (waves, bubbles, etc.) is primarily low-frequency, but snapping shrimp create high-frequency noise that can interfere with transmission detections. Prior work in shallow coastal reefs correlated winds with less high-frequency background noise, and hypothesized that it was due to a balance of biotic and/or abiotic factors: shrimp may be less active during high wind events, and sound attenuation at the surface increases with wave height. To test this hypothesis, passive acoustic recordings from a live-bottom reef are used to quantify snapping shrimp snap rate. Snap rate was strongly correlated with temperature, and warmer environments appeared to be challenging for acoustic telemetry. However, the majority of synoptic variability in noise is shown to be driven by abiotic attenuation. Wind speed has little to no effect on snapping shrimp behavior, but has a significant inverse correlation with high-frequency noise levels due to surface attenuation of high-frequency noise, and therefore a positive effect on detection efficiency, pointing to primarily abiotic forcing behind noise variability and resulting telemetry success. This research gives context to previously collected detection data and can be leveraged to help plan future acoustic arrays in shallow, complex, and/or noisy environments, potentially predicting changes in detection range. Full article

Our study considered porous Bouligand structured polymer, comprising polymer fibres with porous spaces between them. These are more complicated structures than the non-porous Bouligand, since the addition of porosity into the material creates a secondary variable besides fibre pitch. There is currently no analytical model available to predict the modulus of such materials. Our paper explores the correlation between porosity, polymer fibre pitch angle, and flexural modulus in porous Bouligand structured polymers. Our structures were digitally manufactured using stereolithography (SLA) additive manufacturing methods, after which they were subjected to three-point bending tests. Our aim was to simply and parametrically develop an analytical model that would capture the influences of both porosity and polymer fibre pitch angle on the flexural modulus of the material. Our model is expressed as $E_f=E_{poro}(a{\theta }_f^3+b{\theta }_f^2+c{\theta }_f+d)$, and we derive this by applying non-linear regression to our experimental data. This model predicts the flexural modulus, $E_f$, of porous Bouligand structured polymer as a function of both porosity and pitch angle. Here, $E_{poro}$ is defined as the solid material modulus, $E_{solid}$, multiplied by porosity, $\varphi$ and is a linear reduction in the modulus as a function of increasing porosity, while ${\theta }_f$ signifies the polymer fibre pitch angle. This relationship is relatively accurate within the range of 10° ≤ θ_f ≤ 50°, and for porosity values ranging from $0.277\le 0.356$, as supported by our evidence to date. Full article

Snapping Shrimps (SSs) live in warm marine areas. Snapping Shrimps Noise (SSN), loud sounds generated by these underwater creatures, serves as a major source of in performance degradation by decreasing the Signal-to-Noise Ratio (SNR) for underwater acoustic communication and target detection. Thus, we propose a unified solution for SSN detection and reduction in this paper. First, Signal Presence Probability (SPP) is calculated for SSN detection, and then the SPP is provided to Non-negative Matrix Factorization (NMF) as a weight for SSN reduction. In the proposed method, SPP acts as a key factor for SSN detection and reduction. To verify the effectiveness of the proposed method, the SAVEX-15 dataset, real ocean data containing SSN, is used. As a result of SSN detection, it was confirmed that SPP presented the highest performance in the Receiver Operating Characteristics curve, and we achieved 0.014 higher Area Under the Curve compared to competing methods. In addition, Continuous Wave and Linear Frequency Modulation signals were set as target signals and combined with the SAVEX-15 data for evaluation of noise reduction performance. As a result, the performance of the SPP-weighted NMF (WNMF) presented at least 2 dB higher SNR and SDR while maintaining less LSD compared to the Optimally Modified Log Spectral Amplitude estimator and NMF. Full article

Pistol shrimp generate cavitation bubbles. Cavitation impacts due to bubble collapses are harmful phenomena, as they cause severe damage to hydraulic machinery such as pumps and valves. However, cavitation impacts can be utilized for mechanical surface treatment to improve the fatigue strength of metallic materials, which is called “cavitation peening”. Through conventional cavitation peening, cavitation is generated by a submerged water jet, i.e., a cavitating jet or a pulsed laser. The fatigue strength of magnesium alloy when treated by the pulsed laser is larger than that of the jet. In order to drastically increase the processing efficiency of cavitation peening, the mechanism of pistol shrimp (specifically when used to create a cavitation bubble), i.e., Alpheus randalli, was quantitatively investigated. It was found that a pulsed water jet generates a cavitation bubble when a shrimp snaps its claws. Furthermore, two types of cavitation generators were developed, namely, one that uses a pulsed laser and one that uses a piezo actuator, and this was achieved by mimicking a pistol shrimp. The generation of cavitation bubbles was demonstrated by using both types of cavitation generators: the pulsed laser and the piezo actuator. Full article

Snapping Shrimps (SSs) live in a warm ocean except the North and South Poles, and they are characterized by generating strong shock waves underwater using large claws. Shock waves generated by these SSs are used for marine noise research as a signal and as a noise source, because they cause a decrease in the Signal-to-Noise Ratio (SNR), acting as one of the disruptors in fields such as sonar for target detection and underwater communication. A state-of-the-art technique to detect Snapping Shrimp Noise (SSN) is Linear Prediction (LP) analysis. Using the feature where SSN occurs for a very short time, the SSN interval was detected based on the phenomenon where the residuals appear large in the SSN interval when the LP analysis is used. In this paper, we propose an SSN interval detection technique using the Likelihood Ratio (LR) as a follow-up study to the LP-analysis-based method for further performance improvements. The proposed method was used to analyze the statistical distribution characteristics of the LP residual of SSNs compared to Gaussian, Laplace, and Gamma distributions through the Goodness-Of-Fit test. Based on this, the statistical-model-based LRs of the three distributions were computed to detect the SSN interval. Comparing the proposed method with the state-of-the-art method, the proposed method achieved 0.0620, 0.0675, and 0.0662 improvements in Gaussian, Laplace, and Gamma distributions in the Receiver Operating Characteristic curve and Area Under Curve, respectively. The study results confirmed that the proposed method can operate effectively in the marine acoustic environment. This can help find accurate intervals for the automatic labeling of or reduction in SSN. Full article

In order to detect weak underwater tonals, adaptive line enhancers (ALEs) have been widely applied in passive sonars. Unfortunately, conventional ALEs cannot perform well amid impulse noise generated by ice cracking, snapping shrimp or other factors. This kind of noise has a different noise model compared to Gaussian noise and leads to noise model mismatch problems in conventional ALEs. To mitigate the performance degradation of conventional ALEs in under-ice impulse noise, in this study, a modified ALE is proposed for passive sonars. The proposed ALE is based on the least mean p-power (LMP) error criterion and the prior information of the frequency domain sparsity to improve the enhancement performance under impulse noise. The signal-to-noise ratio (SNR) gain is chosen as the metric for evaluating the proposed ALE. The simulation results show that the output SNR gain of the proposed ALE was, respectively, 9.3 and 2.6 dB higher than that of the sparsity-based ALE (SALE) and the least mean p-power ALE (PALE) when the input GSNR was −12 dB. The results of processing the under-ice noise data also demonstrate that the proposed ALE is distinguished among the four ALEs. Full article

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 ($\Delta f$–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 $\Delta f$–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. Full article

The underwater acoustic channel is remarkably dependent on the considered scenario and the environmental conditions. In fact, channel impairments differ significantly in shallow water with respect to deep water, and the presence of external factors such as snapping shrimps, bubbles, rain, or ships passing nearby, changes of temperature, and wind strength can change drastically the link quality in different seasons and even during the same day. Legacy mathematical models that consider these factors exist, but are either not very accurate, like the Urick model, or very computationally demanding, like the Bellhop ray tracer. Deterministic models based on lookup tables (LUTs) of sea trial measurements are widely used by the research community to simulate the acoustic channel in order to verify the functionalities of a network in certain water conditions before the actual deployment. These LUTs can characterize the link quality by observing, for instance, the average packet error rate or even a time varying packet error rate computed within a certain time window. While this procedure characterizes well the acoustic channel, the obtained simulation results are limited to a single channel realization, making it hard to fully evaluate the acoustic network in different conditions. In this paper, we discuss the development of a statistical channel model based on the analysis of real field experiment data, and compare its performance with the other channel models available in the DESERT Underwater network simulator. Full article

Numerous studies have evaluated the acoustic characteristics of soniferous snapping shrimp, but a few are based on long-term mooring measurements. In this study, underwater ambient noise signals were collected from a hydrophone moored 10 m from the sea bed in the coastal sea of western Jeju, South Korea, from mid-September 2019 for 90 days to analyze the variation in the sound of snapping shrimp. The kernel signal and a threshold value were utilized to identify the snapping shrimp, and the snap rate per minute was computed for quantitative analysis. The results show that the mean and standard deviation of the snap rate in the western sea of Jeju was 2132 ± 432 per minute during the whole measurement period. The surface water temperature and tidal level decreased by 7 °C from 25 °C and 50 cm from 190 cm, respectively, over 90 days. The snap rate decreased from September mainly due to the decrease in water temperature by 71 times per minute for every 1 °C decrease. It showed a circadian cycle, increasing by 17~24% at sunrise and sunset compared to the daytime minimum. The snap rate at night was the highest in late summer but the rate dropped like the one during the day in late fall. The snap rate at high tide was 13% higher on average than at low tide. The circadian and tidal changes of the snapping shrimp sound from long-term mooring measurements may be used as primary data for underwater ambient noise and the ecological behavior of snapping shrimp. Full article