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Locating an underwater sensor node over the seabed and acquiring fast, secure data communication between the node and an underwater vehicle could lead to advancements in underwater exploration and marine technology. Currently, the seabed is extensively mapped using multibeam sonar modules, providing detailed information about the bed. Because of its high computational requirements and cost, multibeam sonar is not suitable for this application. The aim of this article is to deploy an experimental setup with a single-beam sonar to localize the node, and then, establish a communication link. The single beam sonar has a 30° beamwidth, which can be improvised to have a full range scan using a custom pan-tilt mechanism setup. To accomplish the full-scale area mapping, underwater servo motors have been used in our customized pan-tilt mechanism. Once the localization is done using a custom pan-tilt mechanism, a line-of-sight optical wireless communication is established with a 200 kbps data rate. The channel is modeled based on the test pool experiments. The channel model is used to simulate underwater optical wireless communication (UOWC) to a longer link length and higher data rate. An underwater link length of 3.13 m was achieved at 1 W and 1 Gbps data rate with a Q factor of 6 and BER of 10−9. For this test setup and simulation parameters, various parameters such as BER and quality factor are examined. [ABSTRACT FROM AUTHOR]

Underwater acoustic vector sensors (UAVSs) are increasingly utilized for remote passive sonar detection, but the accuracy of direction-of-arrival (DOA) estimation remains a challenging problem, particularly under low signal-to-noise ratio (SNR) conditions and complex background noise. In this paper, a comprehensive theoretical analysis is conducted on UAVS signal preprocessing subjected to gain-phase uncertainties for average acoustic intensity measurement (AAIM) and complex acoustic intensity measurement (CAIM)-based vector DOA estimation, aiming to explain the theoretical restrictions of intensity-based vector acoustic preprocessing approaches. On this basis, a generalized vector acoustic preprocessing optimization model is established in which the principle can be described as "maximizing the denoising performance under the constraints of an equivalent amplitude-gain response and phase-bias response". A novel vector acoustic preprocessing method named linear matched stochastic resonance (LMSR) is proposed within the framework of matched stochastic resonance theory, which can naturally guarantee the linear gain-phase restrictions, as well achieving effective denoising performance. Numerical analyses demonstrate the superior vector DOA estimation performance of our proposed LMSR-AAIM and LMSR-CAIM methods in comparison to classical intensity-based AAIM and CAIM methods, especially under low-SNR conditions and non-Gaussian impulsive noise circumstances. Experimental verification conducted in the South China Sea further verifies its the effectiveness for practical application. This work can lay a solid foundation to break through the challenges of underwater remote vector acoustic DOA estimation under low-SNR conditions and complex ocean ambient noise and can provide important guidance for future research work. [ABSTRACT FROM AUTHOR]

Side scan sonar images have great application prospects in underwater surveys, target detection, and engineering activities. However, the acquired sonar images exhibit low illumination, scattered noise, distorted outlines, and unclear edge textures due to the complicated undersea environment and intrinsic device flaws. Hence, this paper proposes a multi-scale fusion strategy for side scan sonar (SSS) image correction to improve the low contrast and noise interference. Initially, an SSS image was decomposed into low and high frequency sub-bands via the non-subsampled shearlet transform (NSST). Then, modified multi-scale retinex (MMSR) was employed to enhance the contrast of the low frequency sub-band. Next, sparse dictionary learning (SDL) was utilized to eliminate high frequency noise. Finally, the process of NSST reconstruction was completed by fusing the emerging low and high frequency sub-band images to generate a new sonar image. The experimental results demonstrate that the target features, underwater terrain, and edge contours could be clearly displayed in the image corrected by the multi-scale fusion strategy when compared to eight correction techniques: BPDHE, MSRCR, NPE, ALTM, LIME, FE, WT, and TVRLRA. Effective control was achieved over the speckle noise of the sonar image. Furthermore, the AG, STD, and E values illustrated the delicacy and contrast of the corrected images processed by the proposed strategy. The PSNR value revealed that the proposed strategy outperformed the advanced TVRLRA technology in terms of filtering performance by at least 8.8%. It can provide sonar imagery that is appropriate for various circumstances. [ABSTRACT FROM AUTHOR]

Accurate bearing‐time recordings play a crucial role in hydroacoustic target motion analysis and situation estimation. The target bearing estimated by vector hydrophone in the interference environment suffers from poor display and low signal‐to‐noise ratio. To solve this problem, a two‐stage bearing‐only motion analysis method is proposed. Firstly, the bearing peak information and bearing dispersion are extracted for each sampling moment of the bearing‐time recording. Custom constraint regions and adaptive parameters are then set based on this information. The order truncate average algorithm is improved to enhance the quality of the low‐quality bearing‐time recording map. Secondly, a bearing‐only target motion model is established based on the bearing‐time recording distribution features, and a bearing‐time recording trust interval is constructed. Then a modified pseudo‐linear estimation algorithm is proposed to solve the target motion situation information, including target abeam time, target abeam bearing, target course, velocity‐to‐initial‐distance ratio, and so forth. Finally, by comparing the solved values of the sea trial data with the automatic identification system calculation results, the enhancement effect of the target bearing‐time recording map is significant and the solving error of the target motion elements meets the needs of engineering applications. [ABSTRACT FROM AUTHOR]

In environments with a low signal-to-reverberation ratio (SRR) characterized by fluctuations in clutter number and distribution, particle filter-based tracking methods may experience significant fluctuations in the posterior probability of existence. This can lead to interruptions or even loss of the target trajectory. To address this issue, an adaptive PF-based tracking method (APF) with joint reverberation suppression is proposed. This method establishes the state space model under the Bayesian framework and implements it through particle filtering. To keep the weak target echoes, all the non-zero entries contained in the sparse matrix processed by the low-rank and sparsity decomposition (LRSD) are treated as the measurements. The prominent feature of this approach is introducing an adaptive measurement likelihood ratio (AMLR) into the posterior update step, which solves the problem of unstable tracking due to the strong fluctuation in the number of point measurements per frame. The proposed method is verified by four shallow water experimental datasets obtained by an active sonar with a uniform horizontal linear array. The results demonstrate that the tracking frame success ratio of the proposed method improved by over 14% compared with the conventional PF tracking method. [ABSTRACT FROM AUTHOR]

In cluttered electromagnetic environments, radar is often disturbed by varied clutter, making target detection challenging. Therefore, achieving effective clutter suppression is crucial for radar target detection. However, traditional clutter suppression methods face three key challenges: (1) significant degradation in target signal detection performance when the clutter's Doppler spectrum completely masks the target signal; (2) heavy reliance on prior knowledge for optimal performance; and (3) inherent signal energy loss during clutter suppression. To address these challenges, we propose a clutter suppression scheme based on blind source separation (BSS). Initially, the scheme utilizes parallel principal skewness analysis (PPSA) to process the echo signals in the range domain, which helps in identifying the position of moving targets. Subsequently, PPSA is applied once more to process the moving targets in the Doppler domain, allowing for the precise determination of their relative velocities. Subsequently, we evaluate the scheme's performance with simulated and real data, comparing it with traditional clutter suppression methods and other BSS techniques. The results confirm the effectiveness of the scheme in clutter suppression. [ABSTRACT FROM AUTHOR]

Remote passive sonar detection with low-frequency band spectral lines has attracted much attention, while complex low-frequency non-Gaussian impulsive noisy environments would strongly affect the detection performance. This is a challenging problem in weak signal detection, especially for the high false alarm rate caused by heavy-tailed impulsive noise. In this paper, a novel matched stochastic resonance (MSR)-based weak signal detection model is established, and two MSR-based detectors named MSR-PED and MSR-PSNR are proposed based on a theoretical analysis of the MSR output response. Comprehensive detection performance analyses in both Gasussian and non-Gaussian impulsive noise conditions are presented, which revealed the superior performance of our proposed detector under non-Gasussian impulsive noise. Numerical analysis and application verification have revealed the superior detection performance with the proposed MSR-PSNR detector compared with energy-based detection methods, which can break through the high false alarm rate problem caused by heavy-tailed impulsive noise. For a typical non-Gasussian impulsive noise assumption with α = 1.5 , the proposed MSR-PED and MSR-PSNR can achieve approximately 16 dB and 22 dB improvements, respectively, in the detection performance compared to the classical PED method. For stronger, non-Gaussian impulsive noise conditions corresponding to α = 1 , the improvement in detection performance can be more significant. Our proposed MSR-PSNR methods can overcome the challenging problem of a high false alarm rate caused by heavy-tailed impulsive noise. This work can lay a solid foundation for breaking through the challenges of underwater passive sonar detection under non-Gaussian impulsive background noise, and can provide important guidance for future research work. [ABSTRACT FROM AUTHOR]

The underwater domain is a challenging environment for robotics because widely used electromagnetic devices must be substituted by acoustic equivalents, much slower and noisier. In this paper a two‐dimensional pose simultaneous localization and mapping (SLAM) system for an Autonomous Underwater Vehicle based on inertial sensors and a mechanical profiling sonar is presented. Two main systems are specially designed. On the one hand, a dead reckoning system based on Lie Theory is presented to track integrated pose uncertainty. On the other hand, a rigid scan matching technique specialized for acoustic data is proposed, which allows one to estimate the uncertainty of the matching result. Moreover, Bayesian–Gaussian mixtures models are introduced to the scan matching problem and the registration problem is solved by an optimization in Lie groups. The SLAM system is tested on real data and executed in real time with the robotic application. Using this system, section maps at constant depth can be obtained from a three‐dimensional underwater domain. The presented SLAM system constitutes the first achievement towards an underwater Active SLAM application. [ABSTRACT FROM AUTHOR]

Underwater image recognition is crucial for underwater detection applications. Fish classification has been one of the emerging research areas in recent years. Existing image classification models usually classify data collected from terrestrial environments. However, existing image classification models trained with terrestrial data are unsuitable for underwater images, as identifying underwater data is challenging due to their incomplete and noisy features. To address this, we propose a cross-modal augmentation via fusion (CMAF) framework for acoustic-based fish image classification. Our approach involves separating the process into two branches: visual modality and sonar signal modality, where the latter provides a complementary character feature. We augment the visual modality, design an attention-based fusion module, and adopt a masking-based training strategy with a mask-based focal loss to improve the learning of local features and address the class imbalance problem. Our proposed method outperforms the state-of-the-art methods. Our source code is available at https://github.com/WilkinsYang/CMAF. [ABSTRACT FROM AUTHOR]

Oceanic delphinids that occur in and around Navy operational areas are regularly exposed to intense military sonar broadcast within the frequency range of their hearing. However, empirically measuring the impact of sonar on the behavior of highly social, free-ranging dolphins is challenging. Additionally, baseline variability or the frequency of vocal state-switching among social oceanic dolphins during undisturbed conditions is lacking, making it difficult to attribute changes in vocal behavior to anthropogenic disturbance. Using a network of drifting acoustic buoys in controlled exposure experiments, we investigated the effects of mid-frequency (3–4 kHz) active sonar (MFAS) on whistle production in short-beaked (Delphinus delphis delphis) and long-beaked common dolphins (Delphinus delphis bairdii) in southern California. Given the complexity of acoustic behavior exhibited by these group-living animals, we conducted our response analysis over varying temporal windows (10 min– 5 s) to describe both longer-term and instantaneous changes in sound production. We found that common dolphins exhibited acute and pronounced changes in whistle rate in the 5 s following exposure to simulated Navy MFAS. This response was sustained throughout sequential MFAS exposures within experiments simulating operational conditions, suggesting that dolphins may not habituate to this disturbance. These results indicate that common dolphins exhibit brief yet clearly detectable acoustic responses to MFAS. They also highlight how variable temporal analysis windows–tuned to key aspects of baseline vocal behavior as well as experimental parameters related to MFAS exposure–enable the detection of behavioral responses. We suggest future work with oceanic delphinids explore baseline vocal rates a-priori and use information on the rate of change in vocal behavior to inform the analysis time window over which behavioral responses are measured. [ABSTRACT FROM AUTHOR]

This paper describes an attempt to use data obtained from sodar (sound detection and ranging) for short-term forecasting of PM 10 concentration levels in Krakow. Krakow is one of the most polluted cities in central Europe (CE) in terms of PM 10 concentration. This is due to the high municipal emissions. Thanks to intensive corrective actions taken by the city authorities, these are being effectively eliminated, but the unfavourable topographic location of the city limits natural ventilation. The article describes all these conditions, focusing on presenting the method of short-term correction of air quality for the time needed to take quick corrective actions by the city authorities in the event of anticipated exceedances of the permissible values. Based on several years of measurements of the physical properties of the atmosphere with sodar, the authors of the paper suggest that sodar data could be considered for operational use to generate short-term predictions. The proposed method is based on the use of the spectrum, i.e. the set of amplitudes of signals returning to the sodar receiver from the reflection of a single-frequency sound transmission and its characteristic properties depending on the physical state of the atmosphere. Similar spectra were parameterised with a single numerical value using statistical methods. It was found that, in some cases preceding high concentrations of PM 10 , the spectral parameters had similar values. This made it possible to develop a forecasting method for such concentrations by using data mining to search for conditions in historical data closest to the state of the atmosphere at the time of forecasting. In this part of the study, data from 2017–2018 were used. In the next step, three methods of using the sodar data developed for PM 10 prediction were proposed, comparing them with the method without sodar use. The study results were tested on independent material using data concerning the episodes of high concentrations of pollutants from October 2021 to March 2022 in Krakow. The findings were considered to be encouraging, also taking into account the speed and low cost of preparing the forecast. [ABSTRACT FROM AUTHOR]

Wideband direction-of-arrival (DOA) estimation is an important task for passive sonar signal processing. Nowadays, sparse Bayesian learning (SBL) attracts much attention due to its good performance. However, performance degrades in the existence of strong interference. This problem can be solved by combining the beamformer and the SBL. The beamformer is a useful tool to suppress interference. Then, the SBL can easily estimate the DOA of the targets from the beamformer power outputs (BPO). Unfortunately, the latter step needs to compute the matrix inversion frequently, which brings some computational burden to the sonar system. In this paper, the BPO-based SBL is modified. A sequential solution is provided for the parameters in the BPO probabilistic model. In this manner, only one signal precision parameter involved in the probabilistic model is updated in each iteration and the matrix inversion is avoided during the iteration, thus reducing the computational burden. Simulation and experimental results show that the proposed method maintains high estimation precision in the interference environment. At the same time, its computational efficiency is almost three times higher in comparison with state-of-the-art methods. [ABSTRACT FROM AUTHOR]

During sonar detection, the fuzzy function of hyperbolic frequency modulation (HFM) in the waveform of active signal is in the shape of a "oblique blade," which leads to the coupling characteristics of its fuzzy function in the time dimension and frequency dimension. Doppler causes a frequency shift in the frequency dimension and a time delay in the time dimension, which makes it impossible for a single HFM signal to measure speed accurately. However, the time delay caused by the same moving target to HFM signals with different frequency bands and different pulse widths is also different. A velocity measurement method combining HFM signals (VCH) is proposed, which employs the time delay correlation between the combined HFM signals to achieve the target distance and speed. In the VCH method, the echo signal is no longer matched and filtered as a whole but is divided into two channels and matched and filtered separately. And then, the combined HFM signals are used to obtain the distance and speed of the target. Extensive simulation results show that the proposed method can estimate the distance and speed of moving targets accurately, and it has reference value for engineering application. [ABSTRACT FROM AUTHOR]

Humans robustly associate spiky shapes to words like "Kiki" and round shapes to words like "Bouba." According to a popular explanation, this is because the mouth assumes an angular shape while speaking "Kiki" and a rounded shape for "Bouba." Alternatively, this effect could reflect more general associations between shape and sound that are not specific to mouth shape or articulatory properties of speech. These possibilities can be distinguished using unpronounceable sounds: The mouth-shape hypothesis predicts no Bouba-Kiki effect for these sounds, whereas the generic shape-sound hypothesis predicts a systematic effect. Here, we show that the Bouba–Kiki effect is present for a variety of unpronounceable sounds ranging from reversed words and real object sounds (n = 45 participants) and even pure tones (n = 28). The effect was strongly correlated with the mean frequency of a sound across both spoken and reversed words. The effect was not systematically predicted by subjective ratings of pronounceability or with mouth aspect ratios measured from video. Thus, the Bouba–Kiki effect is explained using simple shape-sound associations rather than using speech properties. [ABSTRACT FROM AUTHOR]

In this paper, we propose the zero-correlation-zone (ZCZ) of radius r on two-dimensional m × n sonar sequences and define the (m , n , r) ZCZ sonar sequences. We also define some new optimality of an (m , n , r) ZCZ sonar sequence which has the largest r for given m and n. Because of the ZCZ for perfect autocorrelation, we are able to relax the distinct difference property of the conventional sonar sequences, and hence, the autocorrelation of ZCZ sonar sequences outside ZCZ may not be upper bounded by 1. We may sometimes require such an ideal autocorrelation outside ZCZ, and we define ZCZ-DD sonar sequences, indicating that it has an additional distinct difference (DD) property. We first derive an upper bound on the ZCZ radius r in terms of m and n ≥ m . We next propose some constructions for (m , n , r) ZCZ sonar sequences, which leads to some very good constructive lower bound on r. Furthermore, this construction suggests that for m and r, the parameter n can be as large as possible indefinitely. We present some exhaustive search results on the existence of (m , n , r) ZCZ sonar sequences for some small values of r. For ZCZ-DD sonar sequences, we prove that some variations of Costas arrays construct some ZCZ-DD sonar sequences with ZCZ radius r = 2 . We also provide some exhaustive search results on the existence of (m , n , r) ZCZ-DD sonar sequences. Lots of open problems are listed at the end. [ABSTRACT FROM AUTHOR]

The Yangtze finless porpoise (Neophocaena asiaeorientalis asiaeorientalis, YFP) possesses the ability to detect distance through echolocation signals, and its sonar signal signature is adjusted to detect different targets. In order to understand the vocal characteristics of YFPs in different behavioral states and their differential performance, we recorded the vocal activities of YFPs in captivity during free-swimming, feeding, and nighttime resting and quantified their signal characteristic parameters for statistical analysis and comparison. The results showed that the number of vocalizations of the YFPs in the daytime free-swimming state was lower than that in the feeding and nighttime resting states, and the echolocation signals emitted in these three states showed significant differences in the −10 dB duration, −3 dB bandwidth, −10 dB bandwidth, and root-mean-square (RMS) bandwidth. Analysis of the resolution of the echolocation signals of the YFPs using the ambiguity function indicated that their distance resolution could reach the millimeter level. These results indicate that the echolocation signal characteristics of YFPs present diurnal differences and that they can be adjusted with changes in their detection targets. The results of this study can provide certain scientific references and foundations for the studies of tooth whale behavioral acoustics, and provide relevant scientific guidance for the conservation and management of YFPs. [ABSTRACT FROM AUTHOR]

Although research has been conducted on the simultaneous operation of multiple autonomous underwater vehicles (AUVs) to improve the efficiency of oceanographic surveys, it has become clear that sonar interference occurs between AUVs that are in close proximity. In this study, a formation control system was developed for actual operation at sea, based on the assumption of an operational system with an autonomous surface vehicle (ASV) and multiple AUVs. A control algorithm was implemented to maintain the AUVs within the desired range of the ASV, ensure communication, and avoid sonar interference by sending commands to increase or decrease the speed of the AUVs. Simulations were performed to verify the effectiveness of the developed method for the operation of one ASV and 10 AUVs. Evaluation scores for the distance between vehicles were introduced to quantify the effectiveness of the algorithm. The proposed method obtained the highest scores for formation control in the assumed operational scenarios. This confirms the effectiveness of the proposed method in avoiding the side-by-side relationships that cause sonar interference. [ABSTRACT FROM AUTHOR]

In recent years, there has been a trend toward expanding the operating frequency range and increasing the output power of Sound Navigation and Ranging (SONAR) systems to enhance their acoustic detection capabilities. However, due to this increase in operational power, the electrical capacity of amplifiers for SONAR system operation also increases, necessitating High-Power Amplifiers. When configured with a single amplifier, as in conventional methods, the volume of amplifiers increases due to volumetric increases in heat dissipation, components, and windings. These issues are detrimental to SONAR amplifier installation, mobility, maintenance, and equipment lifespan due to stress on individual components. Additionally, amplifiers for SONAR systems are comprised of power conversion devices, transformers for LC filters and matching, necessitating consideration of LC filters and matching transformers for enhancing voltage quality and efficiency to improve amplifier performance transmitted to SONAR transducers. However, previous research has focused on single-amplifier design methods, neglecting such considerations. Therefore, this paper proposes a design technique that overcomes the drawbacks of using the conventional design method by configuring multiple H-bridge inverters in a cascade format and utilizes one of the optimization algorithms, Particle Swarm Optimization (PSO), to derive amplifier design techniques that optimize component parameters for enhancing high-capacity amplifier performance. Subsequently, theoretical analysis, simulations, and experimental results comparing the proposed high-power amplifier design method with conventional single-amplifier design methods demonstrate similar error rates in operational frequency bands. [ABSTRACT FROM AUTHOR]

The Paddlefish (Polyodon spathula) has been extirpated from portions of its native range due to anthropogenic habitat degradation and fragmentation, most notably the impoundment of rivers. To mitigate some of these losses in Oklahoma, Paddlefish have been stocked into reservoirs throughout the state, with variable success in establishing self‐sustaining populations. Two factors thought to contribute to success of Paddlefish stocking are spawning substrate and prey availability, which were quantified in six reservoirs and nine reservoir tributaries. Side‐scan sonar and supervised classification of aerial imagery were used to classify 4517‐ha of river substrate upstream of the river‐reservoir interface in reservoir tributaries. Zooplankton community structure, water clarity, and nutrient availability were also assessed in the same reservoirs and tributaries. One tributary had suitable spawning substrate (>40%), and the rest had minimal (<1.5%), which suggested that availability of suitable spawning substrate was not directly correlated with Paddlefish stocking success. Reservoirs with self‐sustaining Paddlefish populations had higher abundance of large zooplankton (copepods and cladocerans) than reservoirs without a reproducing population. Notably, tributaries associated with Lake Texoma, the one known example of failed restoration, were much more turbid than other rivers. We conclude that abiotic factors such as water clarity may contribute more to variable recruitment than spawning substrate or zooplankton abundance by mediating foraging success of Paddlefish post‐larvae. [ABSTRACT FROM AUTHOR]

To make an Autonomous Underwater Vehicle (AUV) chase a moving target ship that generates wake, wake-responsive guidance can be used. This scenario is applicable to making an underwater torpedo pursue a moving target ship until hitting the target. The objective of our research is to make an AUV pursue a target ship assisted by passive sonar sensors as well as wake sensors. To track a maneuvering target without losing the target, the AUV applies both passive sonar sensors and two wake sensors. Two wake sensors are utilized to decide the turn direction of the AUV in zig-zag maneuvers. In practice, sharp maneuvers of the target can cause the AUV to exit the target's wake abruptly. As the target ship's wake is not detected by wake sensors and the AUV needs to search for the target ship, the AUV's passive sonar measures the direction of sound generated from the target ship. Thereafter, the AUV chases the target ship until the target's wake is detected again. As far as we know, our paper is novel in addressing wake-responsive AUV guidance assisted by passive sonar sensors. The effectiveness of the proposed guidance is verified using computer simulations. [ABSTRACT FROM AUTHOR]

For health and impact studies of water systems, monitoring underwater environments is essential, for which multi-frequency single- and multibeam echosounders are commonly used state-of-the-art technologies. However, the current scarcity of sediment reference datasets of both bottom backscatter angular response and water column scattering hampers empirical data interpretation. Comprehensive reference data derived from measurements in a controlled environment should optimize the use of empirical backscatter data. To prepare for such innovative experiments, we conducted a feasibility experiment in the Delta Flume (Deltares, The Netherlands). Several configurations of sonar data were recorded of the flume floor and suspended sediment plumes. The results revealed that flume reverberation was sufficiently low and that the differential settling of fine-sand plumes in the water column was clearly detected. Following this successful feasibility test, future comprehensive experiments will feature multi-frequency multi-angle measurements on a variety of sediment types, additional scatterers and sediment plumes, resulting in reference datasets for an improved interpretation of underwater backscatter measurements for scientific observation and sustainable management. [ABSTRACT FROM AUTHOR]

Echolocation is the prime sensing modality for many species of bats, who show the intricate ability to perform a plethora of tasks in complex and unstructured environments. Understanding this exceptional feat of sensorimotor interaction is a key aspect into building more robust and performant man-made sonar sensors. In order to better understand the underlying perception mechanisms it is important to get a good insight into the nature of the reflected signals that the bat perceives. While ensonification experiments are an important way to better understand the nature of these signals, they are as time-consuming to perform as they are informative. In this paper we present SonoTraceLab, an open-source software package for simulating both technical as well as biological sonar systems in complex scenes. Using simulation approaches can drastically increase insights into the nature of biological echolocation systems, while reducing the time- and material complexity of performing them.

Coprime and nested sparse arrays are two widely researched sparse arrays. These arrays, requiring fewer sensors compared to full uniform linear arrays (ULAs), still have a high number of degrees of freedom. The reduced sensor count in sparse arrays contributes to cost and system complexity reduction, and it also lessens the computational burden. This study delves into the computational efficiency aspect of sparse arrays, conducting a comparative analysis of coprime and nested arrays in classifying underwater stationary and moving sources using real sonar data. Leveraging two machine learning-based classification algorithms—support vector machine (SVM) and convolutional neural network (CNN)—the study aims to assess the extent of computational time savings achievable with sparse arrays and the associated trade-offs in accuracy. Simulation results reveal that both coprime and nested arrays can achieve near 100% classification accuracy for SVM and CNN models when an appropriate number of snapshots is selected for data processing. Additionally, within a suitable range of number of snapshots, computational time can be significantly reduced compared to full ULA, with only a minimal compromise in accuracy (< 2%). The study underscores the effectiveness of machine learning-based classifiers in source identification using sonar data, highlighting their high accuracy. However, it also notes that while a more powerful algorithm enhances operational capacity, it may concurrently escalate the complexity of the algorithm.

Airborne 3D imaging using ultrasound is a promising sensing modality for robotic applications in harsh environments. Over the last decade, several high-performance systems have been proposed in the literature. Most of these sensors use a reduced aperture microphone array, leading to artifacts in the resulting acoustic images. This paper presents a novel in-air ultrasound sensor that incorporates 1024 microphones, in a 32-by-32 uniform rectangular array, in combination with a distributed embedded hardware design to perform the data acquisition. Using a broadband Minimum Variance Distortionless Response (MVDR) beamformer with Forward-Backward Spatial Smoothing (FB-SS), the sensor is able to create both 2D and 3D ultrasound images of the full-frontal hemisphere with high angular accuracy with up to 70 $\mathrm { \text {dB}}$ main lobe to side lobe ratioin the array response in a single-source scenario. This paper describes both the hardware infrastructure needed to obtain such highly detailed acoustical images, as well as the signal processing chain needed to convert the raw acoustic data into said images. Utilizing this novel high-resolution ultrasound imaging sensor, we wish to investigate the limits of both passive and active airborne ultrasound sensing by utilizing this virtually artifact-free imaging modality.

Fish stock assessment is crucial for sustainable marine fisheries management in rangeland ecosystems. To address the challenges posed by the overfishing of offshore fish species and facilitate comprehensive deep-sea resource evaluation, this paper introduces an improved fish sonar image detection algorithm based on the you only look once algorithm, version 5 (YOLOv5). Sonar image noise often results in blurred targets and indistinct features, thereby reducing the precision of object detection. Thus, a C3N module is incorporated into the neck component, where depth-separable convolution and an inverse bottleneck layer structure are integrated to lessen feature information loss during downsampling and forward propagation. Furthermore, lowercase shallow feature layer is introduced in the network prediction layer to enhance feature extraction for pixels larger than $ 4 \times 4 $. Additionally, normalized weighted distance based on a Gaussian distribution is combined with Intersection over Union (IoU) during gradient descent to improve small target detection and mitigate the IoU's scale sensitivity. Finally, traditional non-maximum suppression (NMS) is replaced with soft-NMS, reducing missed detections due to occlusion and overlapping fish targets that are common in sonar datasets. Experiments show that the improved model surpasses the original model and YOLOv3 with gains in precision, recall and mean average precision of 2.3%, 4.7% and 2.7%, respectively, and 2.5%, 6.3% and 6.7%, respectively. These findings confirm the method's effectiveness in raising sonar image detection accuracy, which is consistent with model comparisons. Given Unmanned Underwater Vehicle advancements, this method holds the potential to support fish culture decision-making and facilitate fish stock resource assessment.

The ability to identify asymptotic scattering is critical for the continuous operation of modern combat systems. In the active sonar equation, acoustic target strength is crucial. The plane-wave propagation target strength equation predicts far-field reradiated intensity. Submarines defend themselves by being invisible. Sonar can be used to detect submarines. Saltwater readily absorbs radio waves. Commercial fishing and scientific ocean exploration both make use of sonar technology. Acoustic wave reflection reduces the area requirements of ocean depth sections, therefore submarine designers take this into consideration. The Target Strength (TS) of a sonar target is used to assess its size. The Pressure Acoustic-Boundary Element Model (PA-BEM) of the High-Frequency Boundary Model (HFB) illuminates and simplifies the TS analysis of the Benchmark Target Echo Strength Simulation (BeTTSi) benchmark submarine. We explore how subsea shape, material qualities, and operation frequency affect acoustic target strength using comprehensive models. The findings underline the need of correctly characterising the structural sections of the submarine and their impact on dispersion. They also help with research into the submarine’s acoustic signature, detectability, and potential detection mitigation measures.

In this study, the mechanisms of jet atomization were analyzed based on a frequency analysis of atomization sounds in the audible range (∼20 kHz). Jet atomization is a two-dimensional, high-speed atomization using a diaphragm, and interesting acoustic signals and atomization phenomena were detected on hydrophobic and hydrophilic diaphragms. The hydrophilic diaphragm strongly interacted and resonated with the surface wave, resulting in symmetrical jet atomization relative to the diaphragm. The resonance between the diaphragm and the surface wave was supported by a calculation of the eigenfrequency of the diaphragm and the coincidence of the droplet diameters as calculated from Lang's equation. Notably, the diaphragm excited by the ultrasonic transducer acted as a new transducer vibrating perpendicular to the transducer. As a result, when the diaphragm and the surface wave were in resonance at 2.4 MHz, a symmetrical two-dimensional high-speed jet atomization was generated in the direction perpendicular to the transducer's vibration direction. This study also revealed that the atomization state can be determined based on the acoustic analysis. This acoustic analysis of atomization sounds can be applied in more advanced atomization control, such as for providing uniform dispersions of droplets containing DNA, drugs, or microplastics. [ABSTRACT FROM AUTHOR]

In ocean observation missions, unmanned autonomous ocean observation platforms play a crucial role, with precise target detection technology serving as a key support for the autonomous operation of unmanned platforms. Among various underwater sensing devices, side-scan sonar (SSS) has become a primary tool for wide-area underwater detection due to its extensive detection range. However, current research on target detection with SSS primarily focuses on large targets such as sunken ships and aircraft, lacking investigations into small targets. In this study, we collected data on underwater small targets using an unmanned boat equipped with SSS and proposed an enhancement method based on the YOLOv7 model for detecting small targets in SSS images. First, to obtain more accurate initial anchor boxes, we replaced the original k-means algorithm with the k-means++ algorithm. Next, we replaced ordinary convolution blocks in the backbone network with Omni-dimensional Dynamic Convolution (ODConv) to enhance the feature extraction capability for small targets. Subsequently, we inserted a Global Attention Mechanism (GAM) into the neck network to focus on global information and extract target features, effectively addressing the issue of sparse target features in SSS images. Finally, we mitigated the harmful gradients produced by low-quality annotated data by adopting Wise-IoU (WIoU) to improve the detection accuracy of small targets in SSS images. Through validation on the test set, the proposed method showed a significant improvement compared to the original YOLOv7, with increases of 5.05% and 2.51% in mAP@0.5 and mAP@0.5: 0.95 indicators, respectively. The proposed method demonstrated excellent performance in detecting small targets in SSS images and can be applied to the detection of underwater mines and small equipment, providing effective support for underwater small target detection tasks. [ABSTRACT FROM AUTHOR]

In recent years, there has been growing interest in autonomous mobile robots equipped with Simultaneous Localization and Mapping (SLAM) technology as a solution to labour shortages in production and distribution settings. SLAM allows these robots to create maps of their environment using devices such as Lidar, radar, and sonar sensors, enabling them to navigate and track routes without prior knowledge of the environment. However, the manual operation of these robots for map construction can be labour-intensive. To address this issue, this research aims to develop a 3D SLAM autonomous mobile robot system that eliminates the need for manual map construction by utilizing existing layout maps. The system includes a PC for self-position estimation, 3DLidar, a camera for verification, a touch panel display, and the mobile robot itself. The proposed SLAM method extracts stable wall point cloud information from 3DLidar, matches it with the wall surface information in the layout map, and uses a particle filter to estimate the robot's position. The system also includes features such as route creation, tracking, and obstacle detection for autonomous movement. Experiments were conducted to compare the proposed system with conventional 3D SLAM methods. The results showed that the proposed system significantly reduced errors in self-positioning and enabled accurate autonomous movement on specified routes, even in the presence of slight differences in layout maps and obstacles. Ultimately, this research demonstrates the effectiveness of a system that can transport goods without the need for manual environment mapping, addressing labour shortages in such environments. [ABSTRACT FROM AUTHOR]

That Loch Ness Monsters, "Nessies", might exist has been argued by many people on the basis of films, sonar contacts, photos, and eyewitness accounts. At the same time, some observers have insisted that these are not real creatures, nothing but misperceptions of natural phenomena or known animals. Their arguments typically address the weakest evidence (eyewitness accounts) rather than the strongest objective evidence of sonar and film. Such evasion or avoidance constitutes a strategy of misdirection, as does the insistence that, since Nessies are not recognized by "science," therefore taking their possible existence seriously amounts to doing pseudo-science. Debunkers are arguably irrational and go beyond the evidence in declaring that Nessies are definitely non-existent. Although Nessie fans do believe that they exist, most will admit that final proof requires a specimen or detailed close-up of unequivocally valid photography and insist only that enough evidence exists to warrant further searches: that is not pseudo-science. [ABSTRACT FROM AUTHOR]

Synthetic Aperture Ladar (SAL) is a sensor that combines laser detection technology with synthetic aperture technology to achieve ultra-high-resolution imaging. Due to its extremely short wavelength, SAL is more sensitive to motion errors. The micrometer-level motion will affect the target's azimuth focus. This article proposes an SAL motion compensation method based on Symmetric Triangular Linear Frequency Modulation Continuous Wave (STLFMCW) segmented interference, utilizing the characteristics of a triangular wave, to solve the problem of target azimuth defocusing. This article first establishes an STLFMCW echo signal model based on the SAL system under the influence of motion errors. Secondly, the radial velocity gradient along the azimuth direction is extracted using the triangular-wave-positive and -negative frequency modulation signals segmented interference method. Then, for the initial phase wrapping problem, the frequency spectral cross-correlation method is used to accurately estimate the initial radial velocity error. The radial velocity gradient is integrated along the azimuth to obtain the platform motion trajectory. Finally, the compensation functions are constructed to complete the echo Range Cell Migration (RCM) correction and residual phase compensation, resulting in a focused SAL image. This article verifies the practical effect of this method in eliminating motion errors using only one-period STLFMCW signal through simulation and real experiments. The quantitative results show that compared with the traditional method, the proposed method reduces the azimuth Peak Sidelobe Ratio (PSLR) by 8dB and the Integrated Sidelobe Ratio (ISLR) by 9 dB. This method has significant improvements and is of great significance for high-resolution FMCW SAL imaging. [ABSTRACT FROM AUTHOR]

Rice cultivation on southern plantation landscapes was a mainstay and major cash crop along the southeast coastal region of the United States in the eighteenth and nineteenth centuries. The workforce involved in growing rice was primarily enslaved Africans and freed African Americans of the Gullah Geechee culture, whose ancestors were forcibly brought over from West Africa, often due to their superior knowledge of rice cultivation. Today, in the tidal regions of major rivers from Florida to North Carolina, the vestiges of complex canal and waterway systems engineered for rice cultivation are still evident today. Within these systems, there are various wood-built, water-control structures in the form of structural dike supports, floodgates and sluices, levee repairs, bulkheads and boat landings. In this study, a combination of visual observations using non-motorized vessels, combined with a customized side scan sonar system designed specifically for shallow water surveys, was used to identify and map dozens of artifacts within the shallow canal and waterway systems of Eagles Island, North Carolina, where there is historical evidence of significant rice growing in the region. The study focused on the northern third of the island, where rice fields are essentially intact, and was designated Eagles Island Rice District. The results of the 2-year study identified 45 rice-related archaeological structures being discovered, in addition to a nineteenth century watercraft. The novel and effective survey techniques employed in this study can be adopted elsewhere within the southeastern United States to locate, map and preserve the knowledge and engineering expertise of the Gullah Geechee, upon whom the region's economic success depended. [ABSTRACT FROM AUTHOR]

Purpose: The low-frequency noise radiated by ships has a significant impact on marine animals; however, traditional ship sound-absorbing materials are not optimal for low-frequency noise control. Therefore, an acoustic metasurface suitable for low-frequency noise control is devised using a spatial folding structure, which is composed of folded channels and perforated structural units. Methods: Numerical methods are used to investigate the acoustic characteristics and absorption mechanism of the metasurface, and the impact of common structural factors on the acoustic performance of the metasurface is studied. An experimental model is produced with 3D printing technology, and the structure's absorption coefficient is examined. Results: A composite acoustic metasurface is designed by coupling multiple cells, and the designed metasurface structure achieves continuous broadband sound absorption in the range of 125–200 Hz. The structure exhibits subwavelength absorption characteristics and has an average absorption coefficient of 0.886 in the target frequency range, with a thickness of 1/27 of the wavelength. Conclusion: Folded channels extend the propagation path of acoustic waves, lead to lower absorption frequencies, and the coupled multicell design broadens the absorption bandwidth. The proposed coupled multicell folded low-frequency acoustic metasurface structure has excellent sound absorption performance and provides new ideas for the design of marine low-frequency broadband acoustic absorbers. [ABSTRACT FROM AUTHOR]

By using sound to visualize the real-world environment, audio games can offer a completely new game experience. In this paper, we study how audio cues can be visualized in audio games and their effects on the players' navigation skills, gaming experience, and immersion. Also, factors that impact the system performance in terms of navigation using audio components. To this end, we propose an audio game in which blindfolded players move through a physical maze with the help of audio cues. To realize this game, a sonar headset is designed and built based on ultrasonic sensors, which maps the external environment features into musical sounds. Actually, the design of the sonar headset is the result of design and research efforts. The gaming environment of this game is a physical maze, where the blindfolded players enter the maze while wearing the sonar headset. A user study was conducted to evaluate the effect of using different sound mapping techniques on navigation performance and playing experience in the game proposed in this paper. The results show that producing musical sound can lead to better navigation performance, game experience, and immersion in players. [ABSTRACT FROM AUTHOR]

The scarcity and difficulty in acquiring Side-scan sonar target images limit the application of deep learning algorithms in Side-scan sonar target detection. At present, there are few amplification methods for Side-scan sonar images, and the amplification image quality is not ideal, which is not suitable for the characteristics of Side-scan sonar images. Addressing the current shortage of sample augmentation methods for Side-scan sonar, this paper proposes a method for augmenting single underwater target images using the CBL-sinGAN network. Firstly, considering the low resolution and monochromatic nature of Side-scan sonar images while balancing training efficiency and image diversity, a sinGAN network is introduced and designed as an eight-layer pyramid structure. Secondly, the Convolutional Block Attention Module (CBAM) is integrated into the network generator to enhance target learning in images while reducing information diffusion. Finally, an L1 loss function is introduced in the network discriminator to ensure training stability and improve the realism of generated images. Experimental results show that the accuracy of shipwreck target detection increased by 4.9% after training with the Side-scan sonar sample dataset augmented by the proposed network. This method effectively retains the style of the images while achieving diversity augmentation of small-sample underwater target images, providing a new approach to improving the construction of underwater target detection models. [ABSTRACT FROM AUTHOR]

An Autonomous Underwater Helicopter (AUH) is a disk-shaped, multi-propelled Autonomous Underwater Vehicle (AUV), which is intended to work autonomously in underwater environments. The near-bottom area sweep in unknown environments is a typical application scenario, in which the complete coverage path planning (CCPP) is essential for AUH. A complete coverage path planning approach for AUH with a single beam echo sounder, including the initial path planning and online local collision avoidance strategy, is proposed. First, the initial path is planned using boustrophedon motion. Based on its mobility, a multi-dimensional obstacle sensing method is designed with a single beam range sonar mounted on the AUH. The VFH+ algorithm is configured for the heading decision-making procedure before encountering obstacles, based on their range information at a fixed position. The online local obstacle avoidance procedure is simulated and analyzed with variations of the desired heading direction and corresponding polar histograms. Finally, several simulation cases are set up, simulated and compared by analyzing the heading decision in front of different obstacle situations. The simulation results demonstrate the feasibility of the complete coverage path planning approach proposed, which proves that AUH completing a full coverage area sweep in unknown environments with a single beam sonar is viable. [ABSTRACT FROM AUTHOR]

This paper investigates the terrain-following problem for an autonomous underwater vehicle (AUV) from control perspectives with full consideration of terrain characteristics. By equipping the AUV with three simple single-beam echo sounders, a set of precise along-track bottom slopes are obtained in a real-time manner, and the occurrence of the lost bottom lock phenomenon caused by a single sonar altimeter is eliminated. A slope-based data processing method is developed, which enables an AUV to characterize seafloor features with complementary sensing modalities to generate proper adaptive height-modified values. In order to keep a fixed height when maneuvering over rugged terrains, a back-stepping depth control is implemented by adjusting horizontal rudder angle, and Lyapunov theory is adopted to analyze the asymptotic stability of the resulting terrain-following control system. At last, simulation results indicate the feasibility and effectiveness of the proposed methodology with a discussion of various sensor configurations. [ABSTRACT FROM AUTHOR]

In response to the demand for efficient and high-precision detection in marine capture fishery, here the omnidirectional fishery sonar was developed to detect the targets in long distance using digital broadband and multiple beams. Broadband technology was used to effectively suppress the interference of interface and volume reverberation. Multiple beams were to improve the resolution of target detection. A distributed architecture of signal processing was also constructed for the omnidirectional fishery sonar using a field programmable gate array (FPGA). The omnidirectional fishery sonar was divided into multiple sectors. The underwater acoustics was simulated to determine the mutual constraints between the three main influencing parameters, namely the size of the transducer array, the maximum distance of detection, and the optimal point of operating frequency. The key parameters were then selected for the fishery sonar, according to the typical fishery vessels in China. The preferred frequency band of the signal was 20-30 kHz. A systematic investigation was also conducted on the effects of noise, interface reverberation, and volume reverberation on the detection performance of omnidirectional fishery sonar. A parallel and serial broadband beamforming FPGA was utilized to reduce the on-chip storage by 90% during operation; the Delta Sigma module was adopted to improve the signal-to-noise ratio of the transmission signal, where the noise within 20-30 kHz shifted to the frequency band above 50 kHz. A one-step stability of the predictive beam was improved using two-point recursive interpolation. The real-time stability errors of the beam were achieved at less than 1.6° (-0.8°-+0.8°) under significant sway of fishing vessels. The core components were also developed, such as a cylindrical transducer array, a highly integrated receiver and transmitter, and a 256 multi-channel signal processor, and system integration. 256 channels were independent receiving and transmitting for the signals in the 20-30 kHz frequency band. The scanning detection capabilities were for horizontal 360° and vertical 70°. The omnidirectional multi-beam fishery sonar was installed on the deep-sea fishery vessel. Environmental and simulated target detection tests were carried out on the fish school. The sea test results showed that the omnidirectional fishery sonar better performed stable, clear and continuous detection of environmental targets, where the detection ability of the 0 dB fish target reached more than 1 500 m. The key indicators of the self-developed omnidirectional sonar can fully meet the needs of marine fishing scenarios. The finding can greatly improve the detection performance of fishing for large-scale autonomous production. [ABSTRACT FROM AUTHOR]

Differences between conventional sonar and Multiple-Input Multiple-Output (MIMO) sonar systems arise in achieving high angular and range resolution. MIMO sonar uses Matched Filtering (MF) with well-correlated transmitted signals to enhance spatial resolution by obtaining virtual arrays. However, imperfect correlation characteristics yield high sidelobe values, which hinder accurate target localization in underwater imagery. To address this, a Compressed Sensing (CS) method is proposed by reconstructing echo signals to suppress correlation noise between orthogonal waveforms. A shifted dictionary matrix and a deterministic Discrete Fourier Transform (DFT) measurement matrix are used to multiply received echo signals to yield compressed measurements. A sparse recovery algorithm is applied to optimize signal reconstruction before joint transmit–receive beamforming forms a 2D sonar image in the angle-range domain. Numerical simulations and lake experimental results confirm the effectiveness of the proposed method, by obtaining a lower sidelobe sonar image under sub-Nyquist sampling rates as compared with other approaches. [ABSTRACT FROM AUTHOR]

Average empirical estimations of the surface air layer height in Moscow have been received by the data of long-term acoustic remote sensing of the atmosphere using the MODOS Doppler sodar (METEK, Germany). Based on the assumption that the average conditions are close to neutral stratification, this height, as the top of the quasi-linear section of the average long-term wind velocity profile in semilogarithmic coordinates, is 40–60 m. The wind rotation height, i.e., the height of intersection of day and night wind profiles, is 95 m per year on average. The roughness length in conditions of loosely packed but high urban development in the vicinity of Moscow State University in Moscow is 5 m. According to the criterion of the constant wind direction in the surface air layer, its height manifests itself in the monthly average wind direction profiles over the "dead zone" of the sodar (40 m) in approximately one out of three cases and usually amounts to 60 m (less often 80 or 100 m). In all other cases, it is apparently masked by the dead zone. According to this approach, the average height of the surface layer is probably a little less than 50 m, which is close to the estimate obtained from the logarithmic distribution of wind velocity with height in this layer. The daily variation of the surface air layer height is noted by the largest values in the afternoon (80–100 m in summer under conditions of prevailing unstable stratification and 60–80 m in winter) and the smallest ones (less than 40 m) in the late evening and at night in summer and from evening to noon in winter. [ABSTRACT FROM AUTHOR]

Sonar systems are frequently used to classify objects at a distance by using the structure of the echoes of acoustic waves as a proxy for the object's shape and composition. Traditional synthetic aperture processing is highly effective in solving classification problems when the conditions are favourable but relies on accurate knowledge of the sensor's trajectory relative to the object being measured. This article provides several new theoretical tools that decouple object classification performance from trajectory estimation in synthetic aperture sonar processing. The key insight is that decoupling the trajectory from classification-relevant information involves factoring a function into the composition of two functions. The article presents several new general topological invariants for smooth functions based on their factorisations over function composition. These invariants specialise to the case when a sonar platform trajectory is deformed by a non-small perturbation. The mathematical results exhibited in this article apply well beyond sonar classification problems. This article is written in a way that supports full mathematical generality. [ABSTRACT FROM AUTHOR]

The frequency–azimuth (FRAZ) spectrum is a critical characteristic in passive target detection and tracking, as it encapsulates information regarding the signal's frequency and azimuth. However, due to the inherent limitations in the sonar array's physical aperture and the analysis time of the system, the signal often suffers from undersampling in both spatial and temporal dimensions. This undersampling leads to energy leakage across the azimuth and frequency domains, adversely affecting the resolution of the FRAZ spectrum. Such a reduction in resolution hampers multitarget resolution and feature extraction. To address these challenges, this study introduces a deconvolution-based FRAZ spectrum estimation method tailored for uniform linear arrays. The proposed method initiates by decoupling the azimuth and frequency in the FRAZ spectrum, forming a two-dimensional point scattering function that possesses shift-invariance. Subsequent to this, the power spectrum and the two-dimensional point scattering function undergo deconvolution using the Richardson–Lucy (R–L) iterative algorithm. The final stage involves calculating the signal azimuths and frequencies based on the deconvolution results from the preceding step. Comparative analyses involving simulations and sea test results reveal that the proposed method achieves a narrower main lobe width and diminished background noise in contrast to traditional FRAZ spectrum estimation techniques. This improvement is instrumental in minimizing the target's energy leakage in both the azimuth and frequency domains. [ABSTRACT FROM AUTHOR]

The Mechanoelectrical transduction (MET) channels of the mammalian hair cells are essential for converting sound stimuli into electrical signals that enable hearing. However, the impact of acoustic overstimulation, a leading cause of hearing loss, on the MET channel function remains poorly understood. In this study, I investigated the effect of loud sound-induced temporary threshold shift (TTS) on the transduction response phase across a wide range of sound frequencies and amplitudes. The results demonstrated an increase in the transduction response phase following TTS, indicating altered transduction apparatus function. Further investigations involving the reduction of extracellular calcium, a known consequence of TTS, replicated the observed phase changes. Additionally, reduction of potassium entry confirmed the specific role of calcium in regulating the transduction response phase. These findings provide novel insights into the impact of loud sound exposure on hearing impairment at the transduction apparatus level and highlight the critical role of calcium in modulating sound transduction. Considering that over 1 billion teenagers and young adults globally are at risk of hearing loss due to unsafe music listening habits, these results could significantly enhance awareness about the damaging effects of loud sound exposure. [ABSTRACT FROM AUTHOR]

We show that Traveling Ionospheric Disturbances (TIDs) may affect the Farley Buneman Instability (FBI) and Gradient Drift Instability (GDI) echoes referred to as the Near Range Echoes (NREs) in the SuperDARN radar backscatter from the lower part of the E‐region. TIDs and NREs are observed concomitantly by the Zhongshan SuperDARN radar (69.38°S, 76.38°E) in the far and near ranges, respectively. At the moment, there is no study about the effects of TIDs on the NREs caused by the FBI using the SuperDARN radars. The GDI are more likely to occur at a lower altitude while FBI occurs at a slightly higher altitude in the lower part of the ionospheric E‐region. We use the Spearman Correlation Coefficient (SCC) to show that a part of the NREs backscatter power could be statistically explained by the MSTIDs backscatter power received by the same radar. We also investigate the simultaneous occurrence rate of the NREs and MSTIDs during the 24th solar cycle. Seasonal variability shows that MSTIDs‐NREs events over Zhongshan mostly occur in summer and equinoxes during local night and morning. The majority of these events lasted between ∼4 and ∼8 hr. Most events disappeared early in the morning. Statistics of the Spearman correlation coefficient values show that ∼9% of NRE amplitude modulation could be due to the MSTIDs. There are almost equal numbers of negative and positive Spearman correlation coefficient values. The relative velocity between the E‐region NREs and the F‐region MSTIDs switching the electric field polarities between the crests and troughs could be the cause of those equal number of the Spearman correlation coefficient values. The orientation of the ionospheric current relative to the MSTID polarization electric field may also play a significant role in the reported Spearman correlation coefficient values. We argue that in some cases, the TIDs might have been close enough to the NREs altitude to modulate them directly by transporting the plasma up and down through shear or compression. Plain Language Summary: SuperDARN radar Near Range Echoes (NREs) were observed at an altitude range of 95–125 km and are caused by the Gradient Drift Instability (GDI) and Farley Buneman Instability (FBI). Medium Scale Traveling Ionospheric Disturbances (MSTIDs) are wave‐like perturbations of plasma density that propagate in the ionosphere. They are caused by any major ionospheric energy input such as the Atmospheric Gravity Waves (AGWs), Joule heating, Perkins instability, and so on. It was argued that the MSTIDs partially modulate the NREs backscatter power associated with the GDI through the polarization electric field. We use the Zhongshan SuperDARN radar to show that apart from GDI, FBI related echoes are also partially modulated by the MSTIDs. We also record the number of MSTID‐NRE events during 2010–2019 and found that the majority of them occurs in summer and equinoxes during local night and morning while the minority occurred in the winter of the southern hemisphere. We also perform a statistical study of the Spearman correlation coefficient values of all events recorded for this study. Key Points: First demonstration of TIDs partially modulating Farley Buneman (FB) and Gradient Drift (GD) wavesFarley Buneman and Gradient Drift Instabilities generate NREsSpearman rank correlation analysis shows that statistically ∼9% of NRE amplitude modulation could be due to the MSTIDs [ABSTRACT FROM AUTHOR]

Offshore reefs in the Laurentian Great Lakes provide critical spawning habitats for native lake trout. Though many historic spawning reefs have been documented, thorough evaluation of the habitat they contain is rare. After decades of stocking, natural recruitment of lake trout has increased dramatically in the Illinois waters of Lake Michigan since 2010, reinforcing the need for information about the viability and distribution of spawning habitats.Using side‐scan sonar and underwater video, this study sought to map bottom substrates at Lake Bluff Reef and Gumby's Reef, offshore of the northern Illinois coast of Lake Michigan, to describe and quantify the availability of substrates suitable for lake trout spawning. Substrates were manually delineated in ArcGIS using side‐scan sonar imagery mosaics. Underwater video was used to verify substrate classifications through direct observation.Suitable spawning substrate consisting of fractured bedrock debris and piled boulder/cobble was observed at both reefs. Underwater video revealed the presence of lake trout at both reefs in the weeks leading up to the spawning season. The largest congregation of fish was observed in the vicinity of the shallowest points, steep slopes, and the largest patches of spawning substrate.The distribution, amount, and condition of spawning substrate available at each reef was in line with others studied in the region and their likely importance for lake trout spawning was reinforced by observed aggregations of mature fish.This study has expanded the inventory of well‐documented offshore reefs in the Illinois waters of Lake Michigan, enhancing appreciation of what is coming to be understood as the Illinois Reef Complex. Knowledge of the distribution and status of habitats critical to the life history of native fishes in the Great Lakes are necessary for managers to properly assess, manage, and conserve lake trout and other fish populations. [ABSTRACT FROM AUTHOR]

Marine communication has attracted widespread attention in the wake of global warming and national defense awareness in recent years, where acoustic systems enabling smooth underwater communication have become a popular research topic. In this study, we proposed an underwater communication system equipped with modulators and demodulators (modems). Specifically, the wireless communication software GNU’s Not Unix Radio (GNU Radio) was adopted to develop communication formats and architectures applied to a Raspberry Pi computer, on which we developed a communication format available for signal synchronization to increase system robustness against underwater channel interferences. We also developed hardware and software modems for the system. The hardware device was developed using the XR2206 function generator and XR2211 equipment for frequency-shift keying (FSK)-based modulation and demodulation, respectively. The software FSK modem was developed using GNU Radio. To increase the robustness of the transmitted data, we added a cyclic redundancy check through the Async CRC32 block, after which the power distribution unit (PDU) to the Tagged Stream block placed a tag to the start of data combined with effective loads and CRC32, facilitating the attachment of header generators. Four experiments with different underwater scenarios were then conducted to verify the proposed system. The hardware modem had a 0 bit error rate (BER) during experiments implemented in a laboratory sink, a 20-m-long indoor swimming pool, and a 50-m-long outdoor swimming pool, compared with BERs of 2.8 × 10−3 and 6.6 × 10−3 during the breeding water tank experiment under transmission rates of 1 and 2 kbps, respectively. Similarly, the software modem delivered 0-BER performance in the laboratory sink as well as in the indoor and outdoor swimming pools, with its BERs being 2.3 × 10−4 and 2.98 × 10−4 under 1 and 2 kbps transmission rates, respectively. The proposed system comprises preambles, headers, and effective load communication formats for signal protection. In particular, its directional ultrasonic cylindrical piezoelectric transducer can mitigate multipath effects and interferences, thereby enhancing system robustness. [ABSTRACT FROM AUTHOR]

The regularization method has a direct impact on the accuracy of the reconstructed sound field in the process of inverse calculation of near−field acoustic holography using the equivalent source method. To expand the frequency range of sound field reconstruction and improve computational accuracy, a forward-backward splitting equivalent source method based on s−difference was proposed, which uses the ratio of the output results of the broadband acoustic holography algorithm as the regularization parameter. Numerical simulations of single source and coherent source sound fields were conducted under different frequency conditions to analyze the performance of the forward-backward splitting regularization algorithm based on s−difference, and experimental verification was performed. The simulation results show that the proposed method can accurately reconstruct the sound field in a wider frequency range, and has high accuracy in reconstructing the sound field of low−frequency coherent sources. The experimental results demonstrate the accuracy and effectiveness of this method in reconstructing mid−to−low−frequency sound fields. [ABSTRACT FROM AUTHOR]

Currently, the phenomenon of ocean desertification, known as rocky shore denudation, is occurring all over the world. One of the causes is the feeding damage by sea urchins on seaweed beds called seagrass beds. To restore the seaweed beds, it is necessary to exterminate the proliferating sea urchins. We have developed an automated survey system that provides information on sea urchin habitat distribution and seafloor topography to streamline the extermination process. Based on a small surfboard-based ASV developed in our laboratory, an underwater camera and sonar are attached to the ASV (autonomous surface vehicle), which navigates automatically to collect data. By analyzing the obtained data, we were able to obtain the habitat distribution of sea urchins and a topographic map of the seafloor, which are necessary for sea urchin extermination. [ABSTRACT FROM AUTHOR]