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Underwater sound in the oceans has been significantly rising in the past decades due to an increase in human activities, adversely affecting the marine environment. In order to assess and limit the impact of underwater noise, the European Commission’s Marine Strategy Framework Directive (MSFD) included the long-term monitoring of low-frequency underwater sound as a relevant indicator to achieve a good environmental status. There is a wide range of commercial hydrophones and observing platforms able to perform such measurements. However, heterogeneity and lack of standardization in both hydrophones and observing platforms makes the integration and data management tasks time-consuming and error-prone. Moreover, their power and communications constraints need to be addressed to make them suitable for long-term ocean sound monitoring. Measured underwater sound levels are challenging to compare because different measurement methodologies are used, leading to a risk of misunderstandings and data misinterpretation. Furthermore, the exact methodology applied is not always public or accessible, significantly reducing ocean sound data re-usability. Within this work, a universal architecture for ocean sound measurement is presented, addressing hydrophone integration, real-time in situ processing and data management challenges. Emphasis is placed on generic and re-usable components, so it can be seamlessly replicated and deployed in new scenarios regardless of the underlying hardware and software constraints (hydrophone model, observing platform, operating system, etc.). Within the proposed architecture, a generic implementation of an underwater sound algorithm based on underwater noise measurement best practices is provided. Standardized and coherent metadata with emphasis on strong semantics is discussed, providing the building blocks for FAIR (Findable, Accessible, Interoperable, Reusable) ocean sound data management. This work has been funded by the Spanish government project RESBIO (grant agreement TEC2017-87861-R), the EU projects ENVRI-FAIR (grant agreement 824068), the JONAS INTERREG Atlantic Area-funded project (EAPA_52/2018), partly by the Generalitat de Catalunya SARTI-MAR project (grant agreement 2017 SGR 371) and partly by the FPI-UPC_2015 scholarship program.

For weak signal detection with known frequency, based on the double coupling Duffing oscillator method, a differential double coupling Duffing oscillator and Van der Pol-Duffing oscillator detection method is proposed. Its feasibility is verified by sinusoidal analog signal. It has intuitive detection effect and high sensitivity, and can detect weak signal with lower signal-to-noise ratio (SNR). For underwater acoustic weak signal detection with unknown frequency, based on the above proposed method, a differential double coupling Duffing oscillator and Van der Pol-Duffing oscillator variable step-size detection method is proposed. Compared with the existing double coupling Duffing oscillator variable step-size method and differential double Duffing oscillator variable step-size method, its SNR threshold is respectively reduced by 6.02dB and 2.28dB. The lowest average error rate of frequency estimation in multiple sinusoidal analog signal detection under Gaussian white noise, Gaussian color noise and Rayleigh distribution noise is 0.423%. Its detection effect is verified in the detection of measured underwater acoustic signals from the website http://atlanttic.uvigo.es/underwaternoise/ . The results show that it has good detection performance. It provides a new detecting method for underwater acoustic weak signal. In the future, it can be applied to detect weak periodic signal such as square wave and general periodic signal with unknown frequency.

Automatic modulation recognition (AMR) is one of the essential parts in the intelligent communication system. In the underwater acoustic communication, it is a challenging work that promptly and easily recognizes the signal modulation schemes by conventional methods. The deep neural network method is a good solution to the problem, which creates a better recognition effect. The packets of data that are fed to the familiar neural network is constant. However, the packets of signal data on the communication course consistently change, which seriously reflects on the signal recognition veracity. A novel deep learning network with the sequence convolutional network in this paper is proposed, which is composed of one-dimensional sequence convolution of residual network modules and the variable convolution kernel range. By extracting the time-domain signal characteristics, the affection of various signal packets can be mitigated. In experiments, the employed network not only has more concentrated on the modulation recognition veracity, but also owns a lower parameter quantity and a shorter training time, which indicates ideal recognition results in the underwater communication environment. Moreover, it is more valuable to the real underwater communication system.

Contention-basedmedium access control (MAC) protocols for underwater acoustic sensor networks are designed to handle packet collisions that are caused by long propagation delays. However, existing protocols are known to suffer from relatively high collisions, which decrease system performance. To enhance system performance, we propose a contention-based MAC protocol that employs a widely-popular machine learning technique, namely, Q-learning. Using Q-learning, the proposed protocol allows the sensor nodes to intelligently select the back-off slots and accordingly schedule the transmission of data packets such that collisions are minimized at the receiver. Unlike in existing protocols, the sensor nodes are not required to exchange scheduling information, which implies that the proposed protocol has low complexity and overhead. Under varying traffic loads and node numbers, the proposed protocol is compared with the state-of-the-art ALOHA-Q for underwater environment (UW-ALOHA-Q), multiple access collision avoidance for underwater (MACA-U) and exponential increase exponential decrease (EIED) protocols. Results demonstrate the effectiveness of the proposed protocol in terms of energy efficiency, channel utilization, and latency.

This paper describes the design, characterization, and testing of a compact hydrophone capable of measuring acoustic signals from cardiomyocytes. Our hydrophone consists of a nanofabricated photonic-crystal diaphragm externally-mounted to the facet of an optical fiber to form a pressure-sensitive Fabry-Pérot cavity. Our hydrophone can operate in small liquid volumes less than 5 mm deep and incorporates a microchannel to vent air during immersion. The venting channel is designed to optimize bandwidth and sensitivity. Modeling and experimental results in water show a bandwidth from 50 Hz to 18 kHz and a minimum detectable pressure of $3~\mu Pa/ \sqrt {Hz}$ . We demonstrate the sensitivity to simulated bio-acoustic sources with nanometer-scale displacements.

Acquiring channel state information and mitigating multi-path interference are challenging for underwater acoustic communications under time-varying channels. We address the issues using a superimposed training (ST) scheme with a least squares (LS) based channel estimation algorithm. The training sequences with a small power are linearly superimposed with the symbol sequences, and the training signals are transmitted over all time, resulting in enhanced tracking capability to deal with time-varying underwater acoustic channels at the cost of only a small power loss. To realize the full potentials of the ST scheme, we develop a LS based channel estimation algorithm with superimposed training, where the Toeplitz matrix is used, which is formed by the training sequences, enabling channel estimation with superimposed training. In particular, a low-complexity channel equalization algorithm based on generalized approximate messaging passing (GAMP) is proposed, where the a priori, a posteriori, extrinsic means and variances of interleaved coded bits are computed, and then convert them into extrinsic log likelihood ratios for BCJR decoding. Its computational complexity is only in a logarithmic order per symbol. Moreover, the channel estimation, GAMP equalization and decoding are performed jointly in an iterative manner, so that the estimated symbol sequences can also be used as virtual training sequences to improve the channel estimation and tracking performance, thereby remarkably enhance the overall system performance. Moving communication experiments in Jiaozhou Bay (communication frequency 12 kHz, bandwidth 6 kHz, sampling frequency 96 kHz, symbol transmission rate 4 ksym/s) were carried out, and the experimental results verify the effectiveness of the proposed technique.

A novel fully quadrature subcarrier-index shift keying orthogonal frequency division multiplexing (FQSISK-OFDM) modulation scheme for underwater acoustic communications (UWAC) is proposed in this paper. In the FQSISK, the data is conveyed by active and non-active OFDM-subcarriers indices. Moreover, the active odd and even subcarriers are marked with separable predefined dummy variables (DV). Herein, the DV $\pm \delta $ (i.e., it can take any predefined value), and its quadrature $\pm j\delta $ are exploited to distinguish between active even and odd subcarriers. Hence, the possibility of power leakage from active to non-active subcarriers is reduced, which minimizes the effect of severe UWAC inter-carrier-interface (ICI). Moreover, the spectral efficiency of the FQSISK hardly depends on the subcarriers grouping size, which reduces the proposed FQSISK decoder complexity significantly. The simulation results demonstrate the proposed FQSISK superiority, as it achieves higher spectral and energy efficiencies than the plain OFDM and the recently introduced OFDM index modulation (OFDM-IM) techniques.

In this work, we focus on the model-mismatch problem for model-based subspace channel tracking in the correlated underwater acoustic channel. A model based on the underwater acoustic channel's correlation can be used as the state-space model in the Kalman filter to improve the underwater acoustic channel tracking compared that without a model. Even though the data support the assumption that the model is slow-varying and uncorrelated to some degree, to improve the tracking performance further, we can not ignore the model-mismatch problem because most channel models encounter this problem in the underwater acoustic channel. Therefore, in this work, we provide a dynamic time-variant state-space model for underwater acoustic channel tracking. This model is tolerant to the slight correlation after decorrelation. Moreover, a forward-backward Kalman filter is combined to further improve the tracking performance. The performance of our proposed algorithm is demonstrated with the same at-sea data as that used for conventional channel tracking. Compared with the conventional algorithms, the proposed algorithm shows significant improvement, especially in rough sea conditions in which the channels are fast-varying., Comment: Submitted to IEEE Access

Underwater acoustic communication plays an important role in underwater wireless sensor network. Different from terrestrial radio channel, modeling of underwater acoustic channel is very challenging due to its unique and dynamic characteristics. In order to verify the proposed acoustic communication algorithms, a general emulation platform which can reduce the verification cost has a wide application prospect. In this paper, we design a general hardware in the loop underwater communication emulation system based on the LabVIEW and MATLAB software and real acoustic transducer. In the emulation system, LabVIEW calls MATLAB script to achieve algorithm implementation, and then uses DAQmx to send and receive data through the acquisition card. The proposed system supports a variety of modulation and demodulation methods, such as multiple frequency-shift-keying(MFSK), multi-carrier frequency-shift-keying(MCFSK), orthogonal frequency division multiplexing(OFDM), etc. In addition, in order to detect frame efficiently, we propose a light-weight frame synchronous algorithm. To verify the function of the systems, lake test and sea test are conducted for different algorithms.

Underwater wireless communication is a rapidly growing field, especially with the recent emergence of technologies such as autonomous underwater vehicles (AUVs) and remotely operated vehicles (ROVs). To support the high-bandwidth applications using these technologies, underwater optics has attracted significant attention, alongside its complementary technology – underwater acoustics. In this paper, we propose a hybrid opto-acoustic underwater wireless communication model that reduces network power consumption and supports high-data rate underwater applications by selecting appropriate communication links in response to varying traffic loads and dynamic weather conditions. Underwater optics offers high data rates and consumes less power. However, due to the severe absorption of light in the medium, the communication range is short in underwater optics. Conversely, acoustics suffers from low data rate and high power consumption, but provides longer communication ranges. Since most underwater equipment relies on battery power, energy-efficient communication is critical for reliable underwater communications. In this work, we derive analytical models for both underwater acoustics and optics, and calculate the required transmit power for reliable communications in various underwater communication environments. We then formulate an optimization problem that minimizes the network power consumption for carrying data from underwater nodes to surface sinks under varying traffic loads and weather conditions. The proposed optimization model can be solved offline periodically, hence the additional computational complexity to find the optimum solution for larger networks is not a limiting factor for practical applications. Our results indicate that the proposed technique yields up to 35% power savings compared to existing opto-acoustic solutions.

Underwater acoustic target recognition is one of the main functions of the SONAR systems. In this paper, a target recognition method based on combined features with automatic coding and reconstruction is proposed to classify ship radiated noise signals. In the existing underwater acoustic target recognition systems, the target category features are mostly constructed based on the power spectrum according to a certain presupposed model, and some useful information in the data is discarded artificially. In the proposed recognition method, a feature extractor based on auto-encoding is designed. The feature extractor uses the restricted Boltzmann machine (RBM) to automatically encode the combined data of the power spectrum and demodulation spectrum of ship radiated noise without supervision and extracts the deep data structure layer by layer to obtain the signal feature vector. The extracted feature vector is sent to a Back Propagation (BP) neural network to realize target recognition. Due to the high cost of ship radiated noise acquisition, the sample size of ship radiated noise signals is often hard to meet the needs of neural network training. A method of data augmentation is designed by RBM auto-encoder to construct the expanded sample set, which improves the performance of the recognition system. The experimental results based on the actual ship’s radiated noise show that the proposed method has better performance than the traditional methods.

Underwater Wireless Sensor Networks (UWSNs) offer a huge number of applications, most of which require tagging the sensed data with location information. This makes localization algorithms an essential part of UWSN design. This paper presents a comprehensive survey of the recently proposed literature on localization in UWSNs. The surveyed algorithms are evaluated based on a wide-ranging set of parameters which constitute the elementary features of a localization algorithm. Moreover, in order to familiarize the readers with the basic design of the surveyed algorithms, brief description of the mode of operations of each algorithm is presented along with its strengths and weaknesses. The algorithms are divided into two categories based on their computational design i.e., centralized and distributed. Each category is further subdivided into the algorithms that consider node mobility, and those that do not. Towards the end, we present our view on the future research directions in the area of localization in UWSNs.

Using single transponder ranging (STR) information to aid positioning satisfies the needs of frogman autonomous positioning in waters emergency rescue, where miniaturized and low-cost devices are preferred. On this basis, a frogman self-navigation method based on virtual transponder array (VTA) and dead reckoning (DR) is proposed in this article, to solve the problem that calculation results of DR still accumulate with time when STR information is taken as the external measurement. In the proposed method, firstly, by constructing the VTA with depth information constraint, frogman autonomous positioning under the condition of single transponder configuration is realized. Then, to combine the characteristics that DR positioning data is smooth and short-term stable, and that VTA positioning error is not cumulative, the DR navigation system is used to describe frogman’s motion law, the frogman positioning coordinates that calculated by VTA are taken as external measurement and the Kalman filter is designed, which solves the problem of DR accumulated errors. Compared to traditional STR-DR method, the proposed VTA-DR method further improves the accuracy and stability of frogman navigation and positioning. Finally, based on the high-precision three-dimensional motion capture system, the semi-physical simulation experimental environment is built to verify the proposed method. The experimental results under different tracks indicate that the average total location error of VTA-DR method is 0.149m, which is reduced by 53.5% compared with STR-DR method. The proposed VTA-DR method can better suppress the accumulation of positioning errors and has better positioning accuracy and robustness.

Underwater Acoustic Sensor Networks have attracted much attention due to various applications. However, routing voids lead performance degradation of UASNs in terms of network connectivity and packet delivery ratio. In this paper, we propose a Routing Void Prediction and Repairing (RVPR) algorithm in AUV-assisted UASNs, which utilizes AUVs to carry sensor nodes to repair the routing voids when foreseeing the occurrence of voids. First, the repair position is calculated based on Particle Swarm Optimization algorithm by maximizing the connectivity of the void area and minimizing the AUV moving distance. Then, the routing void prediction based on Markov chain model is proposed to ensure that the AUVs come to the repair task before the voids have already formed. Next, we design a task selecting rule to let the AUVs choose the most important and urgent repair task. Lastly, RVPR applies an energy-efficient interaction mechanism among nodes and AUVs, which guarantees reliable operation of the algorithm. In the simulation, the RVPR algorithm is applied in several different types of routing protocols (HHVBF, QELAR, EAVARP). The simulation results show that RVPR algorithm improves the protocol performances in terms of the packet delivery ratio and the link connection. More specifically, when there are 100 nodes deployed in the network, the packet delivery ratio of HHVBF, EAVAPR and QELAR employing RVPR are increased by 29.4%,79% and 65% respectively.

Ensuring low energy consumption is a crucial issue in underwater communications, since battery replacement may be difficult and expensive in these scenarios. We analyze in this paper the energy consumption of a multi-hop underwater acoustic network (UWAN) employing fountain codes. Moreover, in order to reduce this energy consumption we optimize the modulation order assuming differential phase-shift keying ( $M$ -DPSK), as well as the number of hops. We investigate the required number of fountain-encoded packets for different modulation orders. Our results show that, by optimizing the modulation order, the number of hops and the number of fountain packets, we can obtain important energy savings, especially for long distances. In addition, with the proposed scheme the energy consumption decreases significantly compared to the case without fountain codes, reaching up to 40% of savings.

In real ocean environments, artificial acoustic and natural acoustic systems are coexisted to share scarce spectrum resources. In this paper, we propose a marine mammals-friendly based high spectral-efficient routing (MF-HER) protocol to improve spectrum utilization and protect marine mammal communications in underwater acoustic sensor networks (UW-ASNs), which makes full use of the interlacing frequency bands that are shared by both marine mammals and UW-ASNs. In the proposed MF-HER protocol, the detour strategy is adopted to adaptively avoid the interference of acoustic radiation from sensor nodes to the acoustic communication habits of marine mammals. Meanwhile, the non-detour strategy is adopted if there is no marine mammal or the marine mammals do not use the same frequency bands for communication in the sea area, and thus the sensor nodes can fully utilize the frequency bands without interference from the marine mammals. Due to the diversity of acoustic frequency bands used by marine mammals, the reasonable design of a routing protocol can shorten the distance of forwarding path and optimize the performance of UW-ASNs while protecting marine mammals. Simulation results show that, as compared to the existing bio-friendly routing protocol of UW-ASNs, the proposed MF-HER protocol can effectively improve the energy consumption of the sensor nodes, bit error rate, and network throughput, while avoiding the communication masking effect among marine mammals.

With the increasingly fierce competition for marine resources, underwater acoustic communication as the main form of underwater communication, its security has received more and more attention. The traditional underwater acoustic communication technology with fixed frequency and modulation may cause information leakage and location exposure of the communicating platform. The communication based on ocean noise is helpful to improve the communication security. This article proposes a new covert underwater acoustic communication scheme based on ship-radiated noise and chaos signal. Firstly, the characteristics of chaos signal is studied, which is generated by the Chebyshev sequence, and the reconstruction process of ship-radiated noise is analyzed. Secondly, we generate mimic ship-radiated noise containing the secret message based on the time and frequency feature of the chaos signal and ship-radiated noise. Finally, resampling technology is used to equalize the Doppler frequency shift, and time inversion mirror technology is used to perform multipath channel equalization. Simulation and sea experiment verify the effectiveness and feasibility of this scheme. In the sea experiments, the proposed scheme can reliably transimit over 40 per second when the communication distance is about 10km.

In recent years, marine exploration has become one of the most popular research subjects. At present, gliders in Underwater Acoustic Sensor Networks (UASNs) are equipped with a variety of sensors, which can play an important role in marine detection and monitoring. In addition, gliders also have the ability of data collection and storage. When coexisting with the sensor nodes, they can be regarded as special sensor nodes with semi-determined sawtooth trajectories. In hybrid UASNs including sensor nodes and gliders, a robust routing protocol is required to improve the poor network connectivity caused by long transmission delay, high bit error rate and unreliable transmission links. In this article, the Fuzzy Logic Algorithm (FLA) is used to convert multiple input parameters into one output value, thus reducing the storage burden of the network. Therefore, a glider-assist routing scheme with trajectory prediction is proposed to improve the connectivity of the hybrid network. The simulation results show that our scheme is superior to other protocols in terms of delivery ratio, end-to-end latency and lifetime.

To enable full-duplex (FD) operation in underwater acoustic systems, the strong self-interference (SI) from the near-end transmitter should be efficiently cancelled. Digital cancellation is considered as the main approach for the SI cancellation. It is believed that the key challenge in achieving a high level of cancellation is to overcome the nonlinear distortion in the transmit and receive chains. The majority of the nonlinearity is introduced by the power amplifier (PA), which can be dealt with by using the PA output as the reference signal for digital cancellation. Further nonlinearity comes mainly from the hydrophone pre-amplifier. For applications working in half-duplex mode, the pre-amplifier can normally be assumed to be linear due to the low received signal level. For FD operations, the strong SI might result in a nonlinear response of the pre-amplifier, and this nonlinearity should be equalized to achieve a high cancellation performance. In this paper, we propose a technique for equalizing the nonlinearity in the pre-amplifier. This is done using a basis expansion model of the nonlinear equalizer response. More specifically, the Legendre polynomials are used as the basis functions. The expansion coefficients are updated to reduce the mean squared error or a cost function derived based on the power spectrum of the received signal. The performance of the equalizer is evaluated using the experimental data with artificial nonlinear distortion and with real nonlinearity introduced by the hydrophone pre-amplifier. Both sets of results demonstrate that nonlinear distortions can be effectively equalized using the proposed adaptive equalization technique.

The limited energy supply of underwater nodes is one of the key issues for the multi-hop underwater acoustic sensor networks (UWA-SN). In this paper, the fusion scheme based on ant colony optimization algorithm (ACOA), artificial fish swarm algorithm (AFSA) and dynamic coded cooperation (DCC) strategy, named as ACOA-AFSA fusion DCC routing algorithm, has been proposed for routing in the multi-hop UWA-SN, aiming at simultaneously reducing the energy consumption and enhancing the robustness. In the proposed ACOA-AFSA fusion DCC routing algorithm, the randomness of the AFSA and the positive feedback mechanism of the ACOA enable the algorithm to find the global optimal routing more efficient and accurate. In addition, most existing routing protocols consider the large-scale networks (more than 100 nodes), while the medium- and small- scale networks (less than 100 nodes) are more practical in nowadays’ multi-hop UWA-SN. The network scale affects the optimal design of routing protocols in terms of energy saving. Considering the practical situation, we compare the proposed scheme with other four existing artificial intelligence (AI) routing algorithms in the medium- and small- scale multi-hop UWA-SN, which is instructive for application of AI in practical multi-hop UWA-SN. The simulation results show that the proposed ACOA-AFSA fusion DCC routing algorithm can reduce the energy consumption by 40.1% compared to that with non-cooperative strategy in the multi-hop UWA-SN with 20 nodes. The proposed routing algorithm also consumes less energy than other four existing AI routing algorithms in the medium-scale multi-hop UWA-SN with 50 nodes or 100 nodes. However, for the small-scale case with 10 nodes, the advantage is not very obvious. In the meantime, the proposed ACOA-AFSA fusion DCC algorithm is compatible with the ACOA-AFSA fusion non-cooperative algorithm, and the complexity is acceptable, which is very appealing to the time-varying marine environments.

Underwater acoustic networks (UANs) have emerged as a new wireless sensor network structure widely used in many applications. Sensor nodes are usually placed in a hostile and unattended underwater environment to gather information with limited resource. Since the underwater information is sensitive and special, only authenticated users have rights to get the information. The existing secure resource-constrained authentication schemes are not inapplicable for underwater acoustic networks, so a lightweight authentication scheme is the primarily task in underwater acoustic networks. In this paper, we present a chaotic maps remote user authentication and key agreement scheme for underwater acoustic networks based on the DLP and DHP, in which only authenticated users have rights to obtain the information. The proposed scheme applies the lightweight cryptographic primitives, such as one-way hash function and chaotic maps to accomplish mutual authentication and key agreement for underwater acoustic networks. The security of the proposed scheme is certified by applying the BAN logic and Random Oracle Model. Security analysis shows that our proposed scheme is safe and can meet ten security requirements and seven security goals. Performance analysis shows that our proposed scheme is more efficient compared with other resource-constrained schemes.

Orthogonal frequency division multiplexing (OFDM) provides an effective approach to combat multipath with high bandwidth efficiency for underwater acoustic communication, thus design and implementation of acoustic OFDM MODEMs draw more and more attention. Extensive work has been performed to mitigate multipath, Doppler shift, and peak average power ratio from the viewpoint of theoretical analysis. Meanwhile, design and implementation of a parameter-configurable OFDM to adapt to highly diverse underwater channels and various missions become more and more important. Traditional MODEM with fixed parameters cannot achieve the best tradeoff between data rate and bit error rate. In order to obtain the best communication performance under long time delay channels, Doppler channels, and frequency-selective channels, in this paper, we provide the design and implementation of a parameter-configurable underwater acoustic OFDM MODEM with the purpose to achieve flexibility. Specifically, the reconfigurable parameters of the OFDM MODEM include the number of receivers, the number of null subcarriers, the number of pilot subcarriers, as well as the type of channel estimation algorithms. The number of pilot subcarriers and type of channel estimation methods are determined based on channel characteristics, the number of null subcarriers is determined based on the Doppler shift, and the number of the received channels is based on fading channel. Moreover, in this paper, the Doppler estimation performance under different number of null subcarriers, and the channel estimation performance under different number of pilot subcarriers and under different channel estimation algorithms, are analyzed in terms of bit error rate. Finally, the effectiveness of the proposed highly configurable OFDM MODEM is demonstrated by two sea trials corresponding to different communication scenarios.

In this paper, a new cooperative localization (CL) method for multiple autonomous underwater vehicles (AUVs) is proposed to address the problem of measurement outliers and communication packet loss caused by the harsh underwater environment. Combining the advantages of both the maximum correntropy criterion (MCC) and the adaptive neuro-fuzzy inference system (ANFIS), the quality of collected data can be improved by MCC and the ANFIS can be better trained. The efficacy of the proposed method in the CL of AUVs is verified by lake trial. The experimental results show that ANFIS can effectively obtain the location of AUVs based on the input data when the communication packet is lost and the combination of MCC and ANFIS provides better positioning accuracy and robustness. When the probability of measurement outliers is 2%, the proposed method reduces the averaged localization error by 80%, the standard deviation by 84%, and the maximum error difference by 73% compared with the CL method based on cubature Kalman filter(CKF). Finally, the effectiveness of this method is verified by various experiments under different measurement outliers probabilities.

This paper mainly investigates the application of underwater acoustic sensor networks (UASNs), which are characterized by large-scale, sparse distribution, and varying traffic loads. Since the underwater acoustic channel is known for limited bandwidth, time variation, and long propagation delays, the strategy to access the common communication medium is required to improve the performance of UASNs. This paper proposes a delay and queue aware adaptive scheduling-based medium access control (DQA-MAC) protocol for UASNs. It combines adaptive scheduling transmission, reduction of handshaking packets, and concurrent transmission with the propose of improving the performance of network throughput, shortening end-to-end delay, reducing average energy consumption, and enhancing the fairness of transmission. Data transmission time is scheduled based on the information of propagation delays and the number of data packets waiting in each node queue. Furthermore, the strategy of concurrent transmission is implemented to leverage the long propagation delays. At last, reducing the number of handshaking packets is achieved with the approach of exchanging information by specially designed packets frames. The simulation results show that the proposed protocol outperforms the related traditional protocols in networks with varying traffic loads.

Underwater acoustic sensor networks (UASNs) provide new opportunities for exploring oceans and consequently improving our understanding of the underwater world. UASNs usually rely on hardware infrastructure with poor flexibility and versatility. Compared with wireless sensor networks, UASNs are quite expensive to manufacture and deploy. Due to the unique data format, protocols, and service constraints of various applications, UASNs are typically deployed in a redundant manner, which not only leads to waste but also causes serious interference due to the presence of multiple signals in the same underwater region. Software-defined networking (SDN) provides an innovative means of improving the flexibility of underwater systems. In this paper, we present an SDN-based UASN framework, followed by the design of a clustering method in which learning automata and degree-constrained connected dominating sets are employed. We then propose a load balancing mechanism involving multiple controllers, based on the consistent hashing algorithm. Finally, we describe a simulation program (called UASNs hypervisor) that we developed and implemented to assess the network survival time, bit-error rate, and computational complexity. The experimental results show that the UASN was improved significantly. This work provides important theoretical and technical support for the implementation of SDN-based UASNs.

There is an emerging need for high-rate underwater acoustic (UW-A) communication platforms to enable a new generation of underwater monitoring applications including video streaming. At the same time, modern UW-A communication architectures need to be flexible to adapt and optimize their communication parameters in real time based on the environmental conditions. Existing UW-A modems are limited in terms of achievable data rates and ability to adapt the protocol stack in real time. To overcome this limitation, we present the design, implementation, and experimental evaluation of a new high-rate software-defined acoustic modem (SDAM) with real-time adaptation capabilities for UW-A communications. We introduce new physical-layer adaptation mechanisms that enable either joint adaptation of communication parameters such as modulation constellation and channel coding rate or seamless switching between different communication technologies such as orthogonal-frequency-division-multiplexing and direct-sequence-spread-spectrum. The performance of the proposed SDAM has been evaluated in both indoor (water tank) and outdoor (lake) environments. We demonstrated that the SDAM achieves 104 kbit/s with bit-error-rate (BER) of 2 × 10-5, 208 kbit/s with BER of 10-3, and 260 kbit/s with BER of 10-2 in real time over a 200 m horizontal link at a very-shallow lake environment.

Low probability of detection (LPD) is an extremely important characteristic of an underwater acoustic communication (UWAC) system when used for military-related applications, since the detection of a communication signal in the channel may reveal the presence of the transmitter or receiver. Furthermore, the recent advances in the understanding of the environmental effects of sound transmission in the ocean have led to a growing interest in LPD for UWAC also for civilian use. This is because systems that are designed for reliable communication at low signal power have a reduced environmental impact. In this paper, we identify the main challenges for the design of UWAC LPD systems. We describe and classify common approaches for transmission, reception, and interception of LPD signals, and we discuss their advantages and weaknesses. We also present several methods to determine the LPD capability of a system and suggest to adopt the range ratio test as a performance measure that captures the effects of signal propagation through the UWAC channel and the capabilities of the communication receiver and a signal interceptor. In light of the environmental benefits of LPD transmission and ongoing discussions about limiting the power spectral density of UWAC signals through regulations, we believe that LPD transmission is an area of growing importance for UWAC research and development. We hope that this paper serves as a motivation and a starting point for further research in this field.

This paper addresses channel compensation in underwater acoustic communications by proposing a method for inserting physical propagation modeling into a passive time-reversal (PTR) receiver. PTR is known as a low complexity channel equalizer that uses multichannel probing for time signal refocusing, reducing inter-symbol interference caused by multipath propagation. The proposed method aims to improve PTR communications performance by replacing the conventional noisy channel estimates with optimized and noiseless channel replicas computed by a numerical ray trace model. The optimization consists of environmental focalization in an “a priori”physical parameter search space to obtain “a posteriori”channel impulse response replicas that best match the observed data. The results obtained on two data sets acquired during the UAN'11 experiment in a shallow water fjord near Trondheim, in May 2011, show that the proposed method clearly outperformed the traditional PTR by a mean square error gain from 1 up to 4 dB. Channel tracking was effective despite a reduced physical parameter search space that could be exhaustively covered with a minimal computational effort. To the best of our knowledge, this is the first successful report on the usage of a physical parameter fed numerical model for underwater acoustic communications channel equalization with real transmitted data in a useful underwater modem frequency band.

Underwater glider is a cost-effective underwater unmanned vehicle with high endurance for applications in both civilian and military fields. Mobile underwater acoustic sensor networks are consisted of underwater gliders confront with several unique challenges, including high spatial–temporal uncertainty and long propagation delay of acoustic signal. In this paper, we propose an OFDMA-based MAC protocol named G-MAC for an underwater glider network, which leverages dynamic sub-channel allocation and transmission power adjustment. G-MAC is a multichannel MAC protocol dedicated for using in underwater centralized networks, which aims to maximize the network’s goodput. To solve the optimal problem, G-MAC allows for concurrent data transmissions by applying Nash equilibrium to allocate transmission subchannel and related power adjustment. In addition, to reduce the negative impact from spatial uncertainty, a motion prediction method based on the characteristic of underwater glider is applied. Simulation results document that G-MAC outperforms the existing solutions in terms of network goodput and energy consumption in the representative network scenario.

Multi-user cooperative transmission is an attractive architecture for underwater acoustic sensor networks (UASNs). Cooperative transmission depends on careful allocations of resources such as relay selection, but traditional relay selection requires precise measurements of channel state information, which is infeasible for multi-user cooperative transmission due to the unique features and hardware restrictions of UASNs. In this paper, we model multi-user relay selection under a multiuser multi-armed bandit (MU-MAB) framework, whereby users are not provided any prior knowledge about underwater acoustic channel conditions. We first exploit a novel MU-MAB algorithm, DSMU-MAB, for relay selection, assuming that the reward distributions are initially unknown but remain constant. Second, we consider an evolving environment in which the reward distributions undergo changes in time, and DSMU-rMAB, a derivative of DSMU-MAB, is proposed, which can be robust to abrupt changes in underwater communication environments. The proposed algorithms not only help sources find the suitable relays to achieve a high quality transmission and avoid collisions among users but also reduce the mass of information exchanged among users. We established the effectiveness of our proposed algorithms using theoretical and numerical analyses.

We focus on mitigating strong interferences that can jam underwater acoustics emissions aimed for detection or communications. We consider two types of interferences: narrowband like continuous waveform and wideband like chirp. Both the types are assumed to be strong, such that, without interference cancellation, performance is poor. We offer two interference canceling algorithms, each corresponding to a different interference type. The two algorithms are designed to mitigate strong interference, while maintaining the desired signal intact. These algorithms can be executed sequentially to manage both types of interference simultaneously. Our solution takes advantage of the sparsity of the underwater acoustic channel, as well as the assumed correlation of the interference signals. Numerical simulations, as well as results from a sea experiment, show that our algorithms significantly reduce the effect of strong interferences for the fast time-varying and long-delay spread underwater acoustic channel.

A tool to estimate the ray-tracing component of the surveyed depth uncertainty was created and made publicly available through Web services and a Web geographic information system. The estimation is based on a spatial variability analysis at the time of validity of two popular, global-scope sources of oceanographic environmental data. The tool has potential applications in all the phases of ocean mapping, from survey planning to data collection and processing.

The installation error of USBL acoustic transceiver array is one of the important error sources for the SINS/USBL integrated navigation system. The installation error of USBL transceiver array can be divided into coordinate shift error and angle rotation error. The angle rotation error (i.e., installation error angle) has a great influence on the positioning accuracy of USBL. In this paper, the traditional surround sailing method is used to study the relationship between the installation error angle and the USBL positioning accuracy. The influence on USBL positioning is analyzed from the component of heading, pitch, and roll of installation error angle, and the simulation results show that the horizontal positioning errors of USBL are mainly affected by the heading and rolling installation errors. The horizontal positioning error of USBL caused by heading or rolling installation error of 1° will result in 17.45 m, under the circumstance that the depth of transponder is 100 m and the radius of surround sailing is 1000 m, without considering the influence of other positioning errors. 1.75 m horizontal positioning error of USBL caused by pitching positioning error of 1° pitching positioning error and the horizontal positioning error of USBL caused by heading and pitching positioning error is also related to the horizontal distance between the transmitter and transponder. A dynamic calibration algorithm of installation error angle based on incremental iteration is proposed in this paper, which could realize the dynamic on-line estimation of installation error angle of USBL transceiver array. The installation error angle increment module can accurately estimate the installation angle error by iterating more than 10 times. In the case of ignoring the other error terms, the horizontal positioning error caused by the installation error angle can be reduced from 8 to 2 m in the positioning range of 1000 m.

Prefixes, in forms of cyclic-prefixes or zero-padding, have often been viewed as indispensable in underwater acoustic single-carrier transmissions to avoid inter-block interference (IBI) and to formulate circular convolution. However, the prefix introduces overhead and reduces spectral efficiency. This is especially true in fast time-varying channel conditions. Here, we propose a prefix-free scheme to facilitate frequency-domain equalization (FDE) in an underwater acoustic communication system, based on the time-reversal processing. In the proposed scheme, three main procedures, block partitioning, IBI cancellation, and prefix reconstruction, precede the FDE operation. The block partitioning at the receiver provides flexibility to support channel equalization in different channel fluctuation rates. The utilized prefix reconstruction scheme requires a strong first arrival to minimize the noise enhancement. Our solution is to use the time-reversal processing, because the resultant equivalent impulse response, also known as the $q$ -function, has a stable and compact peak. To further enhance receiver performance, we incorporate two strategies. One is overlapping partitioning. The other is iterative prefix reconstruction. The proposed schemes have been tested using the field measurements obtained from the Gulf of Mexico in August 2016. Communications over four ranges at the carrier frequency of 85 kHz with a symbol rate of 17 kHz have been demonstrated. The overlapping partitioning and iterative prefix reconstruction strategies have been shown to generate improvements in the receiver performance.

In this paper, a transmission redundancy optimization strategy for fountain codes that uses an adaptive filtering technique as well as recent results concerning the upper bound of the source packet erasure probability for fountain codes over finite fields is proposed. The performance of the proposed strategy was evaluated in static and simulated realistic underwater acoustic channel environments simulated by a recently proposed statistical underwater acoustic channel model. The goal of this investigation is to improve the communication efficiency of underwater acoustic sensor networks that use communication protocols based on fountain codes. The performance of the proposed strategy is compared with the recently proposed approaches of discrete stochastic approximation (DSA) and the joint power and rate control (JPR) schemes. The simulation results demonstrate that the strategy proposed in this paper performs better than the existing schemes in both static and simulated realistic environments. The proposed strategy is 4.75 times better than the DSA in the static convergence performance evaluation. Further analysis shows that in the presence of a simulated realistic environment, compared to DSA and JPR, the strategy proposed in this paper reduces the overall transmission redundancy by approximately 11.4% and 52.6%, respectively. It also improves the average communication efficiency by 1.3% and 12.5%, respectively. The average optimization error relative to optimal redundancy is improved by approximately 62.1% and 92.5%, respectively. These numerical results are obtained by employing the specific simulation parameters and the simulated environment mentioned in this paper.

Localization plays a more and more important role in underwater wireless sensor networks (UWSNs). But in the large-scale UWSNs, the localization algorithm can’t be realized for the continuous packet collision. Therefore, we need to consider the impact of MAC protocol on the positioning algorithm. First, this paper proposes a multi-layer positioning model based on the underwater network architecture. Then according to the non-synchronous localization scheme, we analyze the reason of packet collisions and propose the variable interval ALOHA (VI-ALOHA) protocol based on the Poisson distribution. The VI-ALOHA protocol reduces the collision by adding random space–time. Through the comparison of localization coverage, packet loss, and localization time, this paper evaluates the impact on the localization result in equal interval ALOHA (EI-ALOHA) and VI-ALOHA. Our simulation results show that the MAC protocol has a significant influence on localization; besides, the localization coverage and the packet loss of VI-ALOHA protocol are above 20% better than the EI-ALOHA.