No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
A Survey of Techniques and Challenges in Underwater Localization
Abstract
Underwater Wireless Sensor Networks (UWSNs) are expected to support a variety of civilian and military applications. Sensed data can only be interpreted meaningfully when referenced to the location of the sensor, making localization an important problem. While global positioning system (GPS) receivers are commonly used in terrestrial WSNs to achieve this, this is infeasible in UWSNs as GPS signals do not propagate through water. Acoustic communications is the most promising mode of communication underwater. However, underwater acoustic channels are characterized by harsh physical layer conditions with low bandwidth, high propagation delay and high bit error rate. Moreover, the variable speed of sound and the non-negligible node mobility due to water currents pose a unique set of challenges for localization in UWSNs. In this paper, we provide a survey of techniques and challenges in localization specifically for UWSNs. We categorize them into (i) range-based vs. range-free techniques; (ii) techniques that rely on static reference nodes vs. those who also rely on mobile reference nodes, and (iii) single-stage vs. multi-stage schemes. We compare the schemes in terms of localization speed, accuracy, coverage and communication costs. Finally, we provide an outlook on the challenges that should be, but have yet been, addressed.
... Underwater localization is one of the most essential techniques for building marine positioning, navigation and timing (PNT) systems, and could be widely used for disaster warning, underwater rescue and resource exploring. Compared with radio or optical signal, acoustic wave has become the most popular signal carrier in underwater localization [1]. However, unlike terrestrial radio, the acoustic localization faces many challenges due to the special underwater environment, such as the difficulty in clock synchronization [1,2], the multipath effect [3], insufficient reference nodes [3] and the stratification effect [4,5]. ...
... Compared with radio or optical signal, acoustic wave has become the most popular signal carrier in underwater localization [1]. However, unlike terrestrial radio, the acoustic localization faces many challenges due to the special underwater environment, such as the difficulty in clock synchronization [1,2], the multipath effect [3], insufficient reference nodes [3] and the stratification effect [4,5]. ...
... Comprehensive surveys of challenges and techniques in localization have been carried out in [1][2][3][4]. Because of the features of underwater acoustic channels, high-precision positioning faces challenges mentioned above. ...
Underwater localization is one of the key techniques for positioning, navigation, timing (PNT) services that could be widely applied in disaster warning, underwater rescues and resource exploration. One of the reasons why it is difficult to achieve accurate positioning for underwater targets is due to the influence of uneven distribution of underwater sound velocity. The current sound-line correction positioning method mainly aims at scenarios with known target depth. However, for nodes that are non-cooperative nodes or lack depth information, sound-line tracking strategies cannot work well due to non-unique positional solutions. To solve this problem, we propose an iterative ray tracing 3D underwater localization (IRTUL) method for stratification compensation. To demonstrate the feasibility of fast stratification compensation, we first derive the signal path as a function of initial |grazing angle, and then prove that the signal propagation time and horizontal propagation distance are monotonic functions of the initial grazing angle, which guarantees the fast achievement of ray tracing. Simulation results indicate that IRTUL has the most significant correction effect in the depth direction, and the average accuracy has been improved by about 3 m compared to a localization model with constant sound velocity.
... In addition to traditional optimization techniques, advanced optimization methodologies such as robust optimization and stochastic optimization address uncertainty and variability inherent in multi-stage manufacturing systems. These methodologies develop robust and adaptive strategies that perform well under a wide range of operating conditions and disturbances [14]. ...
Hate speech detection and mitigation have become critical challenges in the digital age, given the proliferation of online platforms where such harmful content can spread rapidly and have real-world consequences. In this paper, we propose a transformative solution leveraging deep learning techniques for hate speech detection and mitigation. Our approach involves the development of advanced deep learning models trained on large-scale datasets annotated for hate speech. These models utilize state-of-the-art natural language processing techniques to analyze text data and accurately identify instances of hate speech with high precision and recall. Additionally, we incorporate techniques for contextual understanding, enabling our models to discern nuanced forms of hate speech that may evade traditional detection methods. Furthermore, we present a mitigation framework that not only identifies hate speech but also provides strategies for addressing it effectively. This includes mechanisms for content moderation, user education, and community engagement aimed at fostering a more inclusive and respectful online environment. Our results demonstrate significant improvements in hate speech detection performance compared to existing methods, highlighting the potential of deep learning for addressing this pervasive societal issue.
... Received Signal Strength-This method measures the intensity of the received acoustic signal and compares it with the signal attenuation model in a given medium. This is difficult to achieve due to multipath and shadow fading [61]. However, compared to Time of Arrival, it does not require time synchronization, and is not affected by the clock skew and clock offset [62]. ...
This study is a survey of sound source localization and detection methods. The study provides a detailed classification of the methods used in the fields of science mentioned above. It classifies sound source localization systems based on criteria found in the literature. Moreover, an analysis of classic methods based on the propagation model and methods based on machine learning and deep learning techniques has been carried out. Attention has been paid to providing the most detailed information on the possibility of using physical phenomena, mathematical relationships, and artificial intelligence to determine sound source localization. Additionally, the article underscores the significance of these methods within both military and civil contexts. The study culminates with a discussion of forthcoming trends in the realms of acoustic detection and localization. The primary objective of this research is to serve as a valuable resource for selecting the most suitable approach within this domain.
... In 1991, James proposed a buoy-based long baseline positioning system in [2], which extended the concept of global positioning system (GPS) to underwater systems for the first time. Unlike terrestrial radio, underwater localization faces with many challenges due to the special underwater environment, such as the difficulty in clock synchronization caused by long signal propagation delay [3,4], the multipath effect caused by signal reflection at the ocean surface or bottom [5], insufficient reference nodes due to limited communication coverage of nodes [4,5], and the signal propagation path bending, which is called stratification effect, caused by the spatio-temporal variety of sound velocity [6,7]. ...
Seafloor geodetic network (SGN) is the foundation for building an underwater positioning, navigation and timing (PNT) system. Traditional network deployment mainly focuses on the deployment of underwater sensor network nodes. However, for SGN, there is no surface buoy node and submarine buoy node, and the number of anchors is limited because it is quite expensive to fully cover large scale areas. To achieve wide coverage and good positioning service of each set of underwater base stations, we focus on the network design of a single set of reference stations in this paper. We propose several deployment plans for a local SGN and then analyze their service quality indicators by considering the stratification effect caused by non-uniformly distributed sound speed. To evaluate the performance of each topology of SGN, we compare their coverage range, horizontal dilution precision (HDOP) and accuracy performance of positioning tests. Based on the overall performance in our simulation, we believe that the star five-node topology is a good topology design under sufficient economic conditions.
... Autonomous underwater vehicles (AUVs) have been widely used in a variety of applications, such as seabed exploration, oceanographic surveys, and biological monitoring, playing an increasingly important role (Papadopoulos et al., 2010;Tan et al., 2011). As AUVs begin to evolve toward intelligence, large size, and high endurance, accurate navigational information is critical for AUVs to perform their missions safely and effectively over long time . ...
The existing strapdown inertial navigation system (SINS)/Doppler velocity log (DVL)/ultra-short baseline system (USBL) integrated navigation error models directly apply algebraic differences to define the vector error, which is not strictly accurate. Considering that the invariant error definitions derived from Lie group theory have been used in the navigation field to obtain more accurate linear error models, in this paper, a new SINS/DVL/USBL integrated navigation system is investigated based on the invariant error definition and tightly coupled structure. In order to suppress the effect of measurement outliers on navigation accuracy, a new statistical similarity measure (SSM)-based multiple adaptive outlier-robust state estimator (MAORSE) is proposed. It decomposes the noise covariance matrix into multiple sub-matrices. Through the estimation and adjustment of sub-matrices, the influence of abnormal observations on the filtering results is weakened while realizing the full utilization of normal observation information. The test results demonstrate the effectiveness and superiority of the proposed invariant error-based SINS/DVL/USBL tightly coupled integrated navigation algorithm and SSM-based MAORSE.
... Underwater Wireless Sensor Networks (UWSN) Review (Tan et al., 2011): This in-depth analysis of UWSNs takes into account elements including ambient variables, localization strategies, media access control, routing protocols, and the effect of packet size on communication effectiveness. ...
Wireless sensor networks (WSNs) have emerged as a crucial component in the field of networking due to their cost-effectiveness, efficiency, and compact size, making them invaluable for various applications. However, as the reliance on WSN-dependent applications continues to grow, these networks grapple with inherent limitations such as memory and computational constraints. Therefore, effective solutions require immediate attention, especially in the age of the Internet of Things (IoT), which largely relies on the effectiveness of WSNs. This study undertakes a comprehensive review of research conducted between 2018 and 2020, categorizing it into six main domains: 1) Providing an overview of WSN applications, management, and security considerations. 2) Focusing on routing and energy-saving techniques. 3) Reviewing the development of methods for information gathering, emphasizing data integrity and privacy. 4) Emphasizing connectivity and positioning techniques. 5) Examining studies that explore the integration of IoT technology into WSNs, with an eye on secure data transmission. 6) Highlighting research efforts aimed with a strong emphasis on energy efficiency. The study addresses the motivation behind employing WSN applications in IoT technologies, as well as the challenges, obstructions, and solutions related to their application and development. It underscores that energy consumption remains a paramount issue in WSNs, with untapped potential for improving energy efficiency while ensuring robust security. Furthermore, it identifies existing approaches' weaknesses, rendering them inadequate for achieving energy-efficient routing in secure WSNs. This review sheds light on the critical challenges and opportunities in the field, contributing to a deeper understanding of WSNs and their role in secure IoT applications.
... The research conducted in [34] focused on security challenges and applications for UWSNs environment. Authors in [35] conducted survey on the challenges and techniques in underwater localization; authors of [36] explored the architectural challenges in UWSNs; authors of [37] discussed the challenges and security issues in UWSNs; authors of [38] discussed the issues and challenges regarding the implementation of UWSNs; authors of [39] conducted survey on security infrastructure for UWSNs; authors of [7] conducted survey on UWSNs and discussed open research challenges; an exhaustive study on UWSNs modems is presented in [40]; the classification of UWSNs modems, analysis, as well as design challenges are presented in [41]. The researchers in [42][43][44][45][46] conducted a survey on routing protocols in UWSNs; authors of [47] conducted a survey on multi-path routing protocols for UWSNs. ...
Citation: Saeed, K.; Khalil, W.; Al-Shamayleh, A.S.; Ahmed, S.; Akhunzada, A.; Alharthi, S.Z.; Gani, A. A Comprehensive Analysis of Security-Based Schemes in Underwater Wireless Sensor Networks. Sustainability 2023, 15, 7198. https://doi.
... Anchor-based underwater localization. There has been prior interest in achieving underwater tracking for dive computers, sensors and robots [24,30,63,68,69,71,78,85,88,89,91,92,94,107]. These proposals use time of arrival [31], time difference of arrival [33], angle of arrival [45] or signal strength [77] to estimate distances and angles from known anchor buoys (see [46] for a detailed survey). ...
The emergence of water-proof mobile and wearable devices (e.g., Garmin Descent and Apple Watch Ultra) designed for underwater activities like professional scuba diving, opens up opportunities for underwater networking and localization capabilities on these devices. Here, we present the first underwater acoustic positioning system for smart devices. Unlike conventional systems that use floating buoys as anchors at known locations, we design a system where a dive leader can compute the relative positions of all other divers, without any external infrastructure. Our intuition is that in a well-connected network of devices, if we compute the pairwise distances, we can determine the shape of the network topology. By incorporating orientation information about a single diver who is in the visual range of the leader device, we can then estimate the positions of all the remaining divers, even if they are not within sight. We address various practical problems including detecting erroneous distance estimates, addressing rotational and flipping ambiguities as well as designing a distributed timestamp protocol that scales linearly with the number of devices. Our evaluations show that our distributed system running on underwater deployments of 4-5 commodity smart devices can perform pairwise ranging and localization with median errors of 0.5-0.9 m and 0.9-1.6 m
... But for underwater environments, no such large-scale system exists. This is because electromagnetic signals attenuate very rapidly in water and do not propagate useful distances [2], [3]. In the absence of localization references such as GPS, it is common for an autonomous M vehicle to rely on its onboard sensors for dead reckoning. ...
Cooperative localization is an important technique in environments devoid of GPS-based localization, more so in underwater scenarios, where none of the terrestrial localization techniques based on radio frequency or optics are suitable due to severe attenuation. Given the large swaths of oceans and seas where autonomous underwater vehicles (AUVs) operate, traditional acoustic positioning systems fall short on many counts. Cooperative localization (CL), which involves sharing mutual information amongst the vehicles, has thus emerged as a viable option in the past decade. This paper assimilates the research carried out in AUV cooperative localization and presents a qualitative overview. The cooperative localization approaches are categorized by their cooperation and localization strategies, while the algorithms employed are reviewed on the various challenges posed by the underwater acoustic channel and environment. Furthermore, existing problems and future scope in the domain of underwater cooperative localization are discussed.
... In the field of underwater detection and communication, bottom-mounted horizontal arrays have received a great deal of attention since its advent. Severe challenges were posed towards deploying scheme designs and signal processing on account of that the underwater acoustic channel is variable and highly dependent on environmental factors, such as temperature, pressure, or salinity of the water column [7][8][9]. Plenty of bearing estimation methods have been developed to collect directional information about these sources [10,11]. These methods are all based on the plane-wave hypothesis, and conventional weighting was conducted in beamforming, which resulted in a deviated bearing estimation due to the multimode mechanism. ...
The direction-of-arrival (DOA) estimation of an underwater bottom-mounted horizontal linear array (HLA) based on weighted phase velocity has been proposed in this paper. The directional response is mainly affected by differences in the modal phase velocities and the sound speed of the water column. Based on the mode theory, the acoustic intensity distribution characteristics and beam deviation were analyzed. The beamforming result obtained provides a distinguishing feature of bearing deviation when the measured sound speed was used. By applying the modal weighted phase velocity instead, source bearing can be well estimated. Particularly, in the presence of a thermocline, the propagating modes can be selected on the basis of the mode trapping theory. Both surface and submerged sources were taken into account based on the experimental data, and the deviation was well explained and reduced. For a source near the end-fire direction, the bearing estimation error was reduced from several degrees to tenths of degrees.
... In particular, the channel between an acoustic source and a receiver may vary dramatically with their positions. While the related literature is abundant with handcrafted model-based solutions [5], many of these methods rely on isovelocity line-of-sight-based geometry, and are thus sensitive to multipath. Other methods that can theoretically operate in nontrivial environments, such as matched field processing [6], are highly sensitive to model mismatch [7], and are therefore less relevant for some practical purposes. ...
... In particular, the channel between an acoustic source and a receiver may vary dramatically with their positions. While the related literature is abundant with handcrafted model-based solutions [5], many of these methods rely on isovelocity line-of-sight-based geometry, and are thus sensitive to multipath. Other methods that can theoretically operate in nontrivial environments, such as matched field processing [6], are highly sensitive to model mismatch [7], and are therefore less relevant for some practical purposes. ...
Key challenges in developing underwater acoustic localization methods are related to the combined effects of high reverberation in intricate environments. To address such challenges, recent studies have shown that with a properly designed architecture, neural networks can lead to unprecedented localization capabilities and enhanced accuracy. However, the robustness of such methods to environmental mismatch is typically hard to characterize, and is usually assessed only empirically. In this work, we consider the recently proposed data-driven method [19] based on a deep convolutional neural network, and demonstrate that it can learn to localize in complex and mismatched environments. To explain this robustness, we provide an upper bound on the localization mean squared error (MSE) in the ``true" environment, in terms of the MSE in a ``presumed" environment and an additional penalty term related to the environmental discrepancy. Our theoretical results are corroborated via simulation results in a rich, highly reverberant, and mismatch channel.
... The research conducted in [34] focused on security challenges and applications for UWSNs environment. Authors in [35] conducted survey on the challenges and techniques in underwater localization; authors of [36] explored the architectural challenges in UWSNs; authors of [37] discussed the challenges and security issues in UWSNs; authors of [38] discussed the issues and challenges regarding the implementation of UWSNs; authors of [39] conducted survey on security infrastructure for UWSNs; authors of [7] conducted survey on UWSNs and discussed open research challenges; an exhaustive study on UWSNs modems is presented in [40]; the classification of UWSNs modems, analysis, as well as design challenges are presented in [41]. The researchers in [42][43][44][45][46] conducted a survey on routing protocols in UWSNs; authors of [47] conducted a survey on multi-path routing protocols for UWSNs. ...
Underwater wireless sensor networks (UWSNs) are comprised of sensor nodes that are deployed under the water having limited battery power and other limited resources. Applications
of UWSNs include monitoring the quality of the water, mine detection, environment monitoring, military surveillance, disaster prediction, and underwater navigation. UWSNs are more vulnerable to security attacks as compared to their counterparts such as wireless sensor networks (WSNs). The possible attacks in UWSNs can abrupt the operation of entire network. This research work presents the analysis of relevant research done on security-based schemes in UWSNs. The security-based schemes are categorized into five sub-categories. Each technique in each category is analyzed in detail.
The major contribution in each security-based scheme along with technique used, possible future research issues and implementation tool are discussed in detail. The open research issues and future trends identified and presented in this research can be further explored by the research community.
... Acoustic signals can propagate more efficiently under the water and are used commonly for underwater communications and sensor applications [2]. An alternative to acoustic sensors for underwater localization may be to use odometry, but due to the integration operation used in filters the sensor noises accumulate in time and the error must be corrected by some other means [3]. Hence, UWSNs are the primary choice for the localization of underwater vehicles. ...
Underwater localization and tracking is a challenging problem and Time-of-Arrival and Time-Difference-of-Arrival approaches are commonly used. However, the performance difference between these approaches is not well understood or analysed adequately. There are some analytical studies for terrestrial applications with the assumption that the signal arrival times are not correlated. However, this assumption is not valid for underwater propagation. To present the distinct nature of the problem under the water, a high-fidelity simulation is required. In this study, Time-of-Arrival and Time-Difference-of-Arrival approaches are compared using a ray tracing based propagation model. Moreover, basic methods to mitigate the multipath propagation problem are also implemented for Bernoulli filters. Since the Bernoulli filter is a joint detection and tracking filter, the detection performance is also analysed. Comparisons are done for all combinations of filter and measurement approaches. The results can help to design underwater localization systems better suited to the needs.
... The existing UWAL methods are based on the complex Underwater Wireless Sensor Networks (UWSNs) [7]. The modem used for underwater node communication, the deployment of related sensor nodes, and clock synchronization are the key factors for the robustness of UWSNS [8,9]. ...
Underwater acoustic localization (UWAL) is extremely challenging due to the multipath nature of extreme underwater environments, the sensor position uncertainty caused by unpredictable ocean currents, and the lack of underwater observation data due to sparse array, which all affect localization performance. Addressing these issues, this paper proposes a simple and effective underwater acoustic localization method using the time difference of arrival (TDOA) measurements based on the multipath channel effect of the underwater environment. By introducing the calibration source, localization performance was improved, and the sensor position error was corrected. The Cramér–Rao lower bound (CRLB) was derived, and the proposed method was able to achieve the CRLB with small deviation. Numerical simulations confirm the improved performance of the proposed method, including (1) a 20 dB and 30 dB reduction in the CRLB for far and near source scenarios, respectively, indicating improved accuracy and reliability when estimating unknown sources; (2) better Mean Squared Error (MSE) performance compared to existing methods and an efficiency of over 90% in low noise and above 80% in moderate noise in several scenarios, with a delayed threshold effect; and (3) achieving CRLB performance with only three sensors in a 3D space, even under moderate noise, while existing methods require at least five sensors for comparable performance. Our results demonstrate the efficacy of the proposed method in enhancing the accuracy and efficiency of source localization.
... From the perspective of data transmission, the twostep methods can be easily implemented in real tasks, while the communication burden is heavy when the direct localization methods are used since raw data is to be transmitted from the sensing platforms to the central station. On the other hand, the latter have higher localization accuracy, since more information about the target source is contained in the transmitted data [18,19]. ...
Traditional two-step localization methods and direct localization methods have practical problems when they are used for underwater acoustic source localization. In this paper, a localization method based on the feature-level information fusion is proposed, in which the Hough Transform is exploited to detect the line characteristics of the spatial features of the target. A secondary accumulation procedure is proposed to extract and fuse the good features instead of fusing all features. The possibility to produce a ghost target is greatly reduced. Hence, the robustness of the proposed method in low SNR scenarios is improved. Experimental results validate the efficiency of exploiting the Hough Transform to eliminate interfering spatial features without sacrificing the localization accuracy.
... However, the nature of the underwater environment induces several challenges in localizing nodes. Examples of these challenges are [2], [3](iii) GPS does not work well underwater due to the high attenuation of radio waves in such environments. Thus, several localization schemes have been developed specifically for UWSNs to address these issues (e.g., [4], [5], [6], [7], [8], [9]). ...
This paper studies the impact of different localization schemes on the performance of location-based routing for UWSNs. Particularly, LSWTS and 3DUL localization schemes available in the literature are used to study their effects on the performance of the ERGR-EMHC routing protocol. First, we assess the performance of two localization schemes by measuring their localization coverage, accuracy, control packets overhead, and required localization time. We then study the performance of the ERGR-EMHC protocol using location information provided by the selected localization schemes. The results are compared with the performance of the routing protocol when using exact nodes' locations. The obtained results show that LSWTS outperforms 3DUL in terms of localization accuracy by 83% and localization overhead by 70%. In addition, the results indicate that the localization error has a significant impact on the performance of the routing protocol. For instance, ERGR-EMHC with LSWTS is better in delivering data packets by an average of 175% compared to 3DUL.
... Environmentally aided navigation in which floats select target depths based on hydrodynamic models of the local currents (Langebrake et al., 2002;Jouffroy et al., 2011;Huynh et al., 2014;Smith and Huynh, 2014;Troesch et al., 2016) could enable low-level spatial coordination behaviors such as aggregation and dispersion (Ota, 2006;Nedjah and Junior, 2019) or persistence in an energetic area of interest (higher-level coordination, like flocking or formation control, are not generally feasible with floats due to the severe underactuation relative to the environment, though specific flow structures like eddies may enable formation control on short time scales). Utilizing the bidirectional nanomodem capabilities could enable field demonstrations of mobile underwater wireless sensor networks (Akyildiz et al., 2002;Tan et al., 2011;Heidemann et al., 2012), though scalability is ultimately limited by acoustic range (∼1 km) and desired position update rates. Such a network would allow µFloats to share environmental information across the array, enabling real-time coordination of float activity and adaptive sampling, thus qualifying as a robotic "swarm" (Şahin, 2004), or as near to as is possible for a system of floats and drifters. ...
Buoyancy-controlled underwater floats have produced a wealth of in situ observational data from the open ocean. When deployed in large numbers, or “distributed arrays,” floats offer a unique capacity to concurrently map 3D fields of critical environmental variables, such as currents, temperatures, and dissolved oxygen. This sensing paradigm is equally relevant in coastal waters, yet it remains underutilized due to economic and technical limitations of existing platforms. To address this gap, we developed an array of 25 μFloats that can actuate vertically in the water column by controlling their buoyancy, but are otherwise Lagrangian. Underwater positioning is achieved by acoustic localization using low-bandwidth communication with GPS-equipped surface buoys. The μFloat features a high-volume buoyancy engine that provides a 9% density change, enabling automatic ballasting and vertical control from fresh to salt water ( 3% density change) with reserve capacity for external sensors. In this paper, we present design specifications and field benchmarks for buoyancy control and acoustic localization accuracy. Results demonstrate depthholding accuracy within ±0.2 m of target depth in quiescent flow and ±0.5 m in energetic flows. Underwater localization is accurate to within ±5 m during periods with sufficient connectivity, with degradation in performance resulting from adverse sound speed gradients and unfavorable spatial distributions of surface buoys. Support for auxiliary sensors (<10% float volume) without additional control tuning is also demonstrated. Overall performance is discussed in the context of potential use cases and demonstrated in a first-ever array-based three-dimensional survey of tidal currents.
... UWSNs (Underwater Wireless Sensor Networks) is born from the need to explore and monitor the underwater environment in real time, in order to provide some agility in the development of countless applications, whether for scientific, commercial or military purposes [3,11,5]. According to [5] a UWSN consists of sensor nodes, the number of which depends on the area to be covered, considering factors such as transmission range and network performance. ...
Underwater Wireless Sensor Networks (UWSNs) technology is strongly present in the research area, where many applications have been developed for monitoring of the underwater environments such as oil bases, pollution control, natural disasters, among others. Considering that the planet is covered by 70% of water, it is important to understand how to carry out communications in these environments, as a challenge by its limitations such as bandwidth, propagation speed, high delays, complex deployments, difficulty in energy recharge, among the most important. This study addresses an application development that allows simulating UWSNs in a controlled environment that considers attributes of the ISO/IEC 25010 standard that covers the quality of the software product. This will enable telecommunications students simulate, learn and understand about UWSN. It will be easier and simpler compared to more robust simulators such as OMNET, NS2 or NS3.
... Range estimates of marine mammal vocalizations have been used to approximate population density 2 or to fully localize the animal. 5 The literature is rich with various approaches for underwater localization using acoustic sensor networks 6 that collectively exhibit tradeoffs between accuracy, efficiency, area coverage, and ease of deployment. The typical approach to localize marine mammals is to use arrays of synchronized sensors to collect PAM data and analyze the relative arrival times. ...
The low-frequency impulsive gunshot vocalizations of baleen whales exhibit dispersive propagation in shallow-water channels which is well-modeled by normal mode theory. Typically, underwater acoustic source range estimation requires multiple time-synchronized hydrophone arrays which can be difficult and expensive to achieve. However, single-hydrophone modal dispersion has been used to range baleen whale vocalizations and estimate shallow-water geoacoustic properties. Although convenient when compared to sensor arrays, these algorithms require preliminary signal detection and human labor to estimate the modal dispersion. In this paper, we apply a temporal convolutional network (TCN) to spectrograms from single-hydrophone acoustic data for simultaneous gunshot detection and ranging. The TCN learns ranging and detection jointly using gunshots simulated across multiple environments and ranges along with experimental noise. The synthetic data are informed by only the water column depth, sound speed, and density of the experimental environment, while other parameters span empirically observed bounds. The method is experimentally verified on North Pacific right whale gunshot data collected in the Bering Sea. To do so, 50 dispersive gunshots were manually ranged using the state-of-the-art time-warping inversion method. The TCN detected these gunshots among 50 noise-only examples with high precision and estimated ranges which closely matched those of the physics-based approach.
... Localization continues to be an important topic for underwater nodes because of the unavailability of Global Positioning System (GPS) signals underwater. Instead, some reference/anchored nodes were used to localize deployed unknown underwater nodes [215][216][217][218][219]. However, an open problem is to investigate the localization of underwater nodes in direct A-W systems, possibly by complementing both reference/surface underwater nodes, and traditional localization mechanisms from overwater. ...
The technologies used in underwater and air-water (A-W) wireless communication are increasingly attracting attention due to numerous modern applications. However, for practical implementations of these modern applications, the security of the communication networks needs to be ensured beforehand. The main focus of this survey is to systematically discuss the security needs of underwater and A-W wireless communication networks, and solutions proposed to date. Before extending our discussion on security, we initially cover the fundamentals of underwater and A-W wireless communication. First, we provide a comprehensive overview of different underwater communication technologies: radio frequency (RF), acoustic, optic, and magnetic induction (MI) in terms of channel characteristics, merits, and demerits. The discussion is further extended to A-W wireless communication by presenting direct and indirect (relay-aided) techniques. Then we present the primer on information security which highlights the four fundamental properties of security (i.e., confidentiality, integrity, authentication, and availability) and security solutions (i.e., cryptography and physical layer security) built for the considered underwater communication technologies. In addition, we present the security aspects of underwater and A-W wireless communication in detail by reviewing and summarizing the existing work in the literature. Finally, we highlight some research gaps in the literature and propose a few security-related open problems that we believe deserve to receive more attention from the research community.
This paper investigates the tracking control problem for unmanned underwater vehicles (UUVs) systems with sensor faults, input saturation, and external disturbance caused by waves and ocean currents. An active sensor fault-tolerant control scheme is proposed. First, the developed method only requires the inertia matrix of the UUV, without other dynamic information, and can handle both additive and multiplicative sensor faults. Subsequently, an adaptive fault-tolerant controller is designed to achieve asymptotic tracking control of the UUV by employing robust integral of the sign of error feedback method. It is shown that the effect of sensor faults is online estimated and compensated by an adaptive estimator. With the proposed controller, the tracking error and estimation error can asymptotically converge to zero. Finally, simulation results are performed to demonstrate the effectiveness of the proposed method.
The construction of an underwater sensor network system necessitates the swift and cost-effective acquisition of precise sound velocity profile data, which is crucial for enhancing underwater positioning accuracy and guaranteeing secure underwater wireless communication. This letter introduces an adaptive sound velocity profile prediction method premised on deep reinforcement learning (DRL-ASP). The DRL-ASP algorithm dynamically interacts with the environment and adjusts its behavior to maximize environmental rewards. During this interactive process, it continuously updates the sound velocity profile, leading to improved accuracy in predicting the sound velocity profile. The efficacy of the DRL-ASP algorithm was evaluated through experiments conducted on datasets from the South China Sea, Arctic Ocean, and Southern Ocean. Its performance in terms of sound velocity error, mean square error, fitting accuracy, and relative error was compared against empirical formula sound velocity prediction methods,
$Q$
-learning-based sound velocity prediction methods, and convolutional-neural-network-based sound velocity prediction methods. The results affirmed that the DRL-ASP algorithm exhibits superior prediction accuracy, enhanced search efficiency, and robust stability.
Underwater swarm robotics has gained prominence as an innovative paradigm for diverse applications, including environmental monitoring and marine exploration. This review paper presents a comprehensive review of low-cost underwater swarm acoustic localization systems, focusing on recent research findings validated through field experiments. To aid research on the concept of low-cost swarm acoustic localization, this article provides overview of cost-effective underwater swarm applications and the applicability assessment of traditional acoustic localization strategies, then presents several crucial components for building an acoustic ranging-based low-cost swarm localization system, including low-cost acoustic modems and low-cost swarm localization system with cooperative strategies. In summary, this review serves as a valuable resource for researchers and practitioners in underwater swarm robotics and acoustic localization, addressing challenges, strategies, and goals of low-cost swarm acoustic localization systems.
Underwater communication improved with the aid of the Internet of Things (IoT) and refers to intelligent system activities, and network modules in different conditions. Past few years, the growth in the development of underwater mapping is highly increasing and demanding. This underwater communication is associated with the transmission of acoustic waves, as these waves have the capability to transmit long-range communication. Due to the aqueous aspect of signal absorption, low-frequency signals are conveyed in the underwater Internet of Things (UIoT). Improving transmission and optimizing network communication performance in IoT-enabled hazardous underwater situations are an endless challenge. The quality of service is changed based on the effect of collisions and network interference, which may lead to energy consumption, end-to-end delay, low packet delivery ratio, and low latency in the networks. This research proposes a Reliable Forwarded Communication Routing Transmission Protocol (RFC-RTP) for efficient energy consumption and improved network lifetime. Artificial rabbits optimization is used to pick the relay and balance the energy consumption ratio and end-to-end delay. In this proposed work, an RTP reduces the underwater collision for forwarder nodes sending information to the surface basin. The RFC-RTP protocol simulations are compared with other existing protocols in terms of energy consumption, end-to-end delay, and network lifetime.
When fully implemented, sixth generation (6G) wireless systems will constitute intelligent wireless networks that enable not only ubiquitous communication but also high-accuracy localization services. They will be the driving force behind this transformation by introducing a new set of characteristics and service capabilities in which location will coexist with communication while sharing available resources. To that purpose, this survey investigates the envisioned applications and use cases of localization in future 6G wireless systems, while analyzing the impact of the major technology enablers. Afterwards, system models for millimeter wave, terahertz and visible light positioning that take into account both line-of-sight (LOS) and non-LOS channels are presented, while localization key performance indicators are revisited alongside mathematical definitions. Moreover, a detailed review of the state of the art conventional and learning-based localization techniques is conducted. Furthermore, the localization problem is formulated, the wireless system design is considered and the optimization of both is investigated. Finally, insights that arise from the presented analysis are summarized and used to highlight the most important future directions for localization in 6G wireless systems.
Background: Navigation and localization are key to the successful execution of autonomous unmanned underwater vehicles (UUVs) in marine environmental monitoring, underwater 3D mapping, and ocean resource surveys. The estimation of the position and the orientation of autonomous UUVs are a long-standing challenging and fundamental problem. As one of the underwater sensors, camera has always been the focus of attention due to its advantages of low cost and rich content information in low visibility waters, especially in the fields of visual perception of the underwater environment, target recognition and tracking. At present, the visual real-time pose estimation technology that can be used for UUVs is mainly divided into geometry-based visual positioning algorithms and deep learning-based visual positioning algorithms.
Methods: In order to compare the performance of different positioning algorithms and strategies, this paper uses C++ and python, takes the ORB-SLAM3 algorithm and DF-VO algorithm as representatives to conduct a comparative experiment and analysis.
Results: The geometry-based algorithm ORB-SLAM3 is less affected by illumination, performs more stably in different underwater environments, and has a shorter calculation time, but its robustness is poor in complex environments. The visual positioning algorithm DF-VO based on deep learning takes longer time to compute, and the positioning accuracy is more easily affected by illumination, especially in dark conditions. However, its robustness is better in unstructured environments such as large-scale image rotation and dynamic object interference.
Conclusions: In general, the deep learning-based algorithm is more robust, but multiple deep learning networks make it need more time to compute. The geometry-based method costs less time and is more accurate in low-light and turbid underwater conditions. However, in real underwater situations, these two methods can be connected as binocular vision or methods of multi-sensor combined pose estimation.
This research develops a novel sensor for aquatic robots inspired by the whiskers of harbor seals. This sensor can detect the movement of water, offering valuable data on speed, currents, barriers, and water disturbance. It employs a mechano-magnetic system, separating the whisker-like drag part from the electronic section, enhancing water resistance and durability. The flexible design allows customizing the drag component's shape for different uses. The study uses an analytical model to examine the sensor's capabilities, including aspects such as shape, cross-sectional area, ratio, and immersion depth of the whisker part. It also explores the effects of design on Vortex-Induced Vibrations (VIVs), a key focus in the study of biological and robotic aquatic whiskers. The sensor's practical use was tested on a remote-controlled boat, showing its proficiency in estimating water flow speed. This development has enormous potential to enhance navigation and perception for aquatic robots in various applications.
The ocean is vital for humankind but may cause catastrophes when unhealthy. Although there have been efforts to build ocean monitoring systems, the understanding of the underwater environment is limited due to the cost and challenges of obtaining real-time marine data. One potential solution is to build stationary ocean observation systems based on wireless communication due to its affordable cost. In this study, we divide these systems into three components: underwater data acquisition, network communication, and data management. We investigate the engineering challenges associated with each component, the causes, and how they relate. The literature has not discussed the technical issues of building stationary smart ocean monitoring systems entirely based on wireless communication yet. This paper fills that research gap by conducting semi-structured interviews with 17 experts knowledgeable about underwater sensors, underwater acoustic communication, offshore network communication, and underwater data usage. The identified challenges are compared with the literature to assess whether our findings are novel or are a confirmation of what have been already found in prior publications. The Internet of Things (IoT) used in smart city platforms is quite advanced, but the Internet of Underwater Things (IoUT) employed in smart ocean monitoring systems has several unresolved issues; although IoT is viewed as a foundation for IoUT. Therefore, we compare fundamental differences between the technologies used in the smart city and the smart ocean domains, explaining why some of our identified challenges are unique in the marine context.
This paper investigates the problem of localization of mobile nodes in the marine environment under conditions of information deficiency. To solve this problem, sparse feature points (SFPs) extraction-based time of flight (ToF) minimum residual localization algorithm and localization based on the prior information of the target under partial information loss are proposed. First, the SFPs extraction method is adopted to fit the sound speed profile (SSP). Based on this, the SFPs extraction-based ToF computational model is proposed. The coordinates of the nodes to be located are calculated by ToF measurement and the ToF model for minimum residual localization. Second, in the case of information loss, particle ranges are generated using the target history a prior information. This is combined with the received node localization information to locate the node by the proposed target prior information-based localization method. Finally, the results of the simulation experiments show that the proposed method achieves a more detailed description of the SSP characteristics. The localization error of the proposed method is reduced fivefold compared with other methods under the condition of information loss, which is more in line with the spatial characteristics of the underwater environment.
Conservation of Underwater Cultural Heritage is crucial to preserve society's history. This work proposes a platform based on Internet of Underwater Things technologies and the Edge Computing paradigm. It will incorporate Artificial Intelligence techniques that support the monitoring and management of Underwater Cultural Heritage. These algorithms and models, capable of generating knowledge, will work as a supporting tool for decision-making. The platform will integrate information stored in databases with data acquired in real-time, working independently and in collaboration with other platforms and systems.
In this paper, we proposed a novel Multiple Constraints Satisfaction Based Reliable Localization Algorithm for mobile Underwater Wireless Sensor Networks (UWSNs). In a typical application, e.g. the ocean battlefields, the localization process has been no doubt constantly restricted by several kinds of uncertainty, which lead to obvious degradation of localization reliability and accuracy, e.g. the confidence of reference information, the mobility of sensor nodes, the reliability of multi-hop localization link, etc. It implies a limit and an insufficiency of localization reliability. Thus, we transformed the reliable localization problem into a multiple Constraints Satisfaction Problem (CSP). In the CSP framework, we firstly integrated three kinds of constraints, i.e. confidence constraint, mobility constraint, and reliability constraint. Then game method has been utilized to deal with the CSP and determine the positions of underwater sensor nodes. Simulation results show that algorithm is effective and efficient.
The paper addresses the general problem of estimating the position of an underwater target carrying an acoustic emitter by measuring the times of arrival (TOAs) of the acoustic signals at a set of surface buoys equipped with submerged hydrophones and GPS receivers. Examples of underwater targets of interest include AUVs (Autonomous Underwater Vehicles) and ROVs (Remotely Operated Vehicles) as well as manned sub- mersibles, divers, and even marine animals. When compared with classical systems, the class of underwater acoustic positioning systems considered in this paper is far more versa- tile and portable and the costs of operation are greatly reduced. This justifies the increasing interest that such systems have received over the past few years, both from a theoretical and practical standpoint. Research and development in this area have progressed to the point where a commercial product made its appearance in the market: the so-called GIB (GPS Intelligent Buoys). However, much work remains to be done towards the develop- ment of operational systems capable of yielding adequate performance in the presence of multi-path eects and acoustic outliers. The paper gives a brie f overview of this area of
In this paper a hydrodynamic model and associated post-processing tools for the Lower Hudson River (LHR) are presented. The
model computes the two-dimensional (2D), depth-averaged Eulerian time-dependent velocity field in response to various external
signals. The paper documents the mathematical background of the model, describes modeling logistics and provides the comparison
of model results with observed data. As an example of the potential application, the scenario of managing sewage releases
from two New York City water pollution treatment plants was investigated using this numerical model. The study was undertaken
as part of research on the chaotic nature of the LHR estuarine system and pollutant dispersion characteristics.
The micro-modem is a compact, low-power, underwater acoustic communications and navigation subsystem. It has the capability to perform low-rate frequency-hopping frequency-shift keying (FH-FSK), variable rate phase-coherent keying (PSK), and two different types of long base line navigation, narrow-band and broadband. The system can be configured to transmit in four different bands from 3 to 30 kHz, with a larger board required for the lowest frequency. The user interface is based on the NMEA standard, which is a serial port specification. The modem also includes a simple built-in networking capability which supports up to 16 units in a polled or random-access mode and has an acknowledgement capability which supports guaranteed delivery transactions. The paper contains a detailed system description and results from several tests are also presented
The underwater acoustic channel is characterized by a path loss that depends not only on the transmission distance, but also on the signal frequency. As a consequence, transmission bandwidth depends on the transmission distance, a feature that distinguishes an underwater acoustic system from a terrestrial radio system. The exact relationship between power, transmission band, distance and capacity for the Gaussian noise scenario is a complicated one. This work provides a closed-form approximate model for (1) power consumption, (2) band-edge frequency and (3) bandwidth as functions of distance and capacity required for a data link. This approximate model is obtained by numerical evaluation of analytical results which takes into account physical models of acoustic propagation loss and ambient noise. The closed-form approximations may become useful tools in the design and analysis of underwater acoustic networks.
For large wireless sensor networks, identifying the exact location of every sensor may not be feasible and the cost may be very high. A coarse estimate of the sensors' locations is usually sufficient for many applications. In this paper, we propose an efficient Area Localization Scheme (ALS) for underwater sensor networks. This scheme tries to estimate the position of every sensor within a certain area rather than its exact location. The granularity of the areas estimated for each node can be easily adjusted by varying system parameters. All the complex calculations are handled by the powerful sinks instead of the sensors. This reduces the energy consumed by the sensors and helps extend the lifetime of the network.
The existence of obstacles in harbors or near shore environments leads to Non-Line-Of-Sight (NLOS) links between two underwater acoustic communication (UWAC) nodes. That is, only echoes of the transmitted signal arrive at the receiving node. Mistaking the first (strong) echo as a Line-Of-sight (LOS) measurement and using it for ranging causes significant degradation of the accuracy level of UWAC-based localization. In this paper, we propose a solution for the NLOS identification problem in underwater acoustic localization. Results from both extensive simulations and sea trial experiments confirm our approach and demonstrate a high detection rate of NLOS measurements.
Underwater acoustic sensor networks are quite different from terrestrial wireless sensor networks. Localization for underwater applications is different due to the bandwidth limited acoustic communication, sparsely distributed network deployment, and more expensive and powerful sensor nodes. In this paper, we propose a new scheme to achieve better localization accuracy for underwater acoustic sensor networks. Instead of using the commonly adopted circle-based event detection and least squares algorithm based location estimation, the proposed scheme utilizes the hyperbola-based approach for event localization and a normal distribution for estimation error modeling and calibration. Our analysis and simulation results indicate that the performance of the proposed scheme is clearly better than those from the least squares location estimation based localization schemes.
In the offshore engineering community, deep underwater construction activities such as installation of mooring systems for oil and gas extraction require payloads such as subsea templates, Christmas trees and manifolds to be installed accurately. In this paper, we consider a recently proposed underwater positioning system (UPS) to support deepwater installations. We identify and demonstrate its shortcomings in harsh underwater acoustic channels. We then propose enhancements to UPS, and demonstrate numerically that our proposed scheme achieves significantly better localization speed, at lower communication costs while preserving the "silent" property with a relatively small underwater acoustic sensor network deployed on the seabed in typically underwater channel conditions.
Automatic Web services composition can be achieved by using AI planning techniques. HTN planning has been adopted to handle the OWL-S Web service composition problem. However, existing composition methods based on HTN planning have not considered the choice of decompositions available to a problem which can lead to a variety of valid solutions.In this paper, we propose a model of combining a Markov decision process model and HTN planning to address Web services composition. In the model, HTN planning is enhanced to decompose a task in multiple ways and hence be able to find more than one plan,taking both functional and non-functional properties into account. Furthermore, an evaluation method to choose the optimal plan and some experimental results illustrate that the proposed approach works effectively.
Underwater mobile acoustic sensor networks are promising tools for the exploration of the oceans. These networks require new robust solutions for fundamental issues such as: localization service for data tagging and networking protocols for communication. All these tasks are closely related with connectivity, coverage and deployment of the network. A realistic mobility model that can capture the physical movement of the sensor nodes with ocean currents gives better understanding on the above problems. In this paper, we propose a novel physically-inspired mobility model which is representative of underwater environments. We study how the model affects a range-based localization protocol, and its impact on the coverage and connectivity of the network under different deployment scenarios.
Distributed time synchronization is an important part of a sensor network where sensing and actuation must be coordinated across multiple nodes. Several time synchronization protocol that maximize accuracy and energy conservation have been developed, including FTSP, TPSN, and RBS. All of these assume nearly instantaneous wireless communication between sensor nodes; each of them work well in today's RF-based sensor networks. We are just beginning to explore underwater sensor networks where communication is primarily via acoustic telemetry. With acoustic communication, where the propagation speed is nearly five orders of magnitude slower than RF, assumptions about rapid communication are incorrect and new approaches to time synchronization are required. We present Time Synchronization for High Latency (TSHL), designed assuming such high latency propagation. We show through analysis and simulation that it achieves precise time synchronization with minimal energy cost. Although at very short distances existing protocols are adequate, TSHL shows twice the accuracy at 500m, demonstrating the need to model both clock skew and propagation latency.
Underwater localization is challenging as its efficacy is affected by propagation delays, motion-induced doppler shift, phase and amplitude fluctuations, multipath interference etc that are inherent in underwater acoustic channels. In this paper, we consider a recently proposed Underwater Positioning Scheme, which offers unique localization only in a finite region. We quantify the conditions for unique localization and propose a variant that offers unique localization with high probability regardless of the reference and unknown node deployment. We demonstrate the trade-offs between both schemes in terms of localizability space, localization latency and energy consumption.
Underwater sensor networks (UWSN) are widely used in many applications, such as oceanic resource exploration, pollution monitoring, tsunami warnings and mine reconnaissance. In UWSNs, determining the location information of each sensor node is a critical issue, because many services are based on the localization results. In this paper, we introduce a novel underwater localization approach based on directional signals, which are transmitted by an autonomous underwater vehicle (AUV). Our method utilizes directional beacons (UDB) to replace traditional omni-directional localization which provides more accurate and efficient ways to locate the sensors themselves by simple calculations. The advantage of this novel scheme is that the communications between AUV and sensors are not necessary because the AUV broadcasts signals and sensors only need to passively listen to the signals. Since the energy consumption for transmissions in underwater environments is a nontrivial factor, our localization scheme not only supports accurate positioning, but also reduces energy consumption of sensors. We evaluate our scheme by simulations. The results show that our new approach is very precise in a strap area. At the same time, we minimize the number of beacons issued from the AUV.
In underwater sensor networks (UWSNs), determining the location of every sensor is important and the process of estimating the location of each node in a sensor network is known as localization. While various localization algorithms have been proposed for terrestrial sensor networks, there are relatively few localization schemes for UWSNs. The characteristics of underwater sensor networks are fundamentally different from that of terrestrial networks. Underwater acoustic channels are characterized by harsh physical layer environments with stringent bandwidth limitations. The variable speed of sound and the long propagation delays under water pose a unique set of challenges for localization in UWSN. This paper explores the different localization algorithms that are relevant to underwater sensor networks, and the challenges in meeting the requirements posed by emerging applications for such networks, e.g. offshore engineering.
Although there are numerous time synchronization algo- rithms recently proposed for terrestrial wireless sensor net- works, none of these could be directly applied to underwater acoustic sensor networks. This is because they typically as- sume that the propagation delay is negligible, which is not the case in underwater. Furthermore, the sensor nodes in underwater tend to have some degree of mobility due to wind or ocean current, which complicates the problem even more by introducing time-varying delay. In this paper, we propose a cluster-based synchronization algorithm for underwater acoustic mobile networks, called "MU-Sync". Our design avoids frequent re-synchronization by estimating both the clock skew and offset. As underwa- ter mobile networks experience both time-varying and long propagation delay, previous works that estimate the clock skew using a single least square error linear regression tend to be inaccurate. In the MU-Sync, the clock skew is esti- mated by performing the linear regression twice over a set of local time information gathered through message exchanges. The first linear regression enables the cluster head to offset the effect of long and varying propagation delay; the second regression in turn obtains the estimated skew and offset. With the help of MAC-level time stamping, we can further reduce the nondeterministic errors that are commonly en- countered by those synchronization algorithms that rely on message exchanges.
In this paper, architectures for two-dimensional and three -dimensional underwater sensor networks are discussed. A detailed overview on the current solutions for medium access control, network, and transport layer protocols are given and open research issues are dis- cussed.
In this paper, we address the localization issue in Underwater Sen- sor Networks (UWSNs). We propose Dive'N'Rise(DNR) Position- ing, the novel idea of using DNR beacons for localization. These beacons get their coordinates from GPS while floating above the water, then they dive into water. While sinking and rising, they broadcast their positions. Sensor nodes are localized by passively listening to DNR beacon messages which reduces the communi- cation cost and the energy consumption. We analyze localization success and error for static and mobile UWSNs.
In this paper, we propose a novel distributed localization scheme LDB, a 3D localization scheme with directional beacons for Underwater Acoustic Sensor Networks (UWA-SNs). LDB localizes sensor nodes using an Autonomous Underwater Vehicle (AUV) as a mobile beacon sender. Mounted with a directional transceiver which creates conical shaped directional acoustic beam, the AUV patrols over the 3D deployment volume with predefined trajectory sending beacons with constant interval towards the sensor nodes. By listening two or more beacons sent from the AUV, the nodes can localize themselves silently. Through theoretical analysis, we provide the upper bound of the estimation error of the scheme. We also evaluate the scheme by simulations and the results show that our scheme can achieve a high localization accuracy, even in sparse networks.
Unlike the terrestrial wireless networks that utilize the radio channel, underwater networks use the acoustic channel, which poses research challenges in the medium access control (MAC) protocol design due to its low bandwidth and high propagation delay characteristics. Since most of the MAC protocols for wireless terrestrial networks have been designed with negligible propagation delay in mind, they generally perform poorly when applied directly in underwater acoustic networks, especially for the case of handshaking-based protocols. In this paper, we propose a MACA-based MAC protocol with packet train to multiple neighbors (MACA-MN). It improves the channel utilization by forming a train of packets destined for multiple neighbors during each round of handshake, which greatly reduces the relative proportion of time wasted due to the propagation delays of control packets. This approach also reduces the hidden terminal problem. Our simulations show that the MACA-MN is able to achieve much higher throughput than the MACA protocol.
This article reviews progress in the area of underwater acoustic modeling techniques since 1980. Emphasis is placed on developments of general interest to the Navy sonar modeling community. They include: model refinements, bottom, interaction modeling, model operating systems and trainers, and specialized modeling applications in shallow water and Arctic environments.
Long baseline (LBL) positioning has many applications both commercially and in research, from surveying a ship hull to positioning offshore platforms in deeper waters. The technique consistently provides accuracies in the order of decimetres over large areas, independent of depth. Recent advances include the integration with other acoustic techniques or with inertial navigation systems for greater levels of accuracy.
Presents the fundamentals of underwater acoustics, acoustic signal generation, and acoustic signal processing in sufficient depth to permit the analysis of optimization of performance of underwater acoustic systems. Covers the generation and propagation of compressional acoustic waves in the ocean, including the complex effects that occur at the surface and bottom boundaries. Reviews Fourier methods, correlation techniques, random processes, and statistical detection and estimation theory.-from Author
Mathematical models describing acoustic underwater channels, cannot accurately predict the channel's behav-ior. To find a channel's response to a specific signal, sea trials need to be conducted. This paper presents a tool to Emulate Underwater Acoustic Channel (EUAC) by eval-uating its time varying impulse response. The tool allows estimation of the channel's output for any given signal communication scheme without the need for a sea trial, thus saving time and resources. The initial procedure requires a set of sea trials. In each experiment specific signals with narrow auto-correlation property are trans-mitted, and then their responses are recorded. This al-lows impulse response, Doppler shift, and phase shift es-timation of the actual channel. The results of the exper-iments can then be used to create a database of various EUAC. This database may be usefull in evaluating the performance of various communication schemes without sea trials.
Two simple equations for the speed of sound in sea waters, down to depths of 4 km, have been obtained as approximations to a more precise equation developed by Lovett. The simpler of the two is valid for all Neptunian waters except the Red Sea, Mediterranean Sea, and Persian Gulf, and agrees with Lovett’s equation to within about 0.1 m/s. The other includes these water masses and is in agreement with Lovett to within about 0.03 m/s. The two equations are well adapted to programmable handheld calculators.
In this paper, the underwater localization is given from wireless acoustic communication signals by probabilistic pattern recognition in eigenspace of PCA (principal components analyses). It should be emphasized that our underwater localization is from existing wireless acoustic communication signals, but not from additional localization systems. Our underwater localization scheme is based on fingerprinting and contains two stages, i.e., the off-line (i.e., training) and on-line (i.e., predicting) stages. In general, the received acoustic signals fluctuate seriously in underwater environments. To reduce the complexity and noise effects, all received signals are projected onto the eigenspace of PCA. Each projected feature is assumed to have Gaussian probabilistic distributions. Therefore, the location information can be easily obtained by probabilistic pattern recognition of projected features in PCA space. Note that our underwater localization scheme is not affected by reflected signals. To illustrate such a benefit, experiments were conducted in a bounded water pool where reflected signals exist near the walls. Experimental results show that the proposed underwater localization scheme is efficient and accurate. The proposed localization scheme is useful for underwater acoustic communication networks, and then in underwater technologies.
A simple yet accurate nine‐term, eight‐variable equation for sound speed in the oceans, suitable for programmable pocket calculators, is presented. Ranges of validity encompass: temperature −2° to 30° C, salinity 30° to 40°/°°, and depth 0 to 8000 m. Good quality oceanographic data at 15 worldwide stations, including two in the Mediterranean, were utilized for the computations. The Del Grosso and Mader [J. Acoust. Soc. Am. 52, 961–974 (1972)] sound‐speedequation was employed as ’’truth’’ after comparisons among Wilson [J. Acoust. Soc. Am. 32, 641–644. 1357 (1960)] and others. A precise method of computing pressure is detailed. Practical differences in critical depth, excess depth, conjugate depth, deep sound‐speed gradients, and echo‐sounder corrections are shown to be small between computations based on Wilson or Del Grosso and Mader sound‐speedequations.
The need for underwater wireless communications exists in off-shore oil industry, environmental monitoring, speech transmission between divers, control of autonomous underwater vehicles, and mapping of the ocean floor for detection of objects and discovery of new resources. Wireless underwater communications can be established by transmission of acoustic waves. However, the communication channels have limited bandwidth, and often cause severe multipath dispersion and time-variability. Despite these limitations, research efforts of the 90's have culminated in the development of underwater acoustic modems that are capable of transmitting information at rates on the order of several kilobits per second systems over varying distances. The emerging scenario is that of an underwater communication network consisting of both stationary and mobile nodes. Current research is focusing on the design of efficient modulation and coding schemes, adaptive signal processing algorithms for equalization and diversity combining, multiple-access communication methods and network protocols suited for low bandwidth, long propagation delays and strict power requirements encountered in the underwater environment.
In this paper, we study the localization problem in large-scale Underwater Wireless Sensor Networks (UWSNs). Unlike in the terrestrial positioning, the global positioning system (GPS) can not work efficiently underwater. The limited bandwidth, the severely impaired channel and the cost of underwater equipment all makes the localization problem very challenging. Most current localization schemes are not well suitable for deep underwater environment. We propose a hierarchical localization scheme to address the challenging problems. The new scheme mainly consists of four types of nodes, which are surface buoys, Detachable Elevator Transceivers (DETs), anchor nodes and ordinary nodes. Surface buoy is assumed to be equipped with GPS on the water surface. A DET is attached to a surface buoy and can rise and down to broadcast its position. The anchor nodes can compute their positions based on the position information from the DETs and the measurements of distance to the DETs. The hierarchical localization scheme is scalable, and can be used to make balances on the cost and localization accuracy. Initial simulation results show the advantages of our proposed scheme.
Three-dimensional Under-Water Acoustic Sensor Networks (UWASN) are supposed to be deployed for many applications. However,
a protocol for sensors’ self-localization and time-synchronization in UWASN remains a challenge problem. In this paper, we
developed a multilateration algorithm which could reliably localize and synchronize underwater sensor networks by acoustic
ranging. To our best knowledge, this is the first scheme which could achieve both them for 3D UWASN simultaneously. Simulation
results are also given to illustrate its effectiveness.
Although many localization protocols have been proposed for terrestrial sensor networks in recent years, the unique characteristics of the underwater acoustic communication channel, such as high and variable propagation delay and the three dimensional volume of the environment make it necessary to design and develop new localization algorithms. In this paper, a localization algorithm called three-dimensional underwater localization (3DUL) is introduced. 3DUL achieves networkwide robust 3D localization by using a distributed and iterative algorithm. Most importantly, 3DUL exploits only three surface buoys for localization initially. The sensor nodes leverage the low speed of sound to accurately determine the inter-node distances. Performance evaluations show that 3DUL algorithm provides high accuracy in underwater localization, which does not degrade with network size.
Due to adverse aqueous environments, non-negligible node mobility and large network scale, localization for large-scale mobile underwater sensor networks is very challenging. In this paper, by utilizing the predictable mobility patterns of underwater objects, we propose a scheme, called Scalable Localization scheme with mobility prediction (SLMP), for underwater sensor networks. In SLMP, localization is performed in a hierarchical way, and the whole localization process is divided into two parts: anchor node localization and ordinary node localization. During the localization process, every node predicts its future mobility pattern according to its past known location information, and it can estimate its future location based on its predicted mobility pattern. Anchor nodes with known locations in the network will control the whole localization process in order to balance the tradeoff between localization accuracy, localization coverage and communication cost. We conduct extensive simulations, and our results show that SLMP can greatly reduce localization communication cost while maintaining relatively high localization coverage and localization accuracy.
Since underwater acoustic (UWA) networks have the nature of long propagation delay, low bit rates and error-prone acoustic communication, protocols designed for underwater acoustic networks are significantly different from that of terrestrial radio networks. Limited by these nature of UWA channels, conventional medium access control (MAC) protocols of radio packet network ether have low efficiency or are not able to apply to underwater acoustic networks. It is necessary to develop an efficient MAC protocol for underwater acoustic networks. In this paper, a collision-free MAC protocol for UWA networks called Ordered Carrier Sense Multiple Access (Ordered CSMA) is proposed and analyzed. Ordered CSMA combines the concepts of round-robin scheduling and CSMA. In Ordered CSMA, each station transmits data frame in a fixed order. More specifically, each station transmits immediately after the data frame transmission of last station in the order, instead of waiting for a period of maximum propagation delay. To achieve this, each station is constantly sensing the carrier and listens to all received frames. Due to the characteristics of collision free and high channel utilization, Ordered CSMA shows a great MAC efficiency improvement in our simulations, compared to previous works.
An accurate localization scheme is essential to many underwater sensor applications. However, due to the persistent existence of uncertainties and measurement errors, an accurate localization is very difficult to achieve. To mitigate this problem, multi-iteration measurement and least squares scheme are often adopted in terrestrial applications to find a good estimate. But, in underwater applications the multi-iteration scheme is not practical due to high communication cost. Meanwhile, it has been observed that the errors in distance measurement often follow a certain pattern, which can be utilized to further improve on localization accuracy. In the paper, we analyze and utilize the measurement error distributions to better improve localization accuracy. An analytical model is developed for performance evaluation, along with extensive simulations. Both uniform error distribution and normal error distribution are considered in our research. Our results indicate that our proposed probabilistic localization method can significantly improve the localization accuracy over the commonly adopted least squares estimate (LSE) scheme.
In this paper, the underwater acoustic localization is given by probabilistic fingerprinting in eigenspace. The eigenspace of this study means the projection of PCA (principal components analyses). The goal is to predict the receiver location through wireless acoustic communication signals in underwater environments. It should be emphasized that our underwater localization is performed from wireless acoustic communication signals, but not from commercial localization systems. In other words, the hardware can be utilized for both communication and localization simultaneously in our experiments. Our underwater localization scheme is based on the fingerprinting of wireless acoustic communication signals in eigenspace of PCA (principal components analyses). It is based on fingerprinting and contains two stages, i.e., the off-line (i.e., training) and on-line (i.e., predicting) stages. In the off-line stage, there are some reference locations. At each reference location, acoustic communication signals at different frequencies are collected and sampled at discrete time points to constitute an acoustic-signal map. In the on-line (predicting) stage, acoustic communication signals at the unknown location are collected to constitute a signal vector. The problem becomes to predict the coordinate of the unknown location by comparing the signal vector with existing acoustic-signal maps. To reduce the complexity of acoustic-signal maps and overcome the severe fluctuation of measured data, all received signals are projected onto the eigenspace of PCA. Each component of the feature vector in eigenspace is assumed to be random Gaussian distribution. In addition, the components of the feature vector are assumed to be independent. The final probability that the signal vector occurred at an arbitrary reference location becomes the product of different Gaussian distribution functions. Such a probability is viewed as the weight for such a reference location. The unknown location can be a-
pproximated by the weighted summation of different reference locations.
In this paper, we present a novel approach based on pattern recognition to treat the underwater localization. The goal is to achieve underwater localization by the pattern matching algorithm. It should be noted that the reflected signals in underwater environments do not affect our location estimation. Therefore, the underwater localization in this study is straightforward and efficient by using the pattern matching algorithm. We exploit the maximum likelihood (ML) to perform our study. Initially, the underwater signals are collected by the sound receiver at some sampling locations. These signals are suitably processed by the ML models and are stored in database. The test location in real-time is estimated through the database. Experimental results show that good accuracy of positioning can be obtained by proposed schemes. The proposed localization schemes can be applied to many other applications in underwater environments.
For supporting location-aware computing in indoor environments, the location sensing/positioning system not only need to provide
objects’ precise location, but also should own such characteristics as: isotropy and convenience for portability. In this
paper, we present an indoor location sensing system, Cicada. This System is based on the TDOA (time difference of arrival)
between Radiofrequency and ultrasound to estimate distance, and adopts a technology integrating Slide Window Filter (SWF)
and Extended Kalman Filter (EKF) to calculate location. Consequently, it not only can determine the coordinate location within
5cm average deviation either for static objects or for mobile objects, but also owns a nearly omni-directional working area.
Moreover, it is able to run independently, mini and light so that it is very easy to be portable and even embedded into people’s
paraphernalia.
The results of indoor multipath propagation measurement using 10-ns, 1. 5-GHz, radarlike pulses are presented for a medium-size office building. The observed channel was very slowly time-varying, with the delay spread extending over a range up to about 200 ns and rms values of up to about 50 ns. The attenuation varied over a 60-dB dynamic range. A simple statistical multipath model of the indoor radio channel that fits the measurements well is presented. More importantly, the model appears to be extendable to other buildings. With this model, the received signal rays arrive in clusters. The rays have independent uniform phases, and independent Rayleigh amplitudes with variances that decay exponentially with cluster and ray delays. The clusters, and the rays within the cluster, form Poisson arrival processes with different, but fixed, rates.
In this paper, we study the localization problem in large-scale Underwater Wireless Sensor Networks (UWSNs). Unlike in the terrestrial positioning, the global positioning system (GPS) can not work efficiently underwater. The limited bandwidth, the severely impaired channel and the cost of underwater equipment all makes the localization problem very challenging. Most current localization schemes are not well suitable for deep underwater environment. We propose a hierarchical localization scheme to address the challenging problems. The new scheme mainly consists of four types of nodes, which are surface buoys, Detachable Elevator Transceivers (DETs), anchor nodes and ordinary nodes. Surface buoy is assumed to be equipped with GPS on the water surface. A DET is attached to a surface buoy and can rise and down to broadcast its position. The anchor nodes can compute their positions based on the position information from the DETs and the measurements of distance to the DETs. The hierarchical localization scheme is scalable, and can be used to make balances on the cost and localization accuracy. Initial simulation results show the advantages of our proposed scheme.
Path loss of an underwater acoustic communication channel de- pends not only on the transmission distance, but also on the sig- nal frequency. As a result, the useful bandwidth depends on the transmission distance, a feature that distinguishes an underwater acoustic system from a terrestrial radio one. This fact influences the design of an acoustic network: a greater information through- put is available if messages are relayed over multiple short hops instead of being transmitted directly over one long hop. We assesthe bandwidthdependencyon the distanceusing an an- alytical method that takes into account physical models of acoustic propagation loss and ambient noise. A simple, single-path time- invariant model is considered as a first step. To assess the fun- damental bandwidth limitation, we take an information-theoretic approach and define the bandwidth corresponding to optimal sig- nal energy allocation - one that maximizes the channel capacity subject to the constraint that the transmission power is finite. Nu- merical evaluation quantifies the bandwidth and the channel ca- pacity, as well as the transmission power needed to achieve a pre- specified SNR threshold, as functions of distance. These results lead to closed-form approximations, which may become useful tools in the design and analysis of acoustic networks.
A myriad of ocean processes affect life on the planet and are a source of intrigue to oceanographers and scientists. Understanding these processes and their interactions with currents requires collection of relevant data. A network of mobile platforms can be used to learn the correlation of processes in space and over time. To do this, data samples collected by nodes have to be annotated with location information. Given limited access to Global Positioning Systems underwater, collaborative self-localization schemes applied periodically are well-suited for this purpose. However, the specific nature of the underwater acoustic environment introduces significant error during network self-localization due to the combined effect of large latencies in communication and node mobility. We propose a method to account for these effects thus significantly improving the accuracy of position estimates.
We introduce and study the localization problem in large scale underwater acoustic sensor networks. Considering that depth information is typically available for underwater sensors, we transform the 3D underwater positioning problem into its two-dimensional counterpart via a projection technique. We then introduce a localization scheme specifically designed for large scale acoustic underwater sensor networks. The proposed localization scheme does not require time-synchronization in the network. This scheme relies on time-differences of arrival (TDoA) measured locally at a sensor to detect range differences from the sensor to three anchors that can mutually hear each other. We consider variations in the speed of sound and analyze the performance of the proposed scheme in terms of the number of localized nodes, location errors, and the number of reference nodes.
Underwater acoustic networks have the potential to support a large variety of applications, such as mining equipment and environmental monitoring. Although underwater acoustics has been studied for decades, underwater networking and protocol design is just beginning as a research field. One critical tool used for the design and testing of new protocols is a network simulator. For simulators to be useful tools, accurate models of both the channel and the modem need to be implemented. In this paper we present the design and implementation of our interface and channel model for underwater acoustic networks in the ns2 network simulator. We show that the models accurately predict the channel con- ditions and interface costs by comparing them to previously published numerical predictions of channel state. Finally, we present a case study of a protocol designed and simu- lated using our model. Our simulation code is open source and available for general use.
In this paper, we study the localization problem in large-scale underwater sensor networks. The adverse aqueous environments, the node mobility, and the large network scale all pose new challenges, and most current localization schemes are not applicable. We propose a hierarchical approach which divides the whole localization process into two sub-processes: anchor node localization and ordinary node localization. Many existing techniques can be used in the former. For the ordinary node localization process, we propose a distributed localization scheme which novelly integrates a 3-dimensional Euclidean distance estimation method with a recursive location estimation method. Simulation results show that our proposed solution can achieve high localization coverage with relatively small localization error and low communication overhead in large-scale 3-dimensional underwater sensor networks.
Underwater sensor networks (USN) are used for tough oceanographic missions where human operation is dangerous or impossible. In the common mobile USN architecture, sensor nodes freely float several meters below the surface and move with the force of currents. One of the significant challenges of the mobile USN is localization. In this paper, we compare the performance of three localization techniques; Dive and Rise Localization (DNRL), Proxy Localization (PL) and Large-Scale Localization (LSL). DNRL, PL and LSL are distributed, range-based localization schemes and they are suitable for large-scale, three dimensional, mobile USNs. Our simulations show that, DNRL and LSL can localize more than 90% of the underwater nodes with high accuracy while LSL has higher energy consumption and higher overhead than DNRL. The localization success and accuracy of PL is lower than the other techniques however it can localize underwater nodes faster when small number of beacons are employed.
We transform the 3D underwater sensor network (USN) localization problem into its 2D counterpart by employing sensor depth information and a simple projection technique. We first prove that a nondegenerative projection preserves network localizability. We then prove that given a network and a constant k, all of the geometric k-lateration localization methods are equivalent. Based on these results, we design a purely distributed bilateration localization scheme for 3D USNs termed as underwater sensor positioning (USP). Through extensive simulations, we show that USP has the following nice features: (1) improved localization capabilities over existing 3D methods, (2) low storage and computation requirements, (3) predictable and balanced communication overhead, and (4) robustness to errors from the underwater environment.
Introduction. Acoustical Oceanography. Propagation I. Observations and Physical Models. Propagation II. Mathematical Models (Part One). Propagation II. Mathematical Models (Part Two). Noise I. Observations and Physical Models. Noise II. Mathematical Models. Reverberation I. Observations and Physical Models. Reverberation II. Observations and Physical Models. Sonar Performance Models. Model Evaluation. Simulation.
The problem of underwater positioning is increasingly crucial due to the emerging importance of sub-sea activities. Knowledge of node location is essential for many applications for which sensor networks can be used. At the surface, positioning problems have been resolved by the extended use of GPS, which is straightforward and effective. Unfortunately, using GPS in the sub-sea environment is impossible and positioning requires the use of special systems. One of the major challenges in the underwater acoustic networks (UANs) area of research is the development of a networking protocol that can cope with the management of a dynamic sub-sea network. We propose a scheme to perform node discovery, using only one seed node (primary seed) in a known position. The discovery protocol can be divided into two parts: First, building up the relative co-ordinate system. Second, involving more remote nodes becoming seed nodes for further discoveries. Four different algorithms have been investigated; (i) Farthest/Farthest Algorithm, (ii) Farthest/Nearest Algorithm, (iii) Nearest/Farthest Algorithm and (iv) Nearest/Nearest Algorithm. We investigated the performances of random and fixed (grid) network topologies. Different locations of primary seed node were exercised and statistics for node discovery will be reported.
The problem of underwater positioning is increasingly crucial due to the emerging importance of sub-sea activities. Knowledge of node location is essential for many applications for which sensor networks can be used. At the surface, positioning problems have been resolved by the extended use of GPS, which is straightforward and effective. Unfortunately, using GPS in the sub-sea environment is impossible and positioning requires the use of special systems. One of the major challenges in the underwater acoustic networks (UANs) area of research is the development of a networking protocol that can cope with the management of a dynamic sub-sea network. We propose a scheme to perform node discovery, using only one seed node (primary seed) in a known position. The discovery protocol can be divided into two parts: First, building up the relative co-ordinate system. Second, involving more remote nodes becoming seed nodes for further discoveries. Four different algorithms have been investigated; (i) Farthest/Farthest Algorithm, (ii) Farthest/Nearest Algorithm, (iii) Nearest/Farthest Algorithm and (iv) Nearest/Nearest Algorithm. We investigated the performances of random network topologies. Different locations of primary seed node were exercised and statistics for node discovery will be reported.