Localization For Underwater Sensor Networks Research Articles

Underwater Wireless Sensor Network-Based Localization Method under Mixed Line-of-Sight/Non-Line-of-Sight Conditions

Source localization in underwater sensor networks (UWSNs) presents complex challenges due to sensor nodes drift caused by ocean currents, non-line-of-sight (NLOS) propagation resulting from underwater multipath effects, and environmental noise. This paper proposes a practical and innovative algebraic solution based on the time difference of arrival (TDOA) for source localization in shallow seas. The proposed solution effectively addresses the issues arising from sensor position errors and multipath effects by incorporating the sea-surface reflection non-line-of-sight (SNLOS) link and optimizing the algorithm, thereby significantly improving positioning accuracy. The core concept of the method involves utilizing the weighted least squares algorithm to obtain an initial estimate of the source position, followed by direct estimation of the bias and subsequent refinement of the solution. In contrast to traditional closed-form solutions, this method avoids the introduction of intermediate parameters and directly handles the estimated bias from the previous step. Even when only considering the line-of-sight (LOS) link, the proposed solution achieves precise localization with a minimal number of sensors. Theoretical analysis demonstrates that the solution can achieve the Cramér–Rao lower bound (CRLB) accuracy under low noise conditions, and simulation results validate the superior performance of the proposed solution.

Broad-Learning-Based Localization for Underwater Sensor Networks With Stratification Compensation

Localization is an indispensable service for underwater sensor networks (USNs). Generally, the convex optimization method is adopted to solve the localization problem. However, the acoustic ray in water medium does not propagate along a straight line, which makes it difficult or impossible to transform the non-convex optimization problem into a convex optimization problem. This paper develops a broad learning (BL) based localization solution for USNs with isogradient sound speed profile. We first employ the ray tracing model to compensate the range bias caused by straight-line propagation. On the basis of collected range information from anchor nodes, the localization optimization problem is transformed into supervised, unsupervised and semisupervised learning frameworks. Correspondingly, three BL-based location estimators are developed to seek the position information of sensor nodes, where the incremental learning schemes are conducted for fast parameter tuning and remodeling. In addition, the Cramer-Rao Lower Bound (CRLB) of positioning error and the convergence to global optimality are both analysed. Finally, simulation and experiment results are presented to show the effectiveness of our approach. It is demonstrated that the proposed solution in this paper has the following nice features: 1) relax the dependence of convex relaxation over convex optimization-based location estimators; 2) reduce the training time and improve the localization efficiency over deep learning-based location estimators.

Hierarchical localization algorithm for sustainable ocean health in large-scale underwater wireless sensor networks

Being an extensive part of marine study, underwater localization has fascinated widespread consideration in both civil and military. The underwater sensor network localization should differ from existing terrestrial and recent localization techniques, owing to catastrophic ocean conditions, large-scale networks, and node drift, even in a static environment, along with the pretense of adverse challenges. To address these technical difficulties, we propose a hierarchical localization approach with anchor and ordinary nodes localized in two phases. First, anchor nodes are localized with the help of surface buoys, drifted on the water. Second, we propose a threshold that originates from the midpoint of the deployed anchor nodes for ordinary node localization. The nature of the threshold in the proposed technique enables the localization of all nodes in a network by demonstrating that the anchor node can cover 100% of the area after the nodes are deployed. Simulation results show that the proposed scheme gains high energy efficiency and precision, as well as wide localization coverage, which helps in ocean sustainability. In addition, the proposed technique is implemented in the Aqua-sim toolkit of NS-2 for the validation of the simulation results.

Privacy preserving solution for the asynchronous localization of underwater sensor networks

Location estimation of underwater sensor networks &#x0028 USNs &#x0029 has become a critical technology, due to its fundamental role in the sensing, communication and control of ocean volume. However, the asynchronous clock, security attack and mobility characteristics of underwater environment make localization much more challenging as compared with terrestrial sensor networks. This paper is concerned with a privacy-preserving asynchronous localization issue for USNs. Particularly, a hybrid network architecture that includes surface buoys, anchor nodes, active sensor nodes and ordinary sensor nodes is constructed. Then, an asynchronous localization protocol is provided, through which two privacy-preserving localization algorithms are designed to estimate the locations of active and ordinary sensor nodes. It is worth mentioning that, the proposed localization algorithms reveal disguised positions to the network, while they do not adopt any homomorphic encryption technique. More importantly, they can eliminate the effect of asynchronous clock, i.e., clock skew and offset. The performance analyses for the privacy-preserving asynchronous localization algorithms are also presented. Finally, simulation and experiment results reveal that the proposed localization approach can avoid the leakage of position information, while the location accuracy can be significantly enhanced as compared with the other works.

Robust and Cooperative Localization for Underwater Sensor Networks in the Existence of Malicious Anchors.

Precise and robust localization in three-dimensional underwater sensor networks is still an important research problem. This problem is particularly challenging if there are some malicious anchors among ordinary anchor nodes that will broadcast their locations falsely and deliberately. In this paper, we study how to self-localize large teams of underwater sensor nodes under the condition that some malicious anchor nodes mixed with ordinary anchors. Due to malicious characteristic of some deliberate anchor nodes, an iterative and cooperative 3D-localization algorithm for underwater sensor networks in the existence of malicious anchors is proposed in this paper. The proposed robust localization algorithm takes advantage of distributed reputation voting method within 1-Hop neighboring reference nodes to detect and eliminate malicious anchor nodes. Moreover, one kind of Minimum Mean Squared Error estimation based iterative localization method is applied to determine accurate location information. Additionally, we analyze and prove that our localization algorithm would have a bounded error when the number of malicious anchors is smaller than a certain threshold. Extensive simulation results are provided to demonstrate performance improvements comparing to traditional Minimum Mean Squared Error and Attack Resistant Minimum Mean Squared Error based localization methods in terms of localization accuracy and coverage ratio.

Feedback-Based Target Localization in Underwater Sensor Networks: A Multisensor Fusion Approach

This paper investigates the problem of target localization in underwater sensor networks, subjected to limited measurement range and accuracy. The localization process is mainly divided into two phases, i.e., distance estimation and position solving. In the first phase, some sensor nodes cannot acquire the direct distance measurements of target, due to the high-dynamic and strong-noise characteristics of underwater environment. Based on this, we formulate the distance measurement as a closed-loop control problem, and then a proportional-integral estimator is designed for sensors to acquire the distance information through indirect measurements. With the estimated distance information, a consensus-based unscented Kalman filtering (UKF) algorithm is proposed in the second phase to localize the target, where direct and indirect measurements are fused to reduce the influence of malicious data. Moreover, stability conditions are provided to show that the distance estimator can stabilize the closed-loop system, while the boundedness analyses are demonstrated to guarantee the localization accuracy. Finally, simulation results reveal that the proposed distance estimator can extend the measurement range of sensors by comparing with the single direct measurement. Meanwhile, the consensus-based UKF algorithm can effectively improve the localization accuracy.

Topology Control for Energy-Efficient Localization in Mobile Underwater Sensor Networks Using Stackelberg Game

The characteristics of mobile underwater sensor networks (UWSNs), such as low communication bandwidth, large propagation delay, and sparse deployment, pose challenging issues for successful localization of sensor nodes. In addition, sensor nodes in UWSNs are usually powered by batteries whose replacements introduce high cost and complexity. Thus, the critical problem in UWSNs is to enable each sensor node to find enough anchor nodes in order to localize itself, with minimum energy costs. In this paper, an energy-efficient localization algorithm (EELA) is proposed to analyze the decentralized interactions among sensor nodes and anchor nodes. A single-leader-multi-follower Stackelberg game is utilized to formulate the topology control problem of sensor nodes and anchor nodes by exploiting their available communication opportunities. In this game, the sensor node acts as a leader taking into account factors such as “two-hop” anchor nodes and energy consumption, while anchor nodes act as multiple followers, considering their ability to localize sensor nodes and their energy consumption. We prove that both players select best responses and reach a socially optimal Stackelberg-Nash Equilibrium. Simulation results demonstrate that the proposed EELA improves the performance of localization in UWSNs significantly, and in particular, the energy cost of sensor nodes. Compared to the baseline schemes, the energy consumption per node is about 48% lower in EELA, while providing a desirable localization coverage, under reasonable error, and delay.

Developing status and some cutting-edge issues of underwater sensor network localization technology

Owing to the complicated marine environment, a vast majority of terrestrial wireless sensor network technologies cannot be used directly in underwater sensor networks, which should be studied in combination with the special marine environment. In the last decade, there has been great progress in underwater sensor network localization technology. This paper summarizes the developing status first, and then puts forward some cutting-edge issues about underwater sensor network localization technology. Finally, this paper forecasts some practical questions expected to be solved in the next few years about underwater sensor network node localization technology.

Energy Harvesting Hybrid Acoustic-Optical Underwater Wireless Sensor Networks Localization.

Underwater wireless technologies demand to transmit at higher data rate for ocean exploration. Currently, large coverage is achieved by acoustic sensor networks with low data rate, high cost, high latency, high power consumption, and negative impact on marine mammals. Meanwhile, optical communication for underwater networks has the advantage of the higher data rate albeit for limited communication distances. Moreover, energy consumption is another major problem for underwater sensor networks, due to limited battery power and difficulty in replacing or recharging the battery of a sensor node. The ultimate solution to this problem is to add energy harvesting capability to the acoustic-optical sensor nodes. Localization of underwater sensor networks is of utmost importance because the data collected from underwater sensor nodes is useful only if the location of the nodes is known. Therefore, a novel localization technique for energy harvesting hybrid acoustic-optical underwater wireless sensor networks (AO-UWSNs) is proposed. AO-UWSN employs optical communication for higher data rate at a short transmission distance and employs acoustic communication for low data rate and long transmission distance. A hybrid received signal strength (RSS) based localization technique is proposed to localize the nodes in AO-UWSNs. The proposed technique combines the noisy RSS based measurements from acoustic communication and optical communication and estimates the final locations of acoustic-optical sensor nodes. A weighted multiple observations paradigm is proposed for hybrid estimated distances to suppress the noisy observations and give more importance to the accurate observations. Furthermore, the closed form solution for Cramer-Rao lower bound (CRLB) is derived for localization accuracy of the proposed technique.

Joint Synchronization and Localization for Underwater Sensor Networks Considering Stratification Effect

In underwater wireless sensor networks, time synchronization and localization are basic requirements in many applications. A joint synchronization and localization framework is expected to provide better accuracy. In this paper, we propose a unified framework to execute synchronization and localization simultaneously taking stratification effect into account. In this method, the stratification effect of underwater medium is modeled using a ray tracing approach. The maximum likelihood (ML) estimator is derived, which is shown to be highly nonlinear and nonconvex. Therefore, we employ the Gauss–Newton algorithm to solve the original nonconvex ML problem in an iterative manner. Furthermore, the Cramer–Rao lower bound for this problem is derived as a benchmark. Simulation results indicate that the proposed method outperforms the existing methods in both accuracy and energy efficiency.

Security based on Received Signal Strength in Localization for Underwater Sensor Networks

Underwater sensor networks are envisioned to enable a broad category of underwater applications such as pollution tracking, offshore exploration, and oil spilling. Such applications require precise location information as otherwise the sensed data might be meaningless. On the other hand, security critical issue as underwater sensor networks are typically deployed in harsh environments. Localization is one of the latest research subjects in UWSNs since many useful applying UWSNs, e.g., event detecting. Now day’s large number of localization methods arrived for UWSNs. However, few of them take place stability or security criteria. In purposed work taking up localization in underwater such that various wireless sensor nodes get localize to each other. RSS based localization technique used remove malicious nodes from the communication intermediate node list based on RSS threshold value. Purposed algorithm improves more throughput and less end to end delay without degrading energy dissipation at each node. The simulation is conducted in MATLAB and it suggests optimal result as comparison of end to end delay with and without malicious node.

Fault-resilient localization for underwater sensor networks

Localization is one of the critical issues in underwater sensor networks (UWSNs) on grounds of environmental characteristics, mobility of sensor nodes, and lack of global positioning system (GPS) services. Mobility modeling and fault tolerance with respect to underwater characteristics are extremely difficult. In this energy constraint network, an adaptive localization scheme with minimum communication and GPS support is required. We propose a fault-resilient localization scheme, which provides good localization accuracy with minimal communication overhead. To resile from an anchor node failure, a sensor node predicts its position by learning the mobility behavior of its neighbors using multiple linear regression. Therefore, the data dissemination process can continue even after an unexpected case of anchor node failure. We simulate the network and analyze the localization accuracy. Several experiments with different test cases are conducted to analyze the validity of the location prediction system. Experimental results show that the last 10 location information from three immediate neighbors are adequate for accurate prediction and the localization scheme is well suited for medium-range UWSNs.

Security and privacy in localization for underwater sensor networks

Underwater sensor networks are envisioned to enable a wide range of underwater applications such as pollution monitoring, offshore exploration, and oil/gas spill monitoring. Such applications require precise location information as otherwise the sensed data might be meaningless. On the other hand, security and privacy are critical issues as underwater sensor networks are typically deployed in harsh environments. Nevertheless, most underwater localization schemes are vulnerable to many attacks and suffer from potential privacy violations as they are designed for benign environments. However, a localization scheme that does not consider security and privacy could lead to serious consequences, especially in critical applications such as military monitoring. In this article, we discuss the security and privacy issues in underwater localization, and investigate the techniques that can provide security and preserve node privacy in underwater sensor networks.

A Novel Localization Scheme for Underwater 3D Acoustic Sensor Network

The localization of Underwater Sensor Networks(UWSNs) faces great challenges with the special underwater environment. In this page, the depth information is considered to use for localization. A novel localization scheme named U-iTPS is designed for UWSNs. Nodes do not rely on special hardware or time synchronization and depend on time difference of arrival (TDoA) signals measured locally to detect range differences from themselves to four anchors and then locate themselves in U-iTPS. U-iTPS is energy conservation because it does not rely on the node degree and the number of anchors, in which the node does not need communication each other and only listen to the beacon packets. After intensive experiment and theoretical analysis, U-iTPS show better performance such as low storage, computation and communication with other schemes, and also show good robustness in the underwater environment.