Three-Dimensional Underwater Target Tracking With Acoustic Sensor Networks

The tracking of underwater targets represents a basic unit in underwater surveillance for offering effective search and rescue operations. However, the tracking of the target is a major constraint in finding the underwater target. This paper devises a model for underwater target tracking considering radar signals. Radar signals are subjected to the image reconstruction process to make them suitable for further processing. The gridding is the next step, which is utilized for generating the grids to focus on each region in a precise manner. The features like Ridgelet transform and Local Gabor XOR Pattern (LGXP) are produced. Data augmentation is the next process, which helps to reduce the size of data by performing resizing. At last, the tracking of targets is performed from each grid with a Deep neuro fuzzy network (DNFN). Here, DNFN training is performed with Exponential-Competitive Swarm Optimization (E-CSO), which is derived by integrating Exponential Weighted Moving Average (EWMA) and Competitive Swarm Optimization (CSO). The proposed E-CSO-based DNFN offered high efficiency with a maximal detection rate of 98.8%, minimal Mean square error of 0.012, and Mean Absolute Percentage Error (MAPE) of 17.883.

The underwater sensor network is currently a hot research field in academia and industry with many underwater applications, such as ocean monitoring, seismic monitoring, environment monitoring, and seabed exploration. Underwater target tracking is a critical component of ocean development. This paper studies the underwater target tracking problem of the wireless sensor network. The core technology of the target tracking algorithm is the filtering algorithm, which identifies the accuracy of the target tracking system. Nonlinear filtering is a hot issue in target tracking because feasible projects are mostly non-linear systems. The linearization method used in traditional Kalman filtering has serious shortcomings. Therefore, this paper presents the improved cubature Kalman filtering (ICKF) algorithm for underwater target tracking. There is uncertainty in the target movement, an adaptive forgetting factor is given into the cubature Kalman filtering algorithm to directly modify the error covariance to reduce the impact of uncertainties. Then, interactive multi-model technology is introduced to establish the IMMICKF algorithm with multiple states. Compared with other filtering algorithms, the new algorithm can effectively deal with non-linear target tracking problems and obtain better estimation accuracy. The numerical simulation is given to demonstrate the effectiveness of the IMMICKF algorithm.

Today, underwater target tracking using underwater wireless sensor networks (UWSNs) is an essential part in many military and non-military applications. Most of moving target tracking studies in UW...

Interest in underwater acoustic sensor networks (UW‐ASNs) has rapidly increased with the desire to control the large portion of the world covered by oceans. Energy efficiency is one of the major concerns in UW‐ASNs due to the limited energy budget of the underwater sensor nodes. In this paper, we tackle the problem of energy holes in UW‐ASNs while taking into consideration the unique characteristics of the underwater channel. We prove that we can evenly distribute the transmission load among sensor nodes provided that sensors adjust their communication range when they send or forward the periodically generated data. In particular, we propose a balanced routing strategy along with the associated deployment pattern that meticulously determines the load weight for each possible next hop that leads to fair energy consumption among all underwater sensors. Consequently, the energy holes problem is overcome, and hence, the network lifetime is improved. To the best of our knowledge, this is the first work that addresses the energy hole problem in UW‐ASNs. Copyright © 2016 John Wiley & Sons, Ltd.

Improving the energy efficiency of underwater acoustic sensor networks (UW-ASNs) is a crucial issue due to the reduced and nonrechargeable energy resource of the underwater sensor nodes. In this work, we address the energy sink hole problem in UW-ASNs while considering the unique and harsh characteristics of the underwater channel. Our goal is to determine the optimal deployment and routing settings that surmount the energy sink hole problem and hence maximize the network lifetime. We prove that sensors can evenly consume their initial battery power provided that first they adjust their transmission power when they transmit the route through traffic and second they are appropriately placed while deployed. Mainly, we propose a deployment scheme and the corresponding balanced routing strategy that lead to uniform energy consumption among all underwater sensors subject to a predefined reliability level at the sink. Specifically, we look for the optimal deployment settings especially in terms of nodes’ separation distances that help achieving uniform energy consumption in the network while satisfying the application requirement especially in terms of desired information reliability. Jointly, at the routing layer, we assume that each sensor is provided with the possibility of dynamically adjusting its transmission power up to a given number of levels N. To this goal, we mainly deal with two main cases: fixed and variable nodes separation distance. For the fixed case, we suppose that any two successive nodes in the network are equally spaced, and we strive for deriving the optimal distance as well as the optimal number of transmission power levels along with optimal load weight corresponding to every possible transmission power level for every sensor node. For the variable case, we deal with two subcases: first, we suppose that the distance separating successive nodes follows an arithmetic progression, and second, we assume that the distance separating successive nodes is following a geometric sequence. Note that for both cases, namely, fixed and variable, we succeed to determine the optimal distances separating successive nodes and the optimal number N of transmission power levels along with the corresponding optimal load weight that overcome the energy holes problem, and hence the network lifespan is maximized while respecting the desired reliability level.

The properties of underwater acoustic channel are quite different from those of terrestrial wireless sensor networks, which brings many challenges to design an efficient media access control (MAC) protocol for underwater acoustic sensor networks (UWASNs). In order to overcome the long propagation delay and the funneling effect of UWASNs, a MAC protocol, named path-oriented code assignment (POCA) CDMA MAC (POCA-CDMA-MAC) protocol, is proposed in the paper. In the proposed protocol, a round-robin method and the CDMA technology are used to make the sink receive packets from multiple neighbors at the same time. Unlike other CDMA-based protocols using the transmitter-oriented code assignment (TOCA) or the receiver-oriented code assignment (ROCA), the POCA is used in the CDMA technology. Since the number of the path is much less than the number of nodes, the length of the spreading code used in systems with POCA is greatly shorter than those of the spreading code used in systems with TOCA or ROCA. Simulation results show that compared to existing MAC protocols for UWASNs, the proposed MAC protocol achieves a higher throughput, and a lower end-to-end delay.

In the design of media access control (MAC) mechanism in underwater acoustic sensor networks (UASNs), due to the propagation characteristic of low-speed underwater acoustic signals, it is necessary to solve the spatial–temporal uncertainty problem. In order to avoid the multi-user access conflict in underwater networks, reduce the energy cost and improve the throughput and fairness across the network, a dynamic channel negotiation MAC mechanism based on spatial–temporal mapping of receiving queue (DCN-MAC) was proposed. DCN-MAC uses a duty cycle mechanism and implements a network management based on dynamic single node wake-up. The awakening node collects the request to send (RTS) and network status information in the network to solve the problem of space-temporal uncertainty and the highly dynamic needs of network access nodes and access services. The simulation results show that in different network scenarios, especially in those featuring high density and heavy network load, compared with the traditional underwater acoustic network MAC protocols, this protocol can effectively improve the network throughput and reduce the packet loss probability caused by multi-node conflict.

Attack Simulation Model and Channel Statistics in Underwater Acoustic Sensor Networks

The Underwater Acoustic Sensor Networks (UWASN) consists of sensors that are deployed underwater for gathering information for the unexplored parts of oceans or rivers. UWASN consists of variable number of floating and anchored sensors, sink and vehicles that are deployed over an area to be explored. The characteristics of UWASN are mainly node mobility for floating, capacity for data collection and recording and autonomous vehicles which are battery operable. The communication is possible among underwater devices through optical waves, radio waves, electromagnetic and acoustics. Out of these, acoustics communication is best suited as it can carry digital information through underwater channel and can travel to longer distances. The communication can be classified in two parts: Single and multi hoping. But in underwater we use multi-hop communication for sending data from end nodes to sink nodes. The various challenges to UWASN are limited bandwidth, multipath fading, limited battery, limited data capacity and delay in propagation. Hence, in this paper we have focussed on various issues and challenges in underwater wireless sensor networks for acoustic communications.

Constrained by the interior properties of underwater acoustic channels such as limited bandwidth, time-varying multipath propagation, and large propagation delay, the design of MAC protocols for underwater acoustic sensor networks (UWSNs) poses significant challenges. Existing MAC protocols for UWSNs exhibit very low performance in channel utilization, throughput and end-to-end delay, as well as energy consumption since 1) they are based on the conventional stop-and-wait (SW) transmission scheme, and 2) fewer has error-control mechanism at data link layer. In this paper, we assume that the UWSN has a multi-hop topology, where there exist a sink node and some common sensor nodes; all the nodes adopt Time Division Multiple Access (TDMA) to access channel. First, we classify all the nodes into different groups according to the numbers of hops between these nodes themselves and the sink node; the nodes belonging to different groups adopt TDMA frames with different starting time. We then propose a new MAC protocol by incorporating the multi-channel technique and the juggling-like stop-and-wait (JSW) transmission scheme, which is called the JM-MAC. Finally, simulation results are presented to highlight its good performance in terms of channel utilization, throughput and delay.

Underwater acoustic sensor networks are widely used for underwater information collection, environmental monitoring and assisted navigation. For energy limited underwater sensor nodes, the design of energy efficient protocols is a key problem in underwater acoustic sensor networks. In this paper, we propose two novel cluster formulation protocols for the Low Energy Adaptive Clustering Hierarchy Protocol (LEACH) in order to achieve further energy savings. The proposed cluster formulation protocols can significantly reduce the transmission collision probability during the cluster formulation process for underwater environments. Simulation results indicate that the proposed protocols outperform the standard LEACH protocol in terms of the network lifetime and the number of alive nodes. The proposed cluster formulation protocols can also be used with other modified LEACH protocols.

Ocean covers nearly 71% of our planet's surface, yet 95% of the ocean remains unexplored by human being, and wireless sensor networks are envisioned to perform monitoring tasks over the large portion of our world. However, deploying wireless sensor networks on the sea poses many challenges and for maritime surveillance security applications we may need to deploy sensors both on the sea surface and underwater for three-dimensional detection. In this paper, we propose a hybrid ocean sensor networks called Double-head maritime Sensor Networks (DSNs), which combine the advantages of wireless sensor networks and underwater acoustic sensor networks. By leveraging the unique characteristics of DSNs, we design a localization scheme LDSN which is consisted of two algorithms SML and FLA. We first use SML to localize moored anchor nodes as seed nodes. After the underwater sensor networks have been localized, the floating double-head nodes can figure out its instant position via FLA algorithm. We evaluate the scheme by simulations and the results show that the scheme can achieve a high localization accuracy.

Marine environmental monitoring, marine resource development, and maritime rights and interests protection had put great demands on underwater acoustic sensor networks. At the same time, it was found that the configuration and optimization of the underwater acoustic sensor network had important influence on the network performance and service quality in the uncertain marine environment. According to the characteristics of dynamic evolution of network topology and combining with different practical application scenarios, this article studied and discussed the model description, configuration mechanism, and optimization strategy of underwater acoustic sensor network. First, the classical underwater acoustic sensor network models were divided and discussed from three aspects: dimension, sensor types, and dynamic and static states. The characteristics of the six models are compared and analyzed. Second, according to the characteristics of six different models, the configuration mechanism and optimization strategy are discussed and classified. The configuration mechanism of models was studied from the aspects about determinism, self-adaptation, and group intelligence. The optimization strategy of models was discussed from the aspects about coverage, connectivity, energy consumption, time delay, data quality, and so on, and the relations and differences between different methods were compared and analyzed. Finally, the five future researches direction were expected, in order to provide a clear idea for further research in this field.

The underwater target tracking environment usually has the characteristics of strong nonlinearity and non-Gaussian. The target tracking problem usually uses the nonlinear filtering algorithm, which combines the nonlinear measurement model with the linear system dynamics. The primary goal of target tracking is to extract accurate information about the real-time state of the target from the noise nonlinear observation obtained by the sensor. A new Gaussian Hermitt Kalman particle filter algorithm (GHKF-PF) is used to improve the tracking accuracy of the particle filter algorithm (PF). GHKF-PF uses the GHKF sampling method to sample particles from the posterior distribution of the target, calculates the mean and covariance for each particle, and uses the mean and variance to guide sampling. In the simulation experiment, the uniform linear motion model of underwater 3D target in the environment of Gaussian mixture noise (GMN) is established, and the application of GHKF-PF algorithm in 3D space is realized, and the accuracy is higher than that of PF. In order to further verify the effectiveness of the algorithm, a six-dimensional uniform acceleration motion model is established and compared with the extended particle filter (EPF) algorithm and the unscented particle filter (UPF) algorithm. The simulation results show that the performance of the GHKF-PF algorithm is similar to that of the UPF algorithm and better than the EPF algorithm.

Like wireless sensor networks, lifetime of sensors is the main constraint for performance of underwater acoustic sensor networks (UASNs). Most previous works on UASNs did not consider dynamics of networks, i.e., as time goes by, in practice, part of sensors may be malfunctioned, deplete their battery power, or get lost due to violent underwater environment changes. Therefore, this paper considers a UASN in ocean and proposes a sleep scheduling scheme in which sensor nodes and autonomous underwater vehicles in this network can dynamically choose to sleep or work to adapt to the environmental change. The concerned problem is to dynamically determine a sufficient number of active nodes in the UASN at different times, such that the targets required to be detected are covered. A special static scenario of the problem has been shown to be NP-complete. Hence, this paper proposes an improved multi-population harmony search algorithm to solve this dynamic problem. By simulation, the proposed algorithm shows high performance in terms of extending network lifetime, robustness, and computing time.