Three-Dimensional Underwater Target Tracking With Acoustic Sensor Networks

Isbitiren, G.; Akan, O.B.

doi:10.1109/tvt.2011.2163538

Cited by 125 publications

(64 citation statements)

References 12 publications

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“…As an emerging research interest, only a few works about target tracking in UWSNs can be found in the literature. In early work, a simple target tracking method utilizing only measurement information for 3D underwater is presented by Isbitiren et al [15]. Based on the time of arrival of the echoes from the target after transmitting acoustic pulses from the sensors, the ranges of the nodes to the target are determined, and trilateration is used to obtain the location of the target.…”

Section: Related Workmentioning

confidence: 99%

An Artificial Measurements-Based Adaptive Filter for Energy-Efficient Target Tracking via Underwater Wireless Sensor Networks

Chen

Zhang

Liu

et al. 2017

Sensors

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We study the problem of energy-efficient target tracking in underwater wireless sensor networks (UWSNs). Since sensors of UWSNs are battery-powered, it is impracticable to replace the batteries when exhausted. This means that the battery life affects the lifetime of the whole network. In order to extend the network lifetime, it is worth reducing the energy consumption on the premise of sufficient tracking accuracy. This paper proposes an energy-efficient filter that implements the tradeoff between communication cost and tracking accuracy. Under the distributed fusion framework, local sensors should not send their weak information to the fusion center if their measurement residuals are smaller than the pre-given threshold. In order to guarantee the target tracking accuracy, artificial measurements are generated to compensate for those unsent real measurements. Then, an adaptive scheme is derived to take full advantages of the artificial measurements-based filter in terms of energy-efficiency. Furthermore, a computationally efficient optimal sensor selection scheme is proposed to improve tracking accuracy on the premise of employing the same number of sensors. Simulation demonstrates that our scheme has superior advantages in the tradeoff between communication cost and tracking accuracy. It saves much energy while loosing little tracking accuracy or improves tracking performance with less additional energy cost.

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Section: Related Workmentioning

confidence: 99%

An Artificial Measurements-Based Adaptive Filter for Energy-Efficient Target Tracking via Underwater Wireless Sensor Networks

Chen

Zhang

Liu

et al. 2017

Sensors

View full text Add to dashboard Cite

show abstract

“…According to the computation algorithm to be implemented, we classify the computation algorithms into two categories as centralized techniques [15] and distributed methods [16]. The centralized technology performs the localization algorithm at the command center or sink node.…”

Section: Related Workmentioning

confidence: 99%

Two-Phase Time Synchronization-Free Localization Algorithm for Underwater Sensor Networks

Luo

Fan

2017

Preprint

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Underwater Sensor Networks (UWSNs) can enable a broad range of applications such as resource monitoring, disaster prevention, and navigation-assisted. It is especially relevant for sensor nodes location in UWSNs. Global Positioning System (GPS) is not suitable for using in UWSNs because of the underwater propagation problems. Hence some localization algorithms based on the precise time synchronization between sensor nodes have been proposed which are not feasible for UWSNs. In this paper, we propose a localization algorithm called Two-Phase Time Synchronization-Free Localization Algorithm (TP-TSFLA). TP-TSFLA contains two phases, namely, range-based estimation phase and range-free evaluation phase. In the first phase, we address a time synchronization-free localization scheme base on the Particle Swarm Optimization (PSO) algorithm to decrease the localization error. In the second phase, we propose a Circle-based Range-Free Localization Algorithm (CRFLA) to locate the unlocalized sensor nodes which cannot obtain the location information through the first phase. In the second phase, sensor nodes which are localized in the first phase act as the new anchor nodes to help realize localization. Hence in this algorithm, we use a small number of mobile beacons to help achieve location without any other anchor nodes. Besides, to improve the precision of the range-free method, an extension of CRFLA by designing a coordinate adjustment scheme is updated. The simulation results show that TP-TSFLA can achieve a relative high localization ratio without time synchronization.

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“…Hybrid networks for sensor scheduling are proposed to overcome communication issues by deploying powerful nodes distributed throughout the environment as "central" processors or cluster heads (CH) [6]. Each CH forms an independent cluster consisting of multiple sensor nodes.…”

Section: Introductionmentioning

confidence: 99%

Decentralized smart sensor scheduling for multiple target tracking for border surveillance

Hare

Gupta

Wilson

2015

2015 IEEE International Conference on Robotics and Automation (ICRA)

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Border surveillance requires regular patrolling to prevent intruders from crossing across, emphasizing the need for an automated network of sensing devices that is capable of detecting and estimating multiple moving targets. This paper proposes a fusion-driven decentralized sensor scheduling scheme that enables dynamic space-time clustering around multiple moving targets for energy-efficient track estimation. Each sensor node runs a Probabilistic Finite State Automata (PFSA) that controls the sensing and communication devices in an energy-efficient manner. This decentralized scheduling scheme is validated and compared with traditional scheduling schemes. The results show that the proposed scheme conserves energy while maintaining accurate track estimation.

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Three-Dimensional Underwater Target Tracking With Acoustic Sensor Networks

Cited by 125 publications

References 12 publications

An Artificial Measurements-Based Adaptive Filter for Energy-Efficient Target Tracking via Underwater Wireless Sensor Networks

An Artificial Measurements-Based Adaptive Filter for Energy-Efficient Target Tracking via Underwater Wireless Sensor Networks

Two-Phase Time Synchronization-Free Localization Algorithm for Underwater Sensor Networks

Decentralized smart sensor scheduling for multiple target tracking for border surveillance

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