Abstract

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.

Highlights

  • More than 70% of the earth’s surface is covered by seas and oceans

  • Underwater wireless sensor networks (UWSNs) are the extending of wireless sensor networks (WSNs) which are applied to terrestrial environments [5,6,7]

  • This paper proposes an artificial measurements-based energy-efficient target tracking scheme in

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Summary

Introduction

More than 70% of the earth’s surface is covered by seas and oceans. Seas and oceans are mysterious and charismatic to human beings because of the huge amount of unexploited resources. We study the problem of accurately and energy-efficiently tracking a maneuvering target via UWSNs. UWSNs are the extending of wireless sensor networks (WSNs) which are applied to terrestrial environments [5,6,7]. In this paper, we improve the energy efficiency of target tracking by cutting down less helpful communications between local sensors and the fusion center. If the measurement residual is larger than the threshold, the fusion center receives information from the local sensor and works as usual. The current version extends the conference version by providing an adaptive method for determining proper criteria which are used to tell local sensors whether their measurements have enough value to be sent to the fusion center.

Related Work
Problem Formulation
System Model
Distributed Fusion Architectures
Measurement Residual-Based Sensor Scheduling
Artificial Measurement Model
Artificial Measurement Based Filter
Adaptive δ Determination
Optimal Sensor Group Selection
Simulation Scenario
Performance Comparison
Impacts of δ
Performance of Adaptive Filter
Performance of Sensor Group Selection
Conclusions

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