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Real-Time Tracking for Moving Target in WSN with Uncovered Holes

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Human Behavior Understanding in Networked Sensing

Abstract

In many practical scenarios, tracking moving targets in the field is very important but also challenging. To effectively track targets, a promising solution is to deploy a target-tracking wireless sensor network (WSN), which has attracted significant attention in the literature. In the past few years, most existing studies in this area have been focused on improving the accuracy and energy efficiency based on the assumption that the field is fully covered. However, this assumption may be invalid because sensors may fail due to various reasons. In this chapter, we tackle this important but largely overlooked problem. Specifically, we consider a WSN in which there exist uncovered areas, a.k.a. holes, in the field, due to the failures of sensors. We propose a novel signaling protocol where the main idea is to identify the hole and boundary nodes at the same time during the tracking course when the target moves into the hole. To quickly discover the boundary, we also propose to adopt directional antenna to achieve wireless communication. Simulation results show that the proposed approach can realize the real-time detection of a moving target when it runs into and out of the hole, and at the same time, consume much less energy than the omnidirectional antenna-based methods.

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Notes

  1. 1.

    Some prototypes of smart antenna that can switch modes can be found in [23, 30].

  2. 2.

    The gain is measured in decibels over either a dipole (dBd) or a theoretical construct called an isotropic radiator (dBi). The isotropic radiator is a spherical signal source that radiates equally well in all directions.

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Acknowledgments

This work has been supported by National Natural Science Foundation of China, NSFC 61170293.

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Correspondence to Huan Li .

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Li, H., Sun, Z., Lu, K. (2014). Real-Time Tracking for Moving Target in WSN with Uncovered Holes. In: Spagnolo, P., Mazzeo, P., Distante, C. (eds) Human Behavior Understanding in Networked Sensing. Springer, Cham. https://doi.org/10.1007/978-3-319-10807-0_4

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  • DOI: https://doi.org/10.1007/978-3-319-10807-0_4

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