Survey of prediction algorithms for object tracking in wireless sensor networks

Mansur, Phiros; Sreedharan, Sasikumaran

doi:10.1109/iccic.2014.7238417

Cited by 4 publications

(1 citation statement)

References 19 publications

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“…In [ 11 ], the authors are focused on introducing the related knowledge of target tracking for sensor networks, rather than analyzing and comparing different target tracking algorithms. Some other review articles are only centered on one aspect of the tracking algorithms based on WSNs such as energy-efficiency [ 12 ], prediction algorithms [ 13 ], target recovery techniques [ 14 ], and security [ 15 ]. As the extension of traditional target tracking in the application of the underwater environment, underwater acoustic target tracking using UWSNs include all the aspect mentioned before.…”

Section: Related Surveys and Contributionsmentioning

confidence: 99%

Underwater Acoustic Target Tracking: A Review

Luo

Han

Fan

2018

Sensors

114

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Advances in acoustic technology and instrumentation now make it possible to explore marine resources. As a significant component of ocean exploration, underwater acoustic target tracking has aroused wide attention both in military and civil fields. Due to the complexity of the marine environment, numerous techniques have been proposed to obtain better tracking performance. In this paper, we survey over 100 papers ranging from innovative papers to the state-of-the-art in this field to present underwater tracking technologies. Not only the related knowledge of acoustic tracking instrument and tracking progress is clarified in detail, but also a novel taxonomy method is proposed. In this paper, algorithms for underwater acoustic target tracking are classified based on the methods used as: (1) instrument-assisted methods; (2) mode-based methods; (3) tracking optimization methods. These algorithms are compared and analyzed in the aspect of dimensions, numbers, and maneuvering of the tracking target, which is different from other survey papers. Meanwhile, challenges, countermeasures, and lessons learned are illustrated in this paper.

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