Compact distributed target-tracking algorithm with binary sensors
Compact distributed target-tracking algorithm with binary sensors
- Author(s): X.-X. Cui ; Z. Fang ; P.-C. Zhou ; K. Liu
- DOI: 10.1049/iet-wss.2010.0105
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- Author(s): X.-X. Cui 1 ; Z. Fang 2 ; P.-C. Zhou 1 ; K. Liu 1
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View affiliations
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Affiliations:
1: New Star Research Institute of Applied Technology, Hefei, People's Republic of China
2: State Key Laboratory of Transducer Technology, Institute of Electronics, Chinese Academy of Sciences, Beijing, People's Republic of China
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Affiliations:
1: New Star Research Institute of Applied Technology, Hefei, People's Republic of China
- Source:
Volume 1, Issue 4,
December 2011,
p.
218 – 228
DOI: 10.1049/iet-wss.2010.0105 , Print ISSN 2043-6386, Online ISSN 2043-6394
A popular family of sensing systems work using binary sensors. In this study, the behaviour of binary sensing methods is investigated where the individual sensors only return information regarding the target's presence or absence within their own sensing range. In order to enhance their performance the authors propose a new compact distributed algorithm based on a triplet circle intersection principle where they take the central point of their common intersection arc among the sensor detection circles is considered as the target's position. It was shown that the new model can reduce the cost of resourcing as well as decreasing overhead communication traffics; it therefore fits very well with low-power sensor network applications. The experimental test-bench results verify the superior performance of our algorithm. Moreover, the results reveal improved performance criteria for conventional tracking evaluation of the average error and the root-mean-square error because of inherent measurement effectiveness of the target-tracking problem.
Inspec keywords: target tracking; mean square error methods; wireless sensor networks; telecommunication traffic
Other keywords:
Subjects: Signal processing and detection; Sensing devices and transducers; Interpolation and function approximation (numerical analysis)
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