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Tracking mobile targets using sensor networks is a challenging task because of the impacts of in-the-field factors such as environment noise, sensing irregularity, etc. This paper proposes a robust tracking framework using node sequences, an ordered list extracted from unreliable sensor readings. Instead of estimating each position point separately in a movement trace, the authors convert the original tracking problem to the problem of finding the shortest path in a graph, which is equivalent to optimal matching of a series of node sequences. In addition to the basic design, multidimensional smoothing is developed to enhance tracking accuracy.
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