A Heuristic Link Selection for Radio Frequency Tomography Based on BCS: Application

Xiao Xi Hao; Xue Mei Guo; Guo Li Wang

doi:10.4028/www.scientific.net/AMR.1049-1050.526

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 1049-1050A Heuristic Link Selection for Radio Frequency...

A Heuristic Link Selection for Radio Frequency Tomography Based on BCS: Application

Abstract:

Radio tomographic imaging as a coarse computational imaging method has attracted much attentions due to its potential applications in human surveillance. It utilizes the shadow fading characteristics of radio signals among wireless sensor network nodes to infer the targets' localization. The recovery process involves a large number of scanning links, which brings heavy burdens on node energy, communication routes and data storage. In general, there is a small number of targets and could be seen as a sparse signal compared with the original high-dimensional space. Hence, the key of scene recovery is the effective links selected. As the continuation of the previous part of work, this part of paper presents experimental studies indicate the proposed method is able to obtain better accuracy under the same number of measurements compared with the existed method. Numerical applications of proposed model are illustrated as well.

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Periodical:

Advanced Materials Research (Volumes 1049-1050)

Pages:

526-529

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.1049-1050.526

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Online since:

October 2014

Authors:

Xiao Xi Hao*, Xue Mei Guo, Guo Li Wang

Keywords:

Bayesian Compressive Sensing, Heuristic Link Selection, Radio Tomographic Imaging

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* - Corresponding Author

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