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FALE

2015; Association for Computing Machinery; Volume: 45; Issue: 4 Linguagem: Inglês

10.1145/2829988.2790020

1943-5819

Liqiong Chang, Xiaojiang Chen, Dingyi Fang, Ju Wang, Tianzhang Xing, Chen Liu, Zhanyong Tang,

Underwater Vehicles and Communication Systems

Many emerging applications and the ubiquitous wireless signals have accelerated the development of Device Free localization (DFL) techniques, which can localize objects without the need to carry any wireless devices. Most traditional DFL methods have a main drawback that as the pre-obtained Received Signal Strength (RSS) measurements (i.e., fingerprint) in one area cannot be directly applied to the new area for localization, and the calibration process of each area will result in the human effort exhausting problem. In this paper, we propose FALE, a fine-grained transferring DFL method that can adaptively work in different areas with little human effort and low energy consumption. FALE employs a rigorously designed transferring function to transfer the fingerprint into a projected space, and reuse it across different areas, thus greatly reduce the human effort. On the other hand, FALE can reduce the data volume and energy consumption by taking advantage of the compressive sensing (CS) theory. Extensive real-word experimental results also illustrate the effectiveness of FALE.