Fingerprint in the Air: Using the RSS Data for Uniqueness Identification
Fingerprint in the Air: Using the RSS Data for Uniqueness Identification
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DOI：
10.1109/icppw.2016.63
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发表时间：
2016-09
期刊：
影响因子：
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通讯作者：
Qiyue Li;Hailong Fan;Wei Sun;Jie Li;Xiaoyan Wang;Zhi Liu
中科院分区：
文献类型：
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作者：
Qiyue Li;Hailong Fan;Wei Sun;Jie Li;Xiaoyan Wang;Zhi Liu
近年来，室内定位、设备识别、无线考勤安全系统得到广泛应用。一直以来都有一个前提，即每个人只能携带一个无线设备，如今这个前提已经不成立了。为了检测唯一性识别问题，指纹、人脸或步态识别系统等生物辅助方法部署在入口附近，难以使用。本文使用可以收集并建模为时间序列的 RF RSS 指纹来研究此类问题。然后我们可以计算时间序列的相似度来判断唯一性识别问题。首先，提出了一种使用动态时间规整的朴素算法来简单地计算异步时间序列的相似度。然后提出一种改进算法，在保持鲁棒性的同时降低计算复杂度。仿真和实验结果表明，我们的算法能够以合理的成本完美地检测唯一性识别问题。
Indoor localization, device identification, and wireless attendance security systems are widely used in recent years. There is always a premise that each person can carry only one wireless device by himself, which is no longer valid nowadays. To detect the uniqueness identification problem, the bio-assisted methods such as fingerprint, face or gait recognition systems are deployed near the entrance which are difficult to use. This paper studies such problem using RF RSS fingerprints which can be collected and modeled as time series. Then we can calculate the similarity of the time series to judge the uniqueness identification problem. Firstly, a naive algorithm using dynamic time warping is presented to simply compute the similarity the asynchronous time series. Then an improved algorithm is proposed to reduce the computational complexity while keeping the robustness. Simulation and experiments results show that our algorithms can perfectly detect the uniqueness identification problem with a reasonable cost.