一种新的基于RSSI的人体室内定位方法:模糊离散倍增

2016 IEEE 6th International Conference on Consumer Electronics - Berlin (ICCE-Berlin) Pub Date : 2016-09-01 DOI:10.1109/ICCE-Berlin.2016.7684767

A. Baldini, L. Ciabattoni, R. Felicetti, F. Ferracuti, S. Longhi, A. Monteriù, A. Freddi

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引用次数: 6

摘要

本文提出了一种新的室内定位算法——模糊离散乘法(FDM)。顾名思义，它详细说明来自任意数量的发射器(锚节点)的数据，并返回未知接收器的估计位置。此外，采用两个级联模糊推理系统来评估从每个信标收集的数据的可靠性。该算法已经在不同的现实世界环境中进行了测试，其中锚节点是智能对象，未知节点是用户持有的任何要定位的智能对象。将本文算法的性能与三种已知的定位算法(信标密度范围为0.03 ~ 0.1 beacon/m2)进行了比较，并给出了结果。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A novel RSSI based approach for human indoor localization: The Fuzzy Discrete Multilateration

In this paper a new algorithm for indoor localization, namely Fuzzy Discrete Multilateration (FDM), is proposed. As the name suggests, it elaborates data from any number of transmitters (anchor nodes), and returns the estimated position of an unknown receiver. Furthermore, two cascade fuzzy inference systems are employed to evaluate the reliability of the data gathered from each beacon. The algorithm has been tested in different real world environments, where the anchor nodes are smart objects and the unknown node is any smart object held by the user to be localized. The performances of our algorithm has been compared with those of three well known localization algorithms (with a beacon density ranging from 0.03 to 0.1 beacon/m2) and results are shown.

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2016 IEEE 6th International Conference on Consumer Electronics - Berlin (ICCE-Berlin)

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