基于Wifi与图像融合的室内定位算法

Zhongshuai Wang, Pheng Sokliep, Chengpei Xu, Jiayu Huang, Linfa Lu, Zhuo Shi
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引用次数: 5

摘要

本文提出了一种图像与WiFi多模式融合定位方法。WiFi指纹10度化是目前最常用的方法之一,但WiFi指纹定位存在多径非视距、信号波动、散射等现象,导致定位效果不稳定。此外,图像使用特征匹配来确定用户的位置,受环境影响较小,更稳定,成本更低。利用这两种算法的优点,提出了一种新的融合位置估计算法。在离线阶段,采集WiFi指纹和图像,建立指纹数据库,使用AlexNet对采集到的图像进行分割和匹配,确定整体范围。在线阶段,通过融合WiFi在区域内进行指纹位置匹配。经过实验,结果表明我们的方法可以有效降低WiFi指纹定位的波动,提高定位精度;可广泛用于为人们提供室内定位服务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Indoor Position Algorithm Based on the Fusion of Wifi and Image
In this paper, an image and WiFi multi-mode fusion localization method is proposed. WiFi fingerprint 10-calization is one of the most commonly used methods at present, but WiFi fingerprint localization has the phenomena of multipath and non-line-of-sight, signal fluctuation, scattering and so on, which leads to the unstable positioning effect. In addition, the image uses feature matching to determine the user’s location, which is less affected by the environment, more stable and lower cost. Taking advantage of the advantages of the two algorithms, a new fusion location estimation algorithm is proposed. In the offline phase, WiFi fingerprint and image are collected, fingerprint database is established, and the collected images are split and matched using AlexNet to determine the overall range. In the online stage, fingerprint location matching is carried out in the area through the fusion WiFi. After experiments, the results show that our method can effectively reduce the fluctuation of WiFi fingerprint positioning and improve the positioning accuracy; it can be widely used to provide indoor positioning services for people.
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