| 李石荣,何富贵,朱雪梅.基于LS-SVM方向判别模型的WLAN室内定位方法[J].井冈山大学自然版,2019,40(3):43-49 |
| 基于LS-SVM方向判别模型的WLAN室内定位方法 |
| WLAN INDOOR POSITIONING METHOD BASED ON DIRECTIONAL DISCRIMINATION MODEL OFLS-SVM |
| 投稿时间：2018-10-28 修订日期：2019-02-05 |
| DOI：10.3969/j.issn.1674-8085.2019.03.008 |
| 中文关键词: 接收信号强度变化 室内定位 阴影衰落 最小二乘法支持向量机 方向判别模型 |
| 英文关键词: RSS indoor positioning shadow fading LS-SVM |
| 基金项目:国家自然科学基金青年项目（61702375）；皖西学院青年项目（WXZR201806） |
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| 中文摘要: |
| 为解决WLAN室内定位中信号在传播过程受人体遮挡产生阴影衰落而影响定位精度的问题，提出了一种最小二乘法支持向量机（LS-SVM）方向判别模型的WLAN室内定位方法。该方法主要分为两个部分：首先，充分利用人体在不同遮挡方向上产生阴影衰落的接收信号强度变化（RSS）特征信息，判定人体遮挡方向；然后，通过LS-SVM回归算法建立指纹点特征数据与位置之间的映射关系获取定位点位置结果。实验结果表明，与传统利用SVM的定位方法相比，提出的方向判别模型可解决人体遮挡产生的阴影衰落影响定位精度的问题，提高了定位的实用性和鲁棒性。 |
| 英文摘要: |
| In order to solve the problem of positioning accuracy error caused by body blocking in the process of WLAN indoor positioning, a WLAN indoor positioning method called Direction Discrimination Model (DDM) is proposed based on Least Squares Support Vector Machine (LS-SVM) algorithm.The method is mainly divided into two parts:First, the body's obstruction direction is determined with the information of the Received Signal Strength (RSS) changes in the shaded fading caused by the human body in different directions of obstruction; Then, the LS-SVMregression algorithm is used to establish the mapping relationship between the fingerprint point feature data and the location to obtain the positioning point location result.The experimental results show that the proposed direction discrimination model reduces the influence of shadow fading caused by human shadows on positioning accuracy and improves the practicability and robustness of positioning,compared with the traditional positioning method based on SVM. |
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