基于室内指纹定位的优化算法  

Optimization Algorithm Based on Indoor Fingerprint Positioning

作　　者：甘露 杨君[1,2] 郭娅婷[1,2] GAN Lu;YANG Jun;GUO Yating(Engineering Research Center of Metallurgical Automation and Measurement Technology,Ministry of Education,Wuhan University of Science and Technology,Wuhan,430081,China;School of Information Science and Engineering,Wuhan University of Science and Technology,Wuhan,430081,China)

机构地区：[1]武汉科技大学冶金自动化检测技术教育部工程研究中心,武汉430081 [2]武汉科技大学信息科学与工程学院,武汉430081

出　　处：《数据采集与处理》2020年第5期903-909,共7页Journal of Data Acquisition and Processing

基　　金：国家自然科学基金(61701354)资助项目。

摘　　要：针对室内环境中WiFi信号强度易受外界干扰,其不稳定性使得在指纹数据库中进行匹配时准确性较低,定位精度不高的问题,提出一种基于室内指纹定位的优化算法。该算法分别对指纹数据库和匹配算法进行优化。数据库优化采用限幅和滑动平均滤波进行预处理,并根据室内环境分配采样点所属区域编号,构建多维指纹数据库;匹配算法优化首先根据支持向量机(Support vector machine,SVM)对待定位点分类,获取其对应的区域编号,再将欧氏距离、曼哈顿距离和切比雪夫距离三者结合得到位置估计。最后,结合行人航位推算(Pedestrian dead reckoning,PDR)算法将得到的步长与航向角一同进行粒子滤波(Particle filtering,PF)实现定位。实验表明:本文的算法将定位精度提高了13.92%。For indoor environment,the WiFi signal strength is susceptible to external interference.Due to its instability,the accuracy of matching in the fingerprint database is low and the positioning accuracy is not high.An optimization algorithm based on indoor fingerprint positioning is proposed.This algorithm optimizes the fingerprint database and matching algorithm.Database optimization uses limiting and moving average filtering for pre-processing.According to the indoor environment,assign the ID of the area to which the sampling point belongs to build a multidimensional fingerprint database.The matching algorithm is optimized to classify the points to be located according to the support vector machine(SVM)and obtain the corresponding area ids.The Euclidean distance,Manhattan distance and Chebyshev distance are combined to obtain a position estimate.Finally,combined with the pedestrian dead reckoning(PDR)algorithm,the obtained step size and heading angle are subjected to particle filtering to achieve positioning.The proposed algorithm improves the positioning accuracy by 13.92%.

关 键 词：室内定位 指纹定位算法 曼哈顿距离 切比雪夫距离 粒子滤波 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]