动态模糊匹配下的多元相似度定位算法

doi:10.19665/j.issn1001-2400.2021.04.004

西安电子科技大学学报 ›› 2021, Vol. 48 ›› Issue (4): 27-35.doi: 10.19665/j.issn1001-2400.2021.04.004

• 信息与通信工程&电子科学与技术 • 上一篇下一篇

动态模糊匹配下的多元相似度定位算法

秦宁宁^1,²(),吴忆松¹(),杨乐³()

1.江南大学轻工过程先进控制教育部重点实验室,江苏无锡 214122
2.南京航空航天大学电磁频谱空间认知动态系统工信部重点实验室,江苏南京 211106
3.坎特伯雷大学电气与计算机工程系,新西兰克赖斯特彻奇 8011

收稿日期:2020-05-20 出版日期:2021-08-30 发布日期:2021-08-31
作者简介:秦宁宁(1980—),女,教授,博士,E-mail: ningning801108@163.com|吴忆松(1995—),男,硕士,E-mail: wuyisong0919@163.com|杨乐(1979—),男,副教授,博士,E-mail: le.yang@canterbury.ac.nz
基金资助:
国家自然科学基金(61702228);国家自然科学基金(61803183);江苏省自然科学基金(BK20170198);江苏省自然科学基金(BK20180591);电磁频谱空间认知动态系统工信部重点实验室开放研究基金(KF20202104);江苏省博士后科研资助计划(1601012A);江苏省“六大人才高峰”项目(DZXX-026);中央高校基本科研业务费专项资金(JUSRP1805XNC)

Algorithm for multivariate similarity localization based on dynamic fuzzy matching

QIN Ningning^1,²(),WU Yisong¹(),YANG Le³()

1. Key Laboratory of Advanced Process Control for Light Industry of Ministry of Education,Jiangnan University,Wuxi 214122,China
2. Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space,Ministry of Industry and Information Technology,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China
3. Department of Electrical and Computer Engineering,University of Canterbury,Christchurch 8011,New Zealand

Received:2020-05-20 Online:2021-08-30 Published:2021-08-31

摘要/Abstract

摘要：

针对指纹定位中传统的区域划分方式无法保证区域匹配准确率的问题,提出了一种模糊匹配算法,使得匹配范围动态调整,提高定位速度的同时削弱区域划分带来匹配失准的缺陷。在位置计算阶段则结合多维相似度系数,并引入环境参量重新分配近邻点权重,克服环境和设备的变化对定位带来的不利影响,降低定位误差。经实测场景测试,在保障匹配准确率的前提下,所提算法相较于全局匹配减少60%以上的指纹匹配量,且通过实验验证,定位精度较现有的算法提高17%以上。

关键词: 室内定位, 指纹定位, 模糊匹配, 多元相似度

Abstract:

Considering the problem that the traditional area division method in fingerprint positioning cannot guarantee the accuracy of area matching,this paper proposes a fuzzy matching algorithm.Its matching range can be dynamically adjusted,and while improving the positioning speed,the algorithm can decrease the defects of mismatch caused by area division.In the position calculation stage,the algorithm uses multivariate similarity coefficients and introduces environmental parameters to redistribute the weights of neighboring points.This algorithm overcomes the adverse effects of fluctuation in environment and equipment,and reduces positioning errors.Tested by an actual scene,on the premise of ensuring the accuracy of matching,the proposed algorithm reduces the amount of fingerprint matching by more than 60% compared with global matching,and experiment verifies that the positioning accuracy is improved by more than 17%,compared with the existing algorithms.

Key words: indoor positioning, fingerprint positioning, fuzzy maching, multivariate similarity

中图分类号:

TN96

秦宁宁,吴忆松,杨乐. 动态模糊匹配下的多元相似度定位算法[J]. 西安电子科技大学学报, 2021, 48(4): 27-35.

QIN Ningning,WU Yisong,YANG Le. Algorithm for multivariate similarity localization based on dynamic fuzzy matching[J]. Journal of Xidian University, 2021, 48(4): 27-35.

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动态模糊匹配下的多元相似度定位算法

Algorithm for multivariate similarity localization based on dynamic fuzzy matching

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