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

Abstract

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

CLC Number:

TN96

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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Algorithm for multivariate similarity localization based on dynamic fuzzy matching

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