基于GAWK-means的地铁车站指纹定位方法

doi:10.16180/j.cnki.issn1007-7820.2022.02.006

Abstract

Abstract:

In order to solve the problem of low matching efficiency and poor positioning accuracy when using iBeacon technology for fingerprint location in urban rail transit stations, a metro station fingerprint location method based on GAWK-means is proposed in this study. In the offline stage, the K-means Euclidean distance weight is optimized according to the discreteness of the fingerprint data to better reflect the intra-class similarity. Then, the improved K-means is combined with the genetic algorithm to optimize the clustering results to reduce the clustering results from falling into the local optimum. In the online stage, the K-nearest neighbor method is used to match the signal vector with the nearest sub-fingerprint database to get the location result, and the overall performance of the method is evaluated by the average positioning error. The experimental results show that the average positioning error of the GAWK-means algorithm is 1.52 m in the offline phase of the subway station. Compared with the un-clustered and traditional K-means clustering, the positioning error of the proposed method is reduced by more than 0.41 m.

Key words: metro station, iBeacon technology, fingerprint location, genetic algorithm, K-means clustering, Euclidean distance, K-nearest neighbor method, GAWK-means

CLC Number:

TN92

JIN Xiao,WU Fei,YAN Song,LU Wenxia,ZHANG Zhongyi. Fingerprint Location Method of Metro Station Based on GAWK-means[J].Electronic Science and Technology, 2022, 35(2): 34-39.

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References 18

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部分采样点坐标/m	部分采样点处的部分RSS值/dB·m
(0.9,65.7)	-83	-85	-68	-66	-68	-64	-65	-67	-70
(0.9,67.5)	-74	-76	-66	-67	-67	-60	-56	-68	-72
(0.9,69.3)	-73	-72	-72	-64	-69	-58	-57	-68	-76
(0.9,71.1)	-73	-71	-68	-99	-68	-60	-62	-72	-73
(0.9,72.9)	-71	-67	-67	-68	-64	-60	-68	-68	-79
(0.9,74.7)	-72	-71	-62	-66	-58	-69	-71	-73	-76
(0.9,76.5)	-70	-66	-62	-67	-55	-65	-71	-71	-76

聚类方法	匹配定位时间/s	平均定位误差/m
未聚类	0.047 2	2.370 5
传统K-means	0.017 9	1.932 5
本文方法	0.014 3	1.520 8

Fingerprint Location Method of Metro Station Based on GAWK-means

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