Comprehensive analysis of distance and similarity measures for Wi-Fi fingerprinting indoor positioning systems

作者：

Highlights：

• We introduce a study in depth of distance/similarity measures for indoor location.

• Alternative measures provide better results than commonly used Euclidean distance.

• Choosing an appropriate non-linear representation is crucial for intensity values.

• Very low intensity values are representative and they should not be filtered.

• All the experiments are validated with a public database, so they are reproducible.

摘要

•We introduce a study in depth of distance/similarity measures for indoor location.•Alternative measures provide better results than commonly used Euclidean distance.•Choosing an appropriate non-linear representation is crucial for intensity values.•Very low intensity values are representative and they should not be filtered.•All the experiments are validated with a public database, so they are reproducible.

论文关键词：Indoor localization,Distance measures,Similarity measures,k-NN,Wi-Fi fingerprint

论文评审过程：Received 18 December 2014, Revised 6 August 2015, Accepted 10 August 2015, Available online 22 August 2015, Version of Record 5 September 2015.

论文官网地址：https://doi.org/10.1016/j.eswa.2015.08.013