Research on indoor localization algorithm based on kernel principal component analysis
An indoor localization algorithm based on kernel principal component analysis (KPCA) was proposed.It applied KPCA to train the original location fingerprint (OLF) and extract the nonlinear feature of the OLF data at the offline stage,such that the information of all AP was more efficiently utilized....
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Journal on Communications
2017-01-01
|
| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2017018/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841539524417552384 |
|---|---|
| author | Hua-liang LI Zhi-hong QIAN Hong-liang TIAN |
| author_facet | Hua-liang LI Zhi-hong QIAN Hong-liang TIAN |
| author_sort | Hua-liang LI |
| collection | DOAJ |
| description | An indoor localization algorithm based on kernel principal component analysis (KPCA) was proposed.It applied KPCA to train the original location fingerprint (OLF) and extract the nonlinear feature of the OLF data at the offline stage,such that the information of all AP was more efficiently utilized.At the online stage,an improved weight k-nearest neighbor algorithm for positioning which could automatically choose neighbors was proposed.The experiments were carried out in a realistic WLAN environment.The results show that the algorithm outperforms the existing methods in terms of the mean error and localization accuracy.Moreover,it requires less times of RSS acquisition and AP number. |
| format | Article |
| id | doaj-art-9942c697b4124d4296a780d314dc51d9 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2017-01-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-9942c697b4124d4296a780d314dc51d92025-01-14T07:11:32ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2017-01-013815816759706900Research on indoor localization algorithm based on kernel principal component analysisHua-liang LIZhi-hong QIANHong-liang TIANAn indoor localization algorithm based on kernel principal component analysis (KPCA) was proposed.It applied KPCA to train the original location fingerprint (OLF) and extract the nonlinear feature of the OLF data at the offline stage,such that the information of all AP was more efficiently utilized.At the online stage,an improved weight k-nearest neighbor algorithm for positioning which could automatically choose neighbors was proposed.The experiments were carried out in a realistic WLAN environment.The results show that the algorithm outperforms the existing methods in terms of the mean error and localization accuracy.Moreover,it requires less times of RSS acquisition and AP number.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2017018/WLANindoor localizationRSSKPCA |
| spellingShingle | Hua-liang LI Zhi-hong QIAN Hong-liang TIAN Research on indoor localization algorithm based on kernel principal component analysis Tongxin xuebao WLAN indoor localization RSS KPCA |
| title | Research on indoor localization algorithm based on kernel principal component analysis |
| title_full | Research on indoor localization algorithm based on kernel principal component analysis |
| title_fullStr | Research on indoor localization algorithm based on kernel principal component analysis |
| title_full_unstemmed | Research on indoor localization algorithm based on kernel principal component analysis |
| title_short | Research on indoor localization algorithm based on kernel principal component analysis |
| title_sort | research on indoor localization algorithm based on kernel principal component analysis |
| topic | WLAN indoor localization RSS KPCA |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2017018/ |
| work_keys_str_mv | AT hualiangli researchonindoorlocalizationalgorithmbasedonkernelprincipalcomponentanalysis AT zhihongqian researchonindoorlocalizationalgorithmbasedonkernelprincipalcomponentanalysis AT hongliangtian researchonindoorlocalizationalgorithmbasedonkernelprincipalcomponentanalysis |