Environmental-adaptive RSS-based indoor localization
A novel two-step dictionary learning (DL) framework was proposed to dynamically adjust the overcomplete basis (a.k.a.dictionary) for matching the changes of the RSS measurements,and then the sparse solution can better represent location estimations.Moreover,a modified re-weighting l<sub&g...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2014-10-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.3969/j.issn.1000-436x.2014.10.024/ |
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| _version_ | 1841539742086201344 |
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| author | Ting-ting WANG Wei KE Chao SUN |
| author_facet | Ting-ting WANG Wei KE Chao SUN |
| author_sort | Ting-ting WANG |
| collection | DOAJ |
| description | A novel two-step dictionary learning (DL) framework was proposed to dynamically adjust the overcomplete basis (a.k.a.dictionary) for matching the changes of the RSS measurements,and then the sparse solution can better represent location estimations.Moreover,a modified re-weighting l<sub>1</sub>norm minimization algorithm was proposed to improve reconstruction performance for sparse signals.The effectiveness of the proposed scheme is demonstrated by experimental results where the locations of targets can be obtained from noisy signals,even if the number of targets is not known a priori. |
| format | Article |
| id | doaj-art-7bb83654337548ac9b16e49a1a1edfcb |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2014-10-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-7bb83654337548ac9b16e49a1a1edfcb2025-01-14T06:44:28ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2014-10-013521021759687121Environmental-adaptive RSS-based indoor localizationTing-ting WANGWei KEChao SUNA novel two-step dictionary learning (DL) framework was proposed to dynamically adjust the overcomplete basis (a.k.a.dictionary) for matching the changes of the RSS measurements,and then the sparse solution can better represent location estimations.Moreover,a modified re-weighting l<sub>1</sub>norm minimization algorithm was proposed to improve reconstruction performance for sparse signals.The effectiveness of the proposed scheme is demonstrated by experimental results where the locations of targets can be obtained from noisy signals,even if the number of targets is not known a priori.http://www.joconline.com.cn/zh/article/doi/10.3969/j.issn.1000-436x.2014.10.024/indoor localizationdictionary learning (DL)compressive sensing |
| spellingShingle | Ting-ting WANG Wei KE Chao SUN Environmental-adaptive RSS-based indoor localization Tongxin xuebao indoor localization dictionary learning (DL) compressive sensing |
| title | Environmental-adaptive RSS-based indoor localization |
| title_full | Environmental-adaptive RSS-based indoor localization |
| title_fullStr | Environmental-adaptive RSS-based indoor localization |
| title_full_unstemmed | Environmental-adaptive RSS-based indoor localization |
| title_short | Environmental-adaptive RSS-based indoor localization |
| title_sort | environmental adaptive rss based indoor localization |
| topic | indoor localization dictionary learning (DL) compressive sensing |
| url | http://www.joconline.com.cn/zh/article/doi/10.3969/j.issn.1000-436x.2014.10.024/ |
| work_keys_str_mv | AT tingtingwang environmentaladaptiverssbasedindoorlocalization AT weike environmentaladaptiverssbasedindoorlocalization AT chaosun environmentaladaptiverssbasedindoorlocalization |