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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Genming Ding Jinbao Zhang Lingwen Zhang Zhenhui Tan |
| Copyright Year | 2013 |
| Description | Author affiliation: Inst. of Broadband Wireless Mobile Commun., Beijing Jiaotong Univ., Beijing, China (Genming Ding; Lingwen Zhang; Zhenhui Tan) || EMC Lab., Beijing Jiaotong Univ., Beijing, China (Jinbao Zhang) |
| Abstract | In recent years, indoor localization technique is anticipated to play an increasingly important role in our society. In general, the indoor localization techniques include trilateral, triangulation and fingerprinting localization. As an important alternative, fingerprinting localization techniques are extensively studied and applied in the existing localization systems. This paper presents an overview of the fingerprinting localization system based on the received signal strength (RSS) in indoor wireless LAN (WLAN) environments. In particular, we describe the structure of localization system and then analyze the challenges that most existing research works try to deal with. Corresponding solutions and several pattern matching algorithms are also presented. Furthermore, we demonstrate a comparative study of existing fingerprinting localization systems and address the possible directions of future research in indoor localization techniques. |
| Sponsorship | IEEE Beijing Sect. |
| Starting Page | 160 |
| Ending Page | 164 |
| File Size | 162802 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781467360777 |
| e-ISBN | 9781467360791 |
| DOI | 10.1109/MAPE.2013.6689973 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-10-29 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Wireless LAN Accuracy Databases RSS fingerprinting localization Estimation Fingerprint recognition indoor environments WLAN Complexity theory Pattern matching |
| Content Type | Text |
| Resource Type | Article |
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