為未來無線區域網路下的指紋式室內定位系統打造智慧型的訊號地圖管理

近來幾年定位技術的發展非常熱門，並且被應用到許多領域中。GPS是其中最常被使用的技術，但在接收不到衛星訊號的地方無法使用GPS，像是室內的環境。為了滿足室內定位的需求，指紋式室內定位技術被用來取代GPS。指紋式室內定位技術是一種依照過去接收到訊號強度的經驗判斷目前使用者位置的技術。但是這種技術會有過去經驗與現實狀況不合的現象。在這篇論文中，我們提出一個方法，使用聚類演算法來分析資料庫，分析的目的是想要找出有共同特性的區域，並以此將空間劃分成數個區域，再藉由同樣數量感測器收集這些區域中的資料，最後用這些資料來校正定位的資料庫，使得資料庫中的內容可以當前的環境一致。最後，我們也進行實驗來評估校正前後精準度的差異。結果證明我們的方法可以有效的利用收集的資料進行資料庫更新，在數個不同的時段中，都有很好的表現。我們成功的藉由這些額外的感測器來修正資料庫的內容，而不用加裝特殊的儀器到伺服器端或是行動裝置上，也不去影響或是修改原本架設的基礎設施，像是Wi-Fi APs。這樣簡單的做法可以使我們方法更容易在現實環境中被實行。

關鍵字

無線區域網路；室內定位；指紋式定位技術；訊號地圖管理；聚類演算法

並列摘要

Localization technology is very popular and was applied to many areas in recent years. GPS is the most well-known technology, but GPS cannot well work in the indoor environment. The Fingerprinting-based technique, which is based on empirical signal strength measurements, is used to replace the GPS as indoor positioning, but however the actual environment may not be always consistent with empirical environment. In this thesis, we propose a method to analyze the database with clustering algorithm, and then find out the common characteristics in each region. The site will be separated into several clusters, and use a sniffer to collect the data in each cluster. As a result, we use these collected data to make the empirical data adapt to the current environment. We conducted experiments to evaluate the accuracy between before and after correction. The results show that our approach has a very good performance in several different times. This proved that we update database in an effective way, and make the localization more accurate.

並列關鍵字

WLAN ； indoor position ； Fingerprinting-based localization ； radio map management ； clustering algorithm

參考文獻

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[3] H. Lim, L. C. Kung , J. C. Hou , H. Luo, “Zero-conﬁguration indoor localization over IEEE 802.11 wireless infrastructure,” ACM Wireless Networks, Vol. 16, Issue 2, 2010.

[4] J. Yin, Q. Yang, L. M. Ni, “Learning Adaptive Temporal Radio Maps for Signal-Strength-Based Location Estimation,” IEEE Transactions on Mobile Computing, Vol. 7, Issue 7, on page: 869 – 883, 2008.

[5] P. Bahl, V. N. Padmanabhan, “RADAR: An In-Building RF-Based User Location and Tracking System,” Proceedings of IEEE INFOCOM, Vol. 2, on page: 775 – 784, 2000.

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為未來無線區域網路下的指紋式室內定位系統打造智慧型的訊號地圖管理

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