隨著科技快速發展，利用無線通訊發展出定位系統已成為重要的研究之一，透過定位系統可以提供人們更便利的服務。許多位置感知服務相繼地被開發出來，而定位技術被認為是位置感知服務的核心部份，故定位技術顯得格外重要。在本論文中，我們的定位技術引用指紋特徵比對法的概念，應用在無線區域網路定位，此概念的流程就像是比對人類指紋一樣，共分為兩個階段，分別是收集訊號的離線階段和實際定位的線上階段。在離線階段，我們在不同參考位置接收訊號的強度值並儲存至資料庫，透過不同的演算法對資料庫做處理。在線上階段，我們將接收到的即時訊號與資料庫的訊號做特徵比對，利用最大似然法來估算出目前接收訊號者的所在位置。
此種定位流程是利用接收訊號的強度值，定位結果不會受到訊號的多重路徑影響，由於指紋特徵比對法需要事先收集資料庫，故本論文應用三種線性演算法對此資料庫進行前置處理，分別為局部保持投影法、邊界費雪分析法和最大散度差法，目的是節省事先收集訊號的時間和減少定位時的計算量，藉此提高定位的效率。實驗結果顯示，這些演算法成功被應用在處理資料庫並且得到準確的位置資訊，達到我們的期望目的與效果，本研究的定位流程，亦可應用在其他領域並且加以利用。

Along with rapid development of technology, using wireless communication to develop positioning system has become a very important research. With the positioning system, people can have more convenient services. There are many location-based services (LBS), which have been exploited sequentially, and the positioning method is considered to be the core of LBS. Therefore, the positioning method becomes especially important. In this thesis, our wireless local area network positioning system is based on the concept of fingerprinting approach. The procedure is the same as human fingerprint identification. The approach is divided into two parts including collecting signal in the off-line stage and estimating the current position in the on-line stage. In the off-line stage, we receive signals strength from each access point at different reference positions, and these signals are stored in the database. Next, the database is processed through different algorithms. In the on-line stage, we utilize maximum likelihood to contrast the real-time measured signals with the database, for estimating the receiver’s current position.
Because our procedure of positioning utilizes received signals strength, it will not be affected by multi-path reflection of received signals. In as much as the fingerprinting approach need to collect the database in advance, we apply three linear algorithms to process this database beforehand including locality preserving projects, marginal fisher analysis, and maximum scatter difference. The goal of these algorithms is to reduce the computation complexity and save a lot of time to gather the signals in advance to increase the efficiency of positioning. The simulation results show that these algorithms are successfully applied to deal with the measured signals and obtain accurate position information to reach our expecting effects. What’s more, the procedure of positioning in this thesis can also be applied to other aspects.

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