一個基於行動網路訊號為基礎的綠能定位演算法—以校園導覽系統為例

Abstract

適地性服務(Location-based Service, LBS)的優劣取決於智慧型手機中定位演算法的精確度與電力的消耗程度。以手機基地台訊號為基礎，利用接收來自行動網路的訊號強度(received signal strength, RSS)的定位演算法相較於傳統的定位方法(如:Cell-ID定位法)是較精準的。在這篇論文中，我們提出一個新的定位演算法，是基於指紋定位演算法( Fingerprint Positioning Algorithm, FPA)，利用接收來自行動手機端透過網路傳送過來的RSS資訊來做定位並且提供LBS給使用者做參考。在實驗中是以校園導覽系統(Campus Guidance System, CGS)為例子，我們的定位結果與來自全球定位系統(Global Position System, GPS)所接受到的真實數據做了比較。其結果是利用FPA所預測出來的定位位置與真實位置的平均誤差值大約是在9.92公尺。而在電力消耗方面，使用GPS來做定位的電力消耗速度是利用FPA做定位的 21.52倍。因此，利用FPA的定位方法是可以稱為一個綠能的定位演算法，適合應用在戶外導覽的環境中，而且他可以被應用於LBS。

The accuracy and power consumption of the positioning algorithm built into smart phone determine the performance of location-based service (LBS). The cellular-based location determination using received signal strength (RSS) from cellular networks is much more accurate than traditional methods (e.g. Cell-ID position method). In this thesis, we propose a new position algorithm which employs the fingerprint positioning algorithm (FPA) using RSS from mobile station/user equipment through cellular networks and LBS for user reference. In experiments we use campus guidance system (CGS) as an example. We compare the estimated positioning information with the real information from global position system (GPS) receiver. The results show that the error of location estimation using FPA is about 9.92 meters. As to power consumption, the cost per sample of GPS is 21.52 times of that of FPA. Consequently, the FPA exerts itself as a green positioning algorithm, and it’s suitable for outdoor environment and thus can be used to support LBS.