以移動行為追蹤為輔助之室內無線定位

Abstract

現今存在很多基於室內位置的服務，而大多數基於室內位置的服務都倚賴區域網路內的無線接取點與行動裝置端點間的無線訊號傳輸來達成。 由於在效能與準確度還有進步的空間，以Ｗi-Fi為基礎的定位技術還是一項熱門的研究領域。在此篇論文中，我們著重在改善利用定位裝置所接收到附近的無線接取點之訊號強度(RSS)以定位裝置位置這個議題上。藉由觀察訊號強度變化與裝置移動行為的關係，我們提出了單純使用Wi-Fi訊號強度的室內定位與追蹤系統。所提出之定位系統利用粒子濾波器(particle filter)與訊號強度變化來預測定為目標之移動行為與位置。我們將所提出之定位與追中系統以Android實作並展示其高定位精準度，同使也使用MATLAB軟體來更深入的評估與分析所提出之系統之效能。

Many indoor location-based services have been proposed, and most of the localization approaches rely on the processing of radio-frequency signals transmitted among the wireless access points of local area networks and the mobile terminals. Wi-Fi based localization is still very active research field since improved performance concerning accuracy of the position estimation are still required. In this work, we focus on the problem of localizing a device by considering the Received Signal Strength (RSS) of signals the device receives from the wireless access points around it. By observing the variety of RSS values during the motion of a pedestrian, I proposed an indoor localization and tracking system were purely exploiting Wi-Fi RSS. The particle filter is applied to our system to estimate smartphone user's location and movement. Experiments and simulations were conducted in Android device to illustrate that our approach can achieve high accuracy localization. We used MATLAB to evaluate performance and provide more insights of the proposed approach.