室內幾何定位演算法之效能評估與改善

Performance Analysis and Improvement of Geometric Location Estimation Algorithms for Indoor Environments

林洋科(Yang-Ke Lin)

指導教授 ： 邱奕世

中原大學/電機資訊學院/通訊工程碩士學位學程/碩士(2019年)

https://doi.org/10.6840/cycu201900451

摘要

隨著無線感測網路以及物聯網技術的蓬勃發展，使得以定位為基礎的適地性服務 (LBS，Location-Based Service) 越來越受到廣泛的關注，因而帶動了定位技術的發展。定位技術依環境可分為戶外以及室內的定位系統，戶外環境定位技術的發展已經十分成熟，例如全球定位系統 (GPS，Global Positioning System)，但因為GPS的訊號無法穿透大部分的建築物，所以無法適用於室內環境。隨著室內環境定位應用需求的增加，已有各式各樣的應用於生活中出現，例如大眾運輸、商業宣傳以及緊急救援等等。常用於室內定位系統的機制有紅外線、超音波、藍芽以及Wi-Fi等技術。定位系統依照定位機制取得資料的方式，可分成 Time of Arrival (TOA)、 Angle of Arrival (AOA)、 Time Difference of Arrival (TDOA) 以及 Received Signal Strength (RSS) 等技術。目前有許多不同的定位方法，本論文探討以及評估數種三角幾何定位演算法之效能。此篇論文是模擬在室內環境中接收到 Wi-Fi 的訊號強度，並將訊號強度依照電波傳遞模型轉換成距離，接著再依照傳遞距離以及三角定位的演算法計算移動端的位置。使用電波傳遞模型的三角定位方法會造成有些估測位置不合理的情形，為了減緩不合理的估測結果，本論文使用卡爾曼濾波 (KF, Kalman Filter) 的追蹤演算法提高定位的準確度，使估測的位置可以更接近真實移動的路徑，進而改善定位的準確度。

關鍵字

室內定位系統 (IPS) ； 卡爾曼濾波 (KF) ； 定位追蹤 ； 三角定位 ； 無線通信

並列摘要

Due to the rapid development of wireless sensor network and internet of things (IoT) technologies, the applications of location-based services (LBSs) are becoming more and more popular, and they have led to the development of localization technologies. According to the environments, positioning systems can be divided into outdoor and indoor localization technologies. The developments of outdoor environmental localization technologies have been very mature, such as global positioning system (GPS). However, the GPS signals can not penetrate most buildings. As a result, it is not suitable for indoor environments. In addition, many localization technologies have been used for indoor positioning systems, such as ultrasonic, infrared, Bluetooth, Wi-Fi, and so on. In terms of the localization mechanisms, the positioning systems can be divided into the time of arrival (TOA), angle of arrival (AOA), time difference of arrival (TDOA), and received signal strengths (RSSs). This thesis evaluates the performances of several kinds of geometric location estimation algorithms. In terms of the Wi-Fi signals in an indoor environment, the trilateration approaches based on the signal propagation model and the collection of RSSs are considered as distance functions to determine user’s location. The localization approach using empirical path loss model related to the environment will cause some unreasonable estimated location. In order to mitigate the unreasonable results, this thesis uses Kalman filter (KF) tracking approach to improve the accuracy of estimated locations. And then, the estimated locations are closer to the real walking path.

並列關鍵字

indoor positioning system ； Kalman filter ； location tracking ； trilateration ； wireless

參考文獻

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