在信號源不足環境下手機的定位和軌跡追蹤演算法

Abstract

手機的定位和軌跡追蹤在近年來受到相當高的注意。手機和基地台之間傳送 的無線電訊號，在一般的網路定位估測機制下被廣泛地使用。此外，定位估測器 加上卡曼爾濾波(Kalman filtering)的技術，可同時獲得位置的估測並且追蹤手 機的軌跡。然而，這些已經存在的估測機制，在信號源不足(基地台數目小於三) 的情況下，會變得無法計算並預測手機的位置跟軌跡。在此篇論文中，有兩種可 預測的定位和軌跡追蹤演算法被提出來解決這個問題。預測定位追蹤機制 ( Predictive Location Tracking (PLT) scheme) 利用從卡曼爾濾波器(Kalman Filter)的預測訊息，提供給定位估測器當作是額外的訊號輸入，彌補訊號源不 足而無法計算的問題。更進一步，地理輔助的預測定位追蹤機制 (Geometric-assisted Predictive Location Tracking (GPLT) scheme)更加入 了幾何精度稀釋(Geometric Dilution of Precision (GDOP))的資訊到演算法 裡。採用所提出的地理輔助的預測定位追蹤(GPLT)機制在手機的定位追縱上都可 獲得更好的正確率，特別是當訊號源不足的時候。在此篇論文中有許多模擬的結 果來證明地理輔助的預測定位追蹤(GPLT)機制跟其他兩種網路定位追蹤機制比 較，可以獲得較高的正確率和穩定性。

Location estimation and tracking for the mobile devices have attracted a significant amount of attention in recent years. The network-based location estimation schemes have been widely adopted based on the radio signals between the mobile device and the base stations. The location estimators associated with the Kalman filtering techniques are exploited to both acquire location estimation and trajectory tracking for the mobile devices. However, most of the existing schemes become unapplicable for location tracking due to the deficiency of signal sources. In this thesis, two predictive location tracking algorithms are proposed to alleviate this problem. The Predictive Location Tracking (PLT) scheme utilizes the predictive information obtained from the Kalman filter in order to provide the additional signal inputs for the location estimator. Furthermore, the Geometric-assisted Predictive Location Tracking (GPLT) scheme incorporates the Geometric Dilution of Precision (GDOP) information into the algorithm design. Persistent accuracy for location tracking can be achieved by adopting the proposed GPLT scheme, especially with inadequate signal sources. Numerical results demonstrate that the GPLT algorithm can achieve better precision in comparison with other network-based location tracking schemes.