臺灣博碩士論文加值系統

無線定位發展的主要動機源自緊急通訊，由於商業應用促進的激勵，藉由行動端點本身現在所處之位置提供以位置為基礎的服務予行動端點在近年來受到許多的關注。對無線定位技術的一項較大的挑戰是如何在所需的精確度和執行的複雜度上取得平衡。
本論文的第一部分，當利用到達時間量測時，我們致力於無線定位所受限的基本的問題之一，且在低的複雜度和允諾的精確度上，發展一個簡單的塑模以估測行動端點位置。這一個塑模使用幾何轉換的方法和單一傳播延遲量測。使用幾何轉換的方法其貢獻為，允許我們克服定位換手的問題，即GSM 網路的強迫換手或者UMTS網路的三方軟式換手。使用所提議的定位塑模，可保有最小程度的網路效能衝擊，且降低硬體和軟體改變的複雜性和要求。
本論文的第二部分，當利用場強量測時，我們致力於無線定位所受限的基本的問題之一。考慮結合取決環境的訊號傳播塑模來估測位置時，由於傳播參數的不確定性導致一個傳播塑模誤差，進而擴大了距離估測的誤差。為了消除不確定性的傳播參數，第一個貢獻是基於差分化方法，發展一個新的無線定位技術，稱為穩態訊號強度差。然而，從穩態訊號強度差定位技術的初步分析所得到的效能是偏低的，其原因為，在所估測的距離值和距離差值內，存在一個大的偏差。為了達成效能的提升，第二個貢獻是基於一個幾何限制條件，利用一個修正方法對所估測之距離差值修正偏差。最後的貢獻是，我們歸納所提的修正方法，且用已經修正的距離差提供一個新的架構對所估測之距離值修正偏差。因為已經修正的距離值和距離差值分別是以最小平方方式計算取得，故達成低的計算負擔和非反覆的解式。目前為止就我們最適當的認知，此類修正的建議對於以場強為基礎的定位技術而言，這是第一次。當在所估測的距離值和距離差值內，存在一個大的偏差，提議的錯誤修正方法顯示證明執行的成效令人滿意，且證明可相當大地改進定位精確度。

Inspired by promotion of commercial applications, support of location-based services to mobile terminals through their current location has been receiving a lot of attention in recent years even though emergency communications is the primary motivation for development of wireless location. A major challenge to wireless location technique is how to balance the implementation complexity and required accuracy.
In the first part of this dissertation, we address one of the fundamental problems in wireless location when using the ToA measurements and develop a simple model to estimate the mobile terminal location with low complexity and promising accuracy. The model employs the geometrical transformation method with single propagation delay measurement. The contribution is that the use of geometrical transformation allows us to overcome the location handover problem, i.e., a forcing handover in a GSM (global system for mobile) network or a three-way soft handover in a UMTS (universal mobile telecommunications system) network. By using the proposed location model, the impact on network performance is kept at the minimum level and the complexity and requirements for hardware and software changes are reduced.
In the second part of this dissertation, we address one of the fundamental problems in wireless location when using the SS (signal strength) measurements. The first contribution is to develop a novel wireless location technique based on a “differ- encing” way, called the SSSD (stationary signal-strength-difference), to remove the uncertainty propagation parameters when merging environment-dependent signal propagation model into the location estimation. This is due to the uncertainty in propagation parameters causes a propagation model error that enlarges error in the distance estimation. The performance gained from the preliminary analysis of SSSD location technique, however, is degraded as a result of the large bias error in the estimated distance and distance difference. To achieve the performance enhancement, the second contribution is to correct the bias error in the estimated distance difference by using a correction method based on a geometric constraint condition. With the corrected distance difference, the final contribution is that we generalized the work on correction method and provide a new framework to correct the error in the estimated distance. As the corrected distance and distance difference is derived by LS (least square) computation, respectively, low computation burden and non-iterative solutions were achieved. To the best of our knowledge thus far, this is first such proposal for a correction to the SS-based location technique. It is demonstrated that the proposed error correction method is shown to perform well when encountering the large error in the estimated distance and distance difference, and prove that the location accuracy can be improved considerably.

Acknowledgements ………………………………………………………….. i
Abstract …………………………………………………………………….... iii
List of Figures ……………………………………………………………….. ix
List of Tables ……………………………………………………………….... xi
Notation and Symbols ………………………………………………………. xiii
List of Acronyms …………………………………………………………….. xiv
1 Introduction ……………………………………………………………… 1
1.1 Overview of Wireless Location Technique . . . . . . . . . . . . . . . . . . . . 3
1.2 Mathematical Preparation for the Location Estimation Problem . . . 9
1.3 Dissertation Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
1.4 Organization of the Dissertation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
2 Performance Analysis for Wireless Location Uses Geometrical Transformation Method with Single Propagation Delay ……………...
23
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
2.2 Location Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
2.2.1 Methodology for the Geometrical Transformation . . . . . . . . 29
2.2.2 Consideration for the Error Conditions . . . . . . . . . . . . . . . . . 34
2.3 Location Estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
2.3.1 Circular Multilateration Algorithm . . . . . . . . . . . . . . . . . . . . 39
2.3.2 Hyperbolic Multilateration Algorithm . . . . . . . . . . . . . . . . 41
2.4 Results and Comparisons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
2.5 Chapter Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
3 Preliminary Performance for Wireless Location Uses SSSD Measures …………………………………………………………… 58
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
3.2 SSSD Location Technique . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
3.3 Location Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
3.4 Field Trial Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
3.4.1 Data Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
3.4.2 Result Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
3.5 Chapter Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
4 Performance Enhancement for Wireless Location Uses SSSD Measures …………………………………………………………… 86
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
4.1.1 Sources of Bias Error . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
4.1.2 Purpose of Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
4.2 Error Correction Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
4.2.1 Review of SSSD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
4.2.2 Bias Error Correction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
4.3 Performance Analysis: Hyperbolic Multilateration . . . . . . . . . . . . . . 103
4.3.1 Analysis of Bias Error . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
4.3.2 Location Accuracy for Urban and Rural Environments . . . . . 110
4.4 Performance Analysis: Circular Multilateration . . . . . . . . . . . . . . . . 118
4.4.1 Analysis of Bias Error . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
4.4.2 Location Accuracy for Urban Environments . . . . . . . . . . . . . 121
4.5 Chapter Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
5 Conclusions …………………………………………………………… 132
Appendices …………………………………………………………………… 137
A Residual Algorithm ……………………………………………………... 137
B Base Vector Algorithm ………………………………………………….. 141
Bibliography …………………………………………………………………. 146
Vita …………………………………………………………………………… 155

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