臺灣博碩士論文加值系統

精確蜂巢式網路定位對於商業與公共安全上的應用是一項重要且新興的技術。然而，大部份用於定位的無線通訊系統皆會受到嚴重的通道衰落、低訊雜比、多使用者干擾及多重路徑訊號干擾，將導致精確度嚴重下降。若能將定位技術提高至足夠精確度，在國防或民生上將能提供極大的益處。
各種不同的無線定位技術已經被廣泛的調查過，它能被分為三類：(1)以訊號強度為基礎的定位，其中有接訊號強度(RSS)量測法；(2)以時間為基礎的定位，其中有到達時間(TOA)或到達時間差(TDOA)的訊號量測法；(3)以角度為基礎的定位，其中有接收訊號的入射角度(AOA)量測法。三者皆有其好壞。訊號強度及到達時間技術需要最少三個定位基地台來進行二維的行動台定位，而且通常較AOA技術為精準；AOA技術在另一方面來說，最少只需要兩個基地台就可以定位估測。然而，當行動台距離基地台較遠時，一個小量的角度量測誤差將會造成大量的定位誤差。
本論文主要研究在蜂巢式網路架構下之行動台的定位技術。首先，我們提出基於TOA架構下之改進共變異數整形最小平方估測演算法，結合了對角化負載的技術以使共變異數整形最小平方演算法在非視距誤差下具有強健效能，但在高訊雜比環境下，其估測效能將不會比傳統的最小平方演算法要好。在高訊雜比環境中，我們也提出最小最大化均方誤差演算法來增加中至高SNR的定位精準度，在高訊雜比及矩陣 受到不確定性因素影響時，它能有效的最小化量測誤差的變異數。最後，利用蜂巢式網路對行動台進行定位估測時，基地台將能為行動台提供較準確的AOA量測訊息。採用將AOA與TOA相結合的混合定位法，模擬結果證實使用混合TOA/AOA定位法能取得比單純使用TOA定位擁有更佳的定位性能。

Accurate geolocation is an important and novel emerging technology for commercial and public safety applications. However, since most wireless communication systems used for position location may suffer from channel fading, low signal-to-noise ratios, multiuser interference, and multipath situations, which lead to a severe degradation of position accuracy. If positioning can achieve enough accuracy, the functions can be much deneficial to national defense and livelihood applications.
Various wireless location schemes which have been extensively investigated can be classified to three categories: (1) signal strength based location, where the received signal strength (RSS) incoming signals is measured and (2) time based location, where the time of arrival (TOA) or the time difference of arrival (TDOA) of the incoming signals is measured and (3) angle based location, where the angle of arrival (AOA) of the received signals is measured. Among categories have their own advantages and limitations. RSS and TOA schemes require at least three properly located base stations (BSs) for two dimensional (2D) mobile station (MS) location, and generally have better accuracy than AOA schemes; on the other hand, the AOA schemes require only two BSs minimum for a location estimate. However, a small error in the angle measurement will result in a large location error when the MS is far away from any BSs involved.
This thesis mainly investigates MS location techniques under the cellular network. First of all, we propose an improved covariance shaping least square (ICSLS) estimation algorithm based on the TOA scheme. In conjugation with a variable loading technique, we present an efficient technique to make the covariance shaping least square (CSLS) estimator has robust capabilities against the non-line of sight (NLOS) effects. But, if it is circumstance of large signal intensity environments, the estimation result would not be better than the traditional least square (LS) method. Secondly, we also present the minimax mean square error (MSE) estimator that attained better performance under sufficiently moderate to high signal-to-noise ratios (SNR). In high SNR and the matrix with uncertainties, the variance of the measurement error can be efficient minimized. Finally, in cellular networks, when TOA techniques are used to determine the position of MS, and BS can provide AOA imformation, we propose a hybrid TOA/AOA location scheme which combines TOA and AOA. Computer simulation results show that the hyprid TOA/AOA location schemes can improve the accuracy performance than the single TOA location schemes.

誌 謝 II
摘 要 III
ABSTRACT IV
目 錄 VI
圖 目 錄 VIII
表 目 錄 XI
符號說明和縮寫 XII
1. 緒論 1
1.1文獻探討 1
1.2研究動機與目的 2
1.3論文架構 5
2. 無線定位原理與探討 6
2.1無線定位技術 6
2.1.1細胞識別碼定位法 6
2.1.2接收訊號強度定位法 7
2.1.3到達時間定位法 9
2.1.4到達時間差定位法 11
2.1.5到達角度定位法 15
2.1.6混合到達時間與到達角度定位法 22
2.2定位精準度的度量與分析 23
2.2.1均方誤差MSE與CRLB 23
2.2.2圓誤差機率CEP 24
2.2.3幾何精度因素GDOP 25
2.2.4影響定位精準度的因素 25
3. 基於TOA架構的無線定位演算法 30
3.1最小平方演算法 30
3.2加權限制最小平方演算法 31
3.2.1 加權限制最小平方演算法 32
3.2.2電腦模擬與分析 37
3.3共變異數整形之最小平方演算法 45
3.3.1定位演算法推導 45
3.3.2改進的共變異數整形之最小平方演算法 51
3.3.3電腦模擬與分析 52
3.4基於TOA的最小最大化均方誤差演算法 57
3.4.1演算法推導 57
3.4.2電腦模擬與分析 62
4. 混合TOA/AOA架構的定位演算法 68
4.1混合TOA/AOA量測模型 69
4.2模擬結果 70
5. 討論與建議 77
參考文獻 78
論文發表 84
自 傳 85

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