本篇論文主旨是在研究超寬頻系統(Ultra-WideBand radio)於稠密的多重路徑環境裡，估測接收訊號的第一個抵達路徑，所使用的估測訊號抵達時間演算法是以廣義最大概似(Generalized Maximum Likelihood; GML)演算法為主體，但因為廣義最大概似演算法的運算需要很久的時間甚至無法實現，所以一個化簡的架構被提出研究，運作上是以遞迴的形式進行搜尋，並設兩個臨界值參數做為演算法的停止機制，其中一個為有關搜尋路徑的抵達時間，另一個為搜尋路徑的衰減振幅。臨界值參數設定可由錯誤形式的分析來取決，錯誤形式包括有錯誤機率和均方根誤差。錯誤機率分析是以誤判(false alarm)機率和遺失(miss)機率為主，兩個臨界值設定會造成誤判機率和遺失機率之間存在一個取決(trade-off)的問題，必須依照演算法需求的錯誤機率表現決定所需的臨界值。在改善臨界值設定的問題上，我們提出了另一個均方根形式的方法，這改善方法是將兩個臨界值在於一個合適的範圍間變動，並計算每一次變動的均方根誤差值，然後選擇最小誤差所對應的臨界值做為演算法所需要的臨界值。模擬結果顯示，當SNR介於-4dB與16dB之間時，提出的改善方法，相較於原來的決定法則，會有較小誤差的結果表現。

The main purpose of this thesis is to estimate the direct path in dense multipath Ultra Wide-Band (UWB) environment. The time-of-arrival (ToA) estimation algorithm used is based on Generalized Maximum-Likelihood (GML) algorithm. Nevertheless, GML algorithm is so time-consuming that the results usually take a very long period of time, and sometimes fail to converge. Hence, the schemes that would improve the algorithm are investigated. In the schemes, the search was executed in sequential form. Two threshold parameters are to be determined—one is about the arrival time of the estimation path while the other is the fading amplitude of the estimation path. The thresholds are determined in order to terminate the sequential algorithm. The determination of thresholds is based on error analysis, including the probability of error and root-mean-square error. The analysis of the probability of error is subject to the probability of false alarm and the probability of miss. However, a trade-off problem on the probability of false alarm and the probability of miss exists in the process of determining thresholds. The thresholds are determined according to the requirement of the probability of error. We propose an improvement scheme for determining the two thresholds. In the proposed scheme, candidate pairs are evaluated within an appropriate range. The root-mean-square error value for each pair of thresholds is calculated. The smallest error, corresponding to the desired thresholds, is chosen for use in ToA estimation. From the simulation results, it is seen that, when SNR falls between -4dB and 16dB, the improvement proposed scheme results has the smaller estimation error.

感謝詞..................................i
中文摘要...............................ii
英文摘要..............................iii
目錄...................................iv
圖目錄.................................vi
表目錄.................................ix
第一章 緒論.............................1
1.1 前言................................1
1.2 文獻回顧與研究動機..................2
1.3 論文架構............................4
第二章 GML演算法........................5
2.1 接收訊號模式........................5
2.2 GML演算法於訊號延遲時間估測.........8
2.2.1 訊號描述重整......................8
2.2.2 GML演算法........................10
2.3 雜訊功率計算.......................14
2.3.1 GML演算法之接收機................17
2.3.2 雜訊功率計算.....................19
第三章 錯誤分析........................21
3.1 參數統計模型.......................21
3.1.1 參數之機率密度函數...............21
3.1.2 結合機率密度函數.................22
3.2 錯誤機率分析.......................28
3.2.1 誤判(false alarm)機率............29
3.2.2 穿級(Level Crossing)機率.........32
3.2.3 遺失(miss)機率...................35
第四章 模擬通道之錯誤分析.............38
4.1 通道模型...........................38
4.1.1 超寬頻通道之衰減振幅分佈.........38
4.1.2 通道模擬.........................41
4.2 參數統計模型.......................45
4.3 錯誤機率分析.......................50
4.4 均方根誤差統計與臨界值的決定.......52
4.4.1 臨界值決定之統計資料.............53
4.4.2 臨界值的決定.....................54
4.4.3 小結.............................60
第五章 電腦模擬與分析..................62
5.1 模擬簡介...........................62
5.2 非直視路徑環境模擬.................62
5.2.1 模擬環境.........................62
5.2.2 模擬結果討論與分析...............65
第六章 結論與未來展望..................78
6.1 結論...............................78
6.2 未來工作與展望.....................78
參考文獻...............................80

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