臺灣博碩士論文加值系統

盲蔽單一輸入多重輸出（single-input multi-output, SIMO）通道鑑別的問題出現在科學與工程領域上需要多個感測器的場合，或是通訊中需要多個天線接收訊號以及對通訊訊號做非整數取樣訊號處理（fractionally-spaced signal processing）時。另一方面，從兩個以上的感測器所接收之信號估計時間之延遲（time delay estimation, TDE），則可應用於多感測器陣列中抵達方向（direction of arrival, DOA）之估計、訊號源之定位、聲納與雷達等。Tugnait以及祁與陳提出了基於高階統計量（higher-order statistics, HOS）之多重輸入多重輸出反轉濾波器準則（multi-input multi-output inverse filter criteria, MIMO-IFC），可用於多重輸入多重輸出線性非時變（linear time-invariant, LTI）系統之等化。祁與陳除了提出根據MIMO-IFC設計最佳反轉濾波器之收斂快速演算法外，亦提出某種非線性關係式，存在於根據MIMO-IFC設計之最佳等化器與最小平均平方誤差（minimum mean square error, MMSE）等化器之間。基於此非線性關係，並給定一組非高斯（Gaussian）測量值，我們在本論文中提出一個使用高階統計量之疊代SIMO盲蔽通道估計（blind channel estimation, BCE）演算法以及時間延遲估計演算法。前者為一基於FFT的快速演算法，可同時估計SIMO系統之振幅響應與相位響應；而後者使用根據MIMO-IFC設計之最佳等化器，由單一輸入P輸出（P>=2）系統之相位資訊中，得到P-1個時間延遲估計值之封閉形式解。我們提出一些模擬結果，可用來支持所提出的SIMO BCE 與TDE演算法之效能。

Tugnait, Chi and Chen proposed multi-input multi-output inverse filter criteria (MIMO-IFC) using higher-order statistics (HOS) for blind deconvolution of MIMO linear time-invariant (LTI) systems. Chi and Chen also proposed a property of nonlinear relationship between the optimum inverse filter associated with MIMO-IFC and the MIMO minimum mean square error (MIMO-MMSE) equalizer. In this paper, based on the nonlinear relationship, an iterative single-input multi-output (SIMO) blind channel estimation (BCE) algorithm and a time delay estimation (TDE) algorithm using HOS are proposed with a given set of non-Gaussian measurements. The former is a fast FFT-based algorithm for joint estimation of magnitude response and phase response of SIMO systems and the latter estimates P-1 time delays from the phase information of single-input P-output (P>=2) system leading to a closed-form solution of time delay estimates using the optimum inverse filter associated with MIMO-IFC. Some simulation results are presented to support the efficacy of the proposed SIMO BCE and TDE algorithms.

CHINESE ABSTRACT
ENGLISH ABSTRACT
ACKNOWLEDGMENTS
CONTENTS
CHAPTER 1. INTRODUCTION
CHAPTER 2. REVIEW OF MIMO-IFC
2-1.MIMO-IFC
2-2.Fast Algorithm for Maximizing MIMO-IFC
2-3.Property of MIMO-IFC
CHAPTER 3. SIMO BCE AND TDE Algorithm
3-1.SIMO BCE
3-2.TDE Algorithm
3-2-1. SIMO Model for TDE
3-2-2. TDE Using Only Phase Information of SIMO System
3-2-3. TDE Using Only the Optimum Inverse Filter
Associated with MIMO-IFC
CHAPTER 4. SIMULATION RESULTS
CHAPTER 5. CONCLUSIONS
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