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研究生:鄭景豪
研究生(外文):Cheng, Ching-Hao
論文名稱:於分碼多重存取通訊系統使用適應性粒子群最佳化實現低計算負荷之到達方向估測
論文名稱(外文):DOA Estimation with Low Computational Load Using Adaptive PSO for CDMA Communication Systems
指導教授:張安成張安成引用關係
口試委員:張志忠陳孝武
口試日期:100/07/13
學位類別:碩士
校院名稱:嶺東科技大學
系所名稱:資訊科技應用研究所
學門:電算機學門
學類:電算機一般學類
論文種類:學術論文
論文出版年:2011
畢業學年度:99
語文別:中文
論文頁數:67
中文關鍵詞:到達方向估測粒子群最佳化
外文關鍵詞:direction-of-arrivalparticle swarm optimization
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本論文於一個分碼多重存取(CDMA)系統中考慮到達方向(DOA)估測的問題,傳統的多重訊號分類(MUSIC)估測的搜尋複雜度與估測的精準度已經被證明與搜尋時的隔柵大小有關。這是相當耗時的,而且我們無法預先知道所需要隔柵大小為多少才是適當的。
粒子群最佳化(PSO)演算法的計算效率高,並且不容易落入區域最佳解。此外,一個最重要的特徵是PSO演算法本身易於被實現。儘管有前述所提到的這些優勢,計算粒子的適應值仍會消耗大量的計算時間,並且有些PSO參數可能會大幅的影響結果。因此,如何減少PSO的計算複雜度是ㄧ個非常重要的問題。
本論文所提的改良技術係針對幾個參數進行調整以使得PSO更有效率。首先,基於ULA的波束場型為固有的幅射對稱,亦即所有角度相對於水平軸都是對稱的特性,本論文提出一種粒子的搜尋位置映射技術,稱之為模數 校正邏輯限制,來取代粒子位置剪裁的方式。第二,提出具有合理平衡的全域探勘能力與區域探勘能力的PSO適應性多重慣性權重,每個粒子的各個維度在每次運行的各次迭代中可以根據搜尋空間中自身的情況選擇合適的慣性權重。透過上述兩種所提方法,PSO的性能可以被改善。接著,我們應用所提的PSO演算法於有區域散射與天線元件位置擾動的環境,且由於所提的PSO方法可以同時估測天線元件的位置擾動誤差與訊號源入射角度,而不需要校正的訊號源。最後,一些模擬結果被提供用以證明所提技術的有效性。

This thesis deals with consider the problem of estimating the direction-of-arrival (DOA) for code-division multiple access (CDMA) system. It has been shown that the searching complexity and estimating accuracy of the conventional spectral searching multiple signal classification (MUSIC) estimator strictly depends on the number of search grids used during the search. It is time consuming and the required number of search grid is not clear to determine.
The particle swarm optimization (PSO) method is computationally efficient and has great capability of escaping local optima. In addition, a key characteristic of PSO is that the algorithm itself is highly robust yet remarkably simple to implement. Although it has those advantages mentioned, it consumes a lot of computation time to compute the fitnesses of particles and some parameters in PSO may affect the solution significantly. Therefore, how to reduce the computational complexity of PSO algorithm is a very important issue.
In this thesis, the PSO with the proposed techniques offers a much efficient option with few parameters to be adjusted. First, based on the inherent radiation symmetry of the ULA, all radiation patterns are symmetric about the axis of the linear array, this paper presents a particle search position mapping technique, which termed as correction logic constraint, to replace the particle position clipping. Second, an adaptive multiple inertia weight is proposed to rationally balance the global exploration and local exploitation abilities for PSO, at each iteration, during the run, every particle can choose appropriate inertia weight along every dimension of search space according to its own situation. By these two proposed methods, the performance of PSO could be improved. Next, we used the proposed PSO algorithm in the local scattering channel and sensor elements position perturbations environment. Because of this proposed PSO method has no requirement for calibration sources while the sensor position errors as well as the DOAs of the incident signals can be estimated simultaneously. Finally, several computer simulations are provided to demonstrate the effectiveness of the proposed techniques.

誌謝 II
摘要 III
ABSTRACT IV
目錄 V
圖目錄 VIII
表目錄 X
符號說明與縮寫表 XI
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. 訊號模型與到達方向估測技術探討 6
2.1 天線陣列模型 6
2.1.1 均勻線性陣列模型 6
2.1.2 區域散射模型 7
2.1.3 天線元件位置擾動模型 8
2.2 分碼多重存取系統 9
2.3 時間-空間陣列訊號模型 11
2.3.1 發射訊號模型 11
2.3.2 接收訊號模型 12
2.3.3 區域散射通道下線性陣列模型 13
2.3.3.1 非線性區域散射模型 13
2.3.3.2 廣義的一階微分區域散射模型 14
2.3.4 天線元件位置擾動模型 15
2.4 到達方向估測演算法 15
2.4.1 最小變異無失真響應演算法 15
2.4.2 多重訊號分類演算法 16
2.4.3 基於廣義一階微分區域散射模型的多重訊號分類演算法 18
3. 基於粒子群最佳化的到達方向估測技術 19
3.1 HPSO-MUSIC估測法 19
3.1.1 線性下降慣性權重 20
3.1.2 粒子位置邊界限制 21
3.1.3 適應函數 21
3.2 MPSO-MUSIC估測法 22
3.2.1 模數 校正邏輯限制技術 23
3.2.2 MPSO-MUSIC模擬分析 25
3.3 APSO-MUSIC估測法 29
3.3.1 多重適應性慣性權重策略 29
3.3.2 A-law壓縮律 31
3.3.3 壓縮律 32
3.3.4 APSO-MUSIC模擬分析 34
3.4 AMPSO-MUSIC 38
3.4.1 AMPSO-MUSIC模擬分析 40
3.4.2 區域散射環境下的模擬分析 44
4. 天線元件位置擾動環境下之強健的到達方向估測 49
4.1 天線元件位置擾動環境中強健的 PSO DOA估測問題 49
4.2 強健的多維PSO估測技術 50
4.3 電腦模擬分析 54
5. 討論與建議 60
參考文獻 61
論文發表 66
自傳 67

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