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系統識別號 U0026-2801201515273900
論文名稱(中文) 應用主成分空間機率模型於水下通訊定位系統
論文名稱(英文) Applying Probabilistic Model for Principal Component Space to Underwater Communication Positioning System
校院名稱 成功大學
系所名稱(中) 系統及船舶機電工程學系
系所名稱(英) Department of Systems and Naval Mechatronic Engineering
學年度 103
學期 1
出版年 104
研究生(中文) 周睿騰
研究生(英文) Jui-Teng Chou
學號 p16001211
學位類別 碩士
語文別 英文
論文頁數 68頁
口試委員 指導教授-李坤洲
口試委員-卿文龍
口試委員-潘欣泰
口試委員-王健仁
中文關鍵字 水下通訊定位  主成分分析  最大散度差  高斯混合模型  最大概似估計  圖樣辨識 
英文關鍵字 Underwater positioning  Principal Component Analysis  Maximum scatter difference  Gaussian mixture model  Maximum likelihood  Pattern recognition 
學科別分類
中文摘要 本論文利用主成分分析法(principal-component-analysis, PCA)與最大散度差演算法(maximum-scatter-difference algorithm, MSDA)於高斯分佈或高斯混合模型下應用於水下聲波通訊定位。
我們的定位系統流程分為兩個階段,分別為收集訊號的訓練階段和實際定位的測試階段。於訓練階段,我們先利用PCA及MSDA對水下聲波訊號做處理以減少訊號雜訊及環境波動影響。PCA能降低資料維度並捨去帶有雜訊之訊號,而MSDA目的為拉開不同資料類別間的距離及縮短同一資料類別內的差距,並採用類間及類內的差別作為區別標準,所以能因此而減少演算過程所造成的複雜度並加速定位計算流程。於測試階段,為了減少多重反射路徑的干擾影響,我們於高斯分佈或高斯混合模型下利用指紋特徵圖樣辨識概念應用於水下聲波定位。為了證明此做法能夠不受反射訊號或多重路徑傳播訊號所帶來的影響,實驗設置在有邊界的拖曳水槽。我們提出了頻率分量來模擬水下通訊訊號發射器的方法,藉此降低於水下環境中硬體成本問題。最後,我們計算實際位置與估計位置的歐式距離以作為定位誤差。
英文摘要 In this thesis, it is found that how to position given underwater acoustic sources via the maximum likelihood estimation for Gaussian distribution or GMM (Gaussian-mixture-model), together with the PCA (principal-component-analysis) and an MSDA (maximum-scatter-difference algorithm).
The process of our positioning system consists of two stages --- training (offline) and testing (online). During the training stage, to reduce the chaos of underwater acoustic signals and the impact of fluctuations, underwater acoustic signals are processed by the PCA and the MSDA. The PCA can descend dimensions of data and the MSDA adopts the difference of both between-class scatter and within-class scatter as a discriminant criterion, so they reduce the algorithm-induced complexity and hence speed up calculation process. In the testing stage, to reduce the disturbance of reflected signals, we utilize location fingerprinting and likelihood-based pattern recognition for Gaussian distribution or GMM to position underwater acoustic sources. To demonstrate such method is not affected by reflected signals or multipath communication signals, experiments are done in bordered towing tank. We propose a method of using frequency components to simulate underwater communication sound projectors to lower hardware cost in underwater environment. Finally, as soon as the Euclidean distances between the actual positions and the estimated ones are calculated, we obtain the errors of underwater positioning.
論文目次 摘要 .................................................. I
Abstract ............................................. II
Table of Contents .................................... IV
List of Figures ....................................... V
Chapter 1 Introduction ................................ 1
1-1 Research Background and Motivation ................ 1
1-2 Contribution ...................................... 2
1-3 Thesis Overview ................................... 3
Chapter 2 Basic Theory ................................ 6
2-1 Maximum-Scatter-Difference Algorithm .............. 6
2-2 Principal-Component-Analysis ...................... 7
2-3 Gaussian-Mixture-Model............................. 8
Chapter 3 Underwater Positioning via Probabilistic Approach with MSDA ................................... 13
3-1 Introduction ..................................... 13
3-2 Formulation ...................................... 14
3-3 Experiment and Result............................. 18
Chapter 4 Underwater Positioning via Probabilistic Approach with PCA and MSDA............................ 30
4-1 Introduction ..................................... 30
4-2 Formulation ...................................... 31
4-3 Experiment and Result............................. 36
Chapter 5 Underwater Positioning via Probabilistic Approach Based on GMM with PCA and MSDA .............. 44
5-1 Introduction ..................................... 44
5-2 Formulation ...................................... 45
5-3 Experiment and Result............................. 53
Chapter 6 Summary .................................... 61
6-1 Conclusion ....................................... 61
6-2 Future Work ...................................... 63
References ........................................... 64
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