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研究生:劉俊成
研究生(外文):Liou, Jiun-Chen
論文名稱:使用新穎水下聽音器陣列製程與希爾伯-黃演算法於水下方位估測應用
論文名稱(外文):Underwater Direction-of-Arrival Estimation Using Novel Hydrophone Array Fabrication and Hilbert-Huang Transform Algorithm
指導教授:洪賢昇張順雄張順雄引用關係
指導教授(外文):Huang, Hsien-SenChang, Shun-Hsyung
口試委員:詹景裕洪賢昇方文賢張順雄何志傑曾敬翔
口試委員(外文):Jan, Gene-EuHuang, Hsien-SenFang, Wen-HsienChang, Shun-HsyungHo, Jyh-JierTseng, Ching-Hsiang
口試日期:2018-06-16
學位類別:博士
校院名稱:國立臺灣海洋大學
系所名稱:電機工程學系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2018
畢業學年度:106
語文別:英文
論文頁數:71
中文關鍵詞:方位估測希爾伯-黃轉換時頻分析微機電製程有限元素分析水下聽音器陣列
外文關鍵詞:Direction-of-Arrival (DOA) estimationHilbert-Huang Transform (HHT)Time-Frequency Analysis (TFA)Finite-Element Analysis (FEA))Micro-Electro-Mechanical Systems (MEMS)Hydrophone Array
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隨著海洋活動近年來的快速發展,使用聲納和水下聽音器陣列的水下聲波探測技術已廣泛應用於近岸石油探勘、失事載具搜尋、水產養殖、海洋科學數據採集、無人水下航行、船舶導航等領域。傳統的水下聽音器陣列,由於陣列孔徑長和體積龐大,不適用於機動性的水下無人載具。有鑑於此,本論文首先研究使用新穎的微機電製程,設計與製造水下聽音器陣列,使其能夠適用於機動性的水下無人載具,作海洋探測之應用。
另一方面,聲納的水下方位估測技術,是用於定位和識別水下目標物(訊號源)的重要水下技術。於被動式聲納中,傳統的高解析度方位估測,使用水下聽音器陣列收集來自目標物的多瞬攝訊號。其中,MUSIC演算法主要是解析接收信號的自相關矩陣之特徵結構,來確定目標方位。其缺點為感測器數目必須大於目標物數目,而且瞬攝數目必須大於感測器數目,否則該演算法無法分析。此外,於陣列感測器數目多的情況下,特徵結構分析需要龐大的計算複雜度。在主動式聲納中,傳統的方法使用回波與傳送訊號的交相關運算,所產生的曖昧函數是有關距離-都卜勒頻率的三維圖。其缺點為,欲找出曖昧函數的峰值需要在二維空間搜尋,其計算量龐大。此外,當應用於多個訊號源(目標物)的定位時,曖昧函數的解析度也會受到鄰近訊號源的影響而降低。為了克服上述的缺點,目前水下的高解析度演算法主要都是基於時頻分析的多維度特性。有鑑於此,本論文的研究發現,應用時頻分佈函數和希爾伯-黃轉換(HHT)可以解析非平穩信號的瞬時頻率,從而獲得目標物的距離和方位角。兹將本論文研究的成果,分成三大部分說明如下:
其一,我們提出一種新穎的高靈敏度水下聽音器陣列的設計與製程方法。設計方式採用有限元素分析法(FEA),決定水下聲學元件的共振頻率。製程方法使用微機電(MEMS)製程技術,將外延薄膜生成於矽晶片上。此外,將完製的水下聽音器陣列置放於水槽中做測試。測試結果証實所提出的設計與製程方法,可以得到高靈敏度水下聽音器陣列,於50赫茲到500赫茲的頻率範圍內,其靈敏度可達到-190 dB,其誤差範圍在2 dB內。
其二,我們以單一靜態之被動式水下聽音器陣列,提出一種適用於多個訊號源(目標物)的方位估測法。此方法的新穎性,在於應用希爾伯-黃轉換可以將每一個訊號源的瞬時頻率,各自獨立地解析出來,從而獲得每一個訊號源的距離和方位角。其優點為: 1)只須要單一個瞬攝數的聽音器陣列接收訊號;2) 沒有感測器數目必須大於目標物件數目的限制;3) 低的運算複雜度容許即時的定位實用性。電腦模擬時,我們以上述的水下聽音器陣列之設計參數情況下,來驗證所提的方位估測法之可行性。
其三,我們以單一移動之主動式水下感測器,提出一種適用於多個訊號源(目標物)的方位估測法。此方法使用希爾伯-黃轉換,來分析每一個訊號源的瞬時頻率,獲得每一個訊號源的都卜勒頻率與方位角的關係,以進一步估測每一個訊號源的方位角。此方法的優點為1)目標物的方位資訊可以從瞬時頻率取得,計算複雜度低,適合於即時處理的應用;2) 只需要單一移動之主動式感測器,成本低;3) 避開傳統方法的曖昧函數解析度因鄰近訊號源的影響而降低的缺憾。電腦模擬時,我們以上述的水下聽音器之設計參數情況下,來驗證所提的方位估測法之可行性。
With the rapid development of marine activities in recent years, underwater detection technologies using sonar and hydrophone array are extensively applied to the areas of offshore oil exploration, crash vehicle search, aquaculture, ocean’s scientific data collection, unmanned vehicle sailing, and vessel navigation, etc. Traditional hydrophone arrays are not applicable to mobile unmanned vehicles due to long array aperture as well as large-size volume. In view of this drawback, the thesis is aimed to investigate a novel MEMS process to design and fabricate hydrophone arrays so that these acoustic devices can be applied to mobile unmanned vehicles for marine exploration application.
On the other hand, sonar’s direction-of-arrival (DOA) estimation is one of the important underwater technologies used for locating and identifying targets. In passive sonar, conventional high-resolution DOA estimation methods use a hydrophone array to collect several snapshot data from multiple sources. One of the such methods is the MUSIC algorithm which mainly performs eigen-structure analysis of the autocorrelation matrix of the received signal to estimate DOAs of multiple targets. Its drawbacks include: 1) the number of sensors needs to be larger than the number of targets, 2) the number of snapshots must be larger than the number of sensors;otherwise, this method would not work. Furthermore, the eigen-structure analysis needs a very large operational complexity for the case of a huge number of sensors. In active sonar, traditional methods use the cross-correlation of the echoed signal and the transmit signal to produce the ambiguity function, a three-dimensional plot of range-versus-Doppler frequency. One of its drawbacks is the intensive operational complexity due to the exhaust search of local peak locations in the two-dimensional domain. In addition, when applied to the localization of multiple sources, the resolution of the ambiguity function deteriorates due to the existence of the nearby sources. To overcome the aforementioned drawbacks, current underwater high-resolution algorithms are mostly based on the multiple dimensional features of time-frequency analysis. Motivated by these findings, our research has discovered that time-frequency distribution function and the Hilbert-Huang Transform (HHT) can be used to analyze the instantaneous frequency of non-stationary signals, leading to obtain the range and DOA of each target.
The research findings of the thesis are listed as follows.
1. A novel design and fabrication methodology for high-sensitivity hydrophone arrays is proposed. The design method determines the resonant frequency of the acoustic device through the finite-element analysis (FEA). The fabrication method involves the Micro-Electro-Mechanical Systems (MEMS) process using epitaxial thin films grown on silicon wafers. Further, the fabricated hydrophone array was placed in a water tank for testing. The testing results demonstrate that the proposed design and fabrication methodology can obtain a high-sensitivity hydrophone array with a sensitivity of −190 dB ± 2dB for frequencies ranging from 50 Hz to 500 Hz.
2. In passive sonar, a novel approach for DOA and range estimation of multiple targets based on a long array of hydrophones is proposed. The novelty of the proposed method uses the Hilbert-Huang transform (HHT) that allows the instantaneous frequency of each source can be decomposed independently and be analyzed to obtain its DOA and range. It has the following advantages: 1) only a single snapshot of the received signal collected from a hydrophone array is needed; 2) the constraint of “ the number of sensors needs to be larger than the number of sources” can be eliminated; and 3) low operational complexity allows real-time localization to be plausible. In computer simulations, the system parameters are chosen to meet the ones used in the design of the MEMS-based hydrophone array, and under this situation, simulation results have demonstrated the feasibility of the proposed method.
3. In active sonar, based on a single mobile active sensor, we propose a novel approach for DOA estimation of multiple sources. The proposed method uses the Hilbert-Huang transform (HHT) that allows the instantaneous frequency (IF) of each source to be analyzed. From the IF characteristic of each source, the relationship between its DOA and Doppler frequency can be obtained and its DOA can be estimated. The advantages of the proposed approach are: 1) information about each source’s DOA is accessible from the instantaneous frequency, leading to low computational complexity and being suitable to real-time processing; 2) only a single mobile and active sensor is needed, thus cost effective; and 3) avoidance of resolution reduction in the ambiguity function caused by the interference of nearby sources. Simulation results have demonstrated feasibility of the proposed method with the system parameters set to be matched with the ones in the design stage.
中文摘要 I
Abstract III
Contents VI
Figure Captions IX
Glossary and Symbols XII
Chapter 1 Introduction 1
1.2 Hydrophone array 2
1.3 Direction-of- Arrival Estimation in Passive Sonar 2
1.4 Direction-of- Arrival Estimation in Active Sonar 3
1.5 Background Techniques 3
1.5 Organization and Contributions of Thesis 6
Chapter 2 Design and Fabrication of Hydrophone Array 8
2.1 Finite-element modeling of MEMS-based hydrophone array 8
2.2 Structure Design of Hydrophone Array 16
2.3 Hydrophone’s Equivalent Circuit 18
2.4 Frequency Response of the Hydrophone Array Sensitivity 22
2.5 Fabrication Procedure 24
2.6 Results and Discussion 25
2.7 Summary 34
Chapter 3 Passive DOA Estimation via HHT and a Static Hydrophone Array 35
3.1 Data Model 35
3.2 Proposed Method 36
3.2.1 Overview of HHT 36
3.2.2 HHT-based target location estimation scheme 38
3.3 Simulation Results 42
3.4 Summary 48
Chapter 4 Active DOA Estimation via HHT and a Mobile Hydrophone 49
4.2 Proposed Method 51
4.3 Simulation results and discussion 53
4.4 Summary 58
Chapter 5 Conclusions and Future Perspective 59
5.1 Conclusions 59
5.2 Future Perspectives 60
References 61
Appendix A: Derivation of Eqn. (32) 67
Appendix B: Regression Line Formula 69
Publication List of Jeng-Cheng Liu 70
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