精確定位是影響水下載具導航的關鍵因素，雖然當前已經發展許多水下定位儀器與方法，但只有極少數的單一系統能夠提供水下載具可靠的三維座標。長基線定位系統雖然可以量測水下載具三維絕對座標，但卻也存在資料更新緩慢的問題，必須整合其他感測資料，才能提昇長基線系統定位水下載具的精度與可靠度。本研究透過數值模擬與實海域量測實驗，探討長基線詢答時間(Interrogate rate)對水下載具定位精度的影響。由數值模擬與實驗分析結果可知，拉長詢答時間會降低定位精度，此外，無法連續收到應答器的詢答回訊則是長基線定位的另一個主要誤差來源。實驗結果也證實，整合長基線系統與速度資訊來估算收發器位置，可大幅降低水下載具定位誤差。因此，本研究透過卡曼濾波運算整合長基線系統與載具運動方程式，以提高水下載具定位精度。為了進行長基線定位與載具動態模式之整合研究，本研究開發一台水下載具以及簡易人機介面，便於操控載具進行水下定位實驗。為了精確模擬載具運動，本研究進行非耦合運動量測實驗，以鑑別載具動力參數。最後，本研究利用拖航水槽進行定位實驗，控制載具以S形軌跡行進，同時收集長基線定位資料、推進器命令、以及深度資料，並透過卡曼濾波運算融合長基線斜距、載具動力模式之速度資訊、以及深度資訊。實驗結果顯示，利用卡曼濾波整合載具動態模式確實可以改善長基線定位誤差，有效提升水下載具定位精度。

Precise positioning is crucial for the success of navigation of underwater vehicles. At present, different instruments and methods are available for underwater positioning but few of them are reliable for three-dimensional position sensing of underwater vehicles. Long baseline (LBL) positioning is the standard method for three-dimensional underwater navigation. However, the accuracy of LBL positioning suffers from its own drawback of relatively low update rates. To improve the accuracy in positioning an underwater vehicle, integration of additional sensing measurements in a LBL navigation system is necessary. In this study, numerical simulation and experiment are conducted to investigate the effect of interrogate rate on the accuracy of LBL positioning. Numerical and experimental results show that the longer the interrogate rate, the greater the LBL positioning error. In addition, no reply from a transponder to transceiver interrogation is another major error source in LBL positioning. The experimental result also shows that the accuracy of LBL positioning can be significantly improved by the integration of velocity sensing. Therefore, based on Kalman filter, this study integrates a LBL system with vehicle dynamic model to improve the accuracy of positioning an underwater vehicle. For conducting the positioning experiments, a remotely operated vehicle (ROV) with dedicated Graphic User Interface (GUI) is designed, constructed, and tested. To have a precise motion simulation of ROV, a nonlinear dynamic model of ROV with six degrees of freedom (DOF) is used and its hydrodynamic parameters are identified. Finally, the positioning experiment is run by maneuvering the ROV to move along an “S” trajectory, and Kalman filter is adopted to propagate the error covariance, to update the measurement errors, and to correct the state equation when the measurements of range, depth, and thruster command are available. The experimental result demonstrates the effectiveness of the integrated LBL system with the ROV dynamic model on the improvement of accuracy of positioning an underwater vehicle.

第一章 緒論 1
1.1 研究動機與目的..........................................................1
1.2 文獻回顧......................................................................2
1.3 論文架構......................................................................4
第二章 研究方法 5
2.1 長基線定位原理..........................................................5
2.2 應答器定位估算..........................................................8
2.3 載具運動方程式..........................................................9
2.3.1 座標系統定義.......................................................9
2.3.2 運動方程式........................................................12
2.4 卡曼濾波運算............................................................17
2.4.1 離散卡曼濾波.....................................................17
2.4.2 擴展式卡曼濾波.................................................20
第三章 長基線定位精度探討 23
3.1 數值模擬....................................................................24
3.2 實海域實驗................................................................26
3.3 長基線定位資料分析................................................34
3.4 定位誤差改善............................................................43
第四章 水下載具開發 48
4.1 系統元件與感測器.....................................................48
4.2 系統架構....................................................................54
4.3 硬體設計....................................................................58
4.4 人機介面....................................................................64
第五章 載具動力參數鑑別 67
5.1 推力配置....................................................................67
5.2 非耦合運動順序........................................................70
5.2.1 起伏運動.............................................................70
5.2.2 縱移運動.............................................................71
5.2.3 平擺運動.............................................................72
5.2.4 橫搖運動.............................................................73
5.2.5 縱搖運動.............................................................74
5.2.6 縱移平擺運動.....................................................75
5.2.7 載具運動順序.....................................................76
5.3 載具動力參數鑑別....................................................77
5.3.1 起伏運動.............................................................80
5.3.2 橫搖運動.............................................................85
5.3.3 縱搖運動.............................................................87
5.3.4 平擺運動.............................................................89
5.3.5 縱移運動.............................................................94
5.3.6 縱移平擺運動.....................................................97
5.3.7 鑑別結果...........................................................102
第六章 長基線定位與載具動力模式整合 103
6.1 實驗規劃..................................................................103
6.2 長基線定位..............................................................107
6.3 卡曼濾波運算整合長基線定位與載具動態模式..109
第七章 結論與建議 114
7.1 結論..........................................................................114
7.2 建議..........................................................................116

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