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  1. NTU Theses and Dissertations Repository
  2. 工學院
  3. 工程科學及海洋工程學系
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/98970
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dc.contributor.advisor郭振華zh_TW
dc.contributor.advisorJen-Hwa Guoen
dc.contributor.author郭又禎zh_TW
dc.contributor.authorYu-Chen Kuoen
dc.date.accessioned2025-08-20T16:28:59Z-
dc.date.available2025-08-21-
dc.date.copyright2025-08-20-
dc.date.issued2025-
dc.date.submitted2025-08-14-
dc.identifier.citationB. S. Bourgeois, "Using Range and Range Rate for Relative Navigation," Naval Research Laboratory Marine Geosciences Division Stennis Space Center, Arlington, 2007.
T. I. Fossen, Handbook of Marine Craft Hydrodynamics and Motion Control. Wiley, 2011.
A. A. Pereira, J. Binney, G. A. Hollinger, and G. S. Sukhatme, “Risk-aware path planning for autonomous underwater vehicles using predictive ocean models,” Journal of Field Robotics, vol. 30, no. 5, pp. 741–762, Jul. 2013
Nijmeijer, H.; van der Schaft, A. Nonlinear Dynamical Control Systems; Springer: Berlin,Germany, 1990.
F. Arrichiello, G. Antonelli, A. P. Aguiar, A. Pascoal, "An Observability Metric for Underwater Vehicle Localization Using Range Measurements," Sensors (Basel), pp. 16191-16215, 27 November 2013.
A. T. Hsiao, "Localization of An Autonomous Underwater Vehicle Using AcousticSounds from a Single Beacon," Graduate Institute of Engineering Science and Ocean Engineering College of Engineering Master Thesis, National Taiwan University, 2018.
Y. J. Chan, " Observability Analysis of Autonomous Underwater Vehicles Using Range and Range-Rate Measurements " Graduate Institute of Engineering Science and Ocean Engineering College of Engineering Master Thesis, National Taiwan University, 2018.
P. Batista, C. Silvestre and P. Oliveira, ”Single beacon navigation: Observability analysis and filter design,” Proceedings of the2010 American Control Conference, 2010, pp. 6191-6196, doi:10.1109/ACC.2010.5531613.
J.J. Leonard, A. Bahr, ”Autonomous Underwater Vehicle Navigation,”in Springer Handbook of Ocean Engineering. Belrin: Springer, Cham,2016, ch.14, pp. 345-349
F. Thomas and L. Ros, “Revisiting trilateration for robot localization,” IEEE Trans. Robot., vol. 21, no. 1, pp. 93–101, Feb. 2005.
B. D. Hong, " On the Dynamics of a Cable-connected Underwater Glider," Graduate Institute of Engineering Science and Ocean Engineering College of Engineering Master Thesis, National Taiwan University, 2022
L. Techy, K. A. Morgansen, and C. A. Woolsey, “Long-baseline acoustic localization of the seaglider underwater glider,” in Proc. Amer. Control Conf., Jun. 2011, pp. 3990–3995.
J. Sun, S. Liu, J. Yu. A. Zheng. F. Zhang. Localization of underwater gliders with acoustic travel-time in an observation network. Proc. of Oceans 2016-Shandai.Shanghai China, 2016.
Eichhorn, M., Aragon, D., Shardt, Y.A., Roarty, H., 2020. Modeling for the performance of navigation, control and data post-processing of underwater gliders. Appl. Ocean Res. 101, 102191.
N. Mahmoudian, C. Woolsey, and J. Geisbert. Steady turns and optimal path for underwater gliders. Hilton Head, SC, Aug 20-23 2007. AIAA Guidance, Navigation and Control Conference and Exhibit
F. Ham and R. Brown. Observability, eigenvalues, and kalman filtering. IEEE Transactions on Aerospace and Electronic Systems, AES19(2):269–273, 1983.
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dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/98970-
dc.description.abstract本論文為使用單聲標的水下滑翔機,提出了一套事後導航與可觀測性分析的框架。研究提出了一種基於擴展卡爾曼濾波器的平滑方法論,該方法首先利用終點GPS數據來校正流場,而後將修正後的航位推算路徑與GPS和聲學量測進行融合。我們透過李導數建構了一個非線性可觀測性矩陣,以提供一個量化的可觀測性指標。數值模擬確定了在與相對位置向量垂直的運動中,可觀測性會達到最大化。現場試驗驗證了此特性,揭示了成功的軌跡重建,發生在經分析預測具有最高可觀測性程度的聲標配置中。此發現表明,幾何位置關係是達成穩定且準確估計的關鍵因素。本研究所提出的感測器融合策略與可觀測性分析,為未來滑翔機的軌跡規劃與自主導航提供了穩健且考慮幾何因素的理論基礎。zh_TW
dc.description.abstractThis thesis introduces a framework for the post-navigation and observability analysis of an underwater glider using a single acoustic beacon. An EKF-based smoothing methodology is proposed, which first corrects for ocean currents using end-point GPS data, then fuses the corrected path with acoustic measurements in a Kalman-based framework. A nonlinear observability matrix is constructed via Lie derivatives to provide a quantitative observability metric. Numerical simulations establish that observability is maximized during motion orthogonal to the relative position vector. Field trials validate this framework, revealing that the successful trajectory reconstruction occurred with the beacon configuration that exhibited the highest degree of observability, as predicted by the analysis. This finding suggests that a favorable geometric configuration is a critical factor for achieving a stable and accurate estimation. The proposed sensor-fusion strategy and observability analysis provide a robust, geometry-aware foundation for future glider trajectory planning and autonomous navigation.en
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dc.description.tableofcontents致謝 i
中文摘要 iii
Abstract iv
Contents v
List of Figures vii
List of Tables xi
List of Symbols xii
Chapter 1 Introduction 1
1.1 Background and motivation 1
1.2 Scope of this thesis 2
Chapter 2 Methodology 5
2.1 Method of positioning 5
2.1.1 Dead Reckoning 5
2.1.2 Trilateration 8
2.1.3 Smoothing method based on Extended Kalman Filter 9
2.1.4 Smoothing methodology used in this thesis 13
2.2 Observability 15
2.2.1 Observability matrix 16
2.2.2 Lie Derivative 16
2.2.3 The simplification of observability 18
2.2.4 Condition Number 19
Chapter 3 Model and Simulation 21
3.1 Model of underwater system 21
3.1.1 Description of State 21
3.1.2 The Measurement Model 24
3.1.3 Formulation of the Recursive Smoothing Stage 27
3.2 Observability Matrix 29
3.2.1 Description 29
3.2.2 Observability and Rank 32
3.3 Glider’s Motion Simulation 35
3.3.1 Circle path in different radius 36
3.3.2 Different Paths in straight line 40
3.3.3 circle path with different beacon positions 45
Chapter 4 Experiment 50
4.1 Experiment equipment 50
4.1.1 Underwater glider 50
4.1.2 Acoustic sensor 55
4.1.3 Experiment environment 57
4.2 Result of Experiment 59
4.2.1 Positioning result 59
4.2.2 Instantaneous Observability and the measurement 63
4.2.3 Discussion 66
Chapter 5 Conclusion 69
Appendices 71
A. Sensors in Underwater Glider 71
References 77
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dc.language.isoen-
dc.subject後處理zh_TW
dc.subject共變異數zh_TW
dc.subject水下滑翔機zh_TW
dc.subject李導數zh_TW
dc.subject觀測度zh_TW
dc.subject擴展卡爾曼濾波器zh_TW
dc.subjectExtended Kalman Filteren
dc.subjectPost-processingen
dc.subjectUnderwater glideren
dc.subjectCovarianceen
dc.subjectLie derivativeen
dc.subjectObservabilityen
dc.title水下滑翔機系統相對單聲標之觀測度研究zh_TW
dc.titleSingle-beacon observability for an underwater glider systemen
dc.typeThesis-
dc.date.schoolyear113-2-
dc.description.degree碩士-
dc.contributor.oralexamcommittee黃千芬;戴璽恆zh_TW
dc.contributor.oralexamcommitteeChen-Fen Huang;Hsi-Heng Daien
dc.subject.keyword水下滑翔機,後處理,觀測度,李導數,擴展卡爾曼濾波器,共變異數,zh_TW
dc.subject.keywordUnderwater glider,Post-processing,Observability,Lie derivative,Extended Kalman Filter,Covariance,en
dc.relation.page79-
dc.identifier.doi10.6342/NTU202504250-
dc.rights.note未授權-
dc.date.accepted2025-08-15-
dc.contributor.author-college工學院-
dc.contributor.author-dept工程科學及海洋工程學系-
dc.date.embargo-liftN/A-
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