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A calibration method for MEMS inertial sensors based on optical techniques.

Dong, Zhuxin. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (leaves 77-80). / Abstracts in English and Chinese. / Abstract --- p.ii / 摘要 --- p.iii / Acknowledgements --- p.iv / Table of Contents --- p.v / List of Figures --- p.vii / List of Tables --- p.ix / Chapter Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Architecture of UDWI --- p.3 / Chapter 1.2 --- Background of IMU Sensor Calibration --- p.5 / Chapter 1.3 --- Organization --- p.7 / Chapter Chapter 2 --- 2D Motion Calibration --- p.10 / Chapter 2.1 --- Experimental Platform --- p.10 / Chapter 2.1.1 --- Transparent Table --- p.10 / Chapter 2.2 --- Matching Algorithm --- p.13 / Chapter 2.2.1 --- Motion Analysis --- p.13 / Chapter 2.2.2 --- Core Algorithm and Matching Criterion --- p.14 / Chapter 2.3 --- Usage of High Speed Camera --- p.17 / Chapter 2.4 --- Functions Realized --- p.17 / Chapter Chapter 3 --- Usage of Camera Calibration --- p.21 / Chapter 3.1 --- Introduction to Camera Calibration --- p.21 / Chapter 3.1.1 --- Related Coordinate Frames --- p.21 / Chapter 3.1.2 --- Pin-Hole Model --- p.24 / Chapter 3.2 --- Calibration for Nonlinear Model --- p.27 / Chapter 3.3 --- Implementation of Process to Calibrate Camera --- p.28 / Chapter 3.3.1 --- Image Capture --- p.28 / Chapter 3.3.2 --- Define World Frame and Extract Corners --- p.28 / Chapter 3.3.3 --- Main Calibration --- p.30 / Chapter 3.4 --- Calibration Results of High Speed Camera --- p.33 / Chapter 3.4.1 --- Lens Selection --- p.33 / Chapter 3.4.2 --- Property of High Speed Camera --- p.34 / Chapter Chapter 4 --- 3D Attitude Calibration --- p.36 / Chapter 4.1 --- The Necessity of Attitude Calibration --- p.36 / Chapter 4.2 --- Stereo Vision and 3D Reconstruction --- p.37 / Chapter 4.2.1 --- Physical Meaning and Mathematical Model Proof --- p.37 / Chapter 4.2.2 --- 3D Point Reconstruction --- p.38 / Chapter 4.3 --- Example of 3D Point Reconstruction --- p.40 / Chapter 4.4 --- Idea of Attitude Calibration --- p.42 / Chapter Chapter 5 --- Experimental Results --- p.45 / Chapter 5.1 --- Calculation of Proportional Parameter --- p.45 / Chapter 5.2 --- Accuracy Test of Stroke Reconstruction --- p.46 / Chapter 5.3 --- Writing Experiments of 26 Letters --- p.47 / Chapter 5.3.1 --- Experimental Results of Letter b --- p.48 / Chapter 5.3.2 --- Experimental Results of Letter n with ZVC --- p.51 / Chapter 5.3.3 --- Experimental Results of Letter u --- p.54 / Chapter 5.4 --- Writing of Single Letter s - Multiple Tests --- p.56 / Chapter 5.5 --- Analysis on Resolution Property of Current Vision Algorithm --- p.58 / Chapter 5.5.1 --- Resolution of Current Algorithm --- p.58 / Chapter 5.5.2 --- Tests with Various Filters --- p.59 / Chapter 5.6 --- Calculation of Static Attitude --- p.61 / Chapter Chapter 6 --- Future Work --- p.64 / Chapter 6.1 --- Another Multiple Tests of Letter k --- p.64 / Chapter 6.2 --- Letter Recognition Based on Neural Networks Classification --- p.66 / Chapter Chapter 7 --- Conclusion --- p.69 / Chapter 7.1 --- Calibration ofMAG-μlMU Sensors --- p.69 / Chapter 7.2 --- Calibration of Accelerometers --- p.70 / Chapter 7.3 --- Calibration of Attitude --- p.70 / Chapter 7.4 --- Future Work --- p.71 / Appendix A The Experimental Results of Writing English Letters --- p.72

Identiferoai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_326244
Date January 2008
ContributorsDong, Zhuxin., Chinese University of Hong Kong Graduate School. Division of Automation and Computer-Aided Engineering.
Source SetsThe Chinese University of Hong Kong
LanguageEnglish, Chinese
Detected LanguageEnglish
TypeText, bibliography
Formatprint, ix, 80 leaves : ill. (some col.) ; 30 cm.
RightsUse of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/)

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