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Elevation and Deformation Extraction from Tomosar

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Elevation and Deformation Extraction from Tomosar Title Elevation and Deformation Extraction from TomoSAR Lang Feng Thesis submitted for the degree of Doctor of Philosophy Mullard Space Science Laboratory Department of Space and Climate Physics University College London 2019 1 This page is intentionally left blank. 2 Author Declaration I, Lang Feng, confirm that the work presented in this thesis is my own. Where information has been derived from other sources, I confirm that this has been indicated in the thesis. LANG FENG 2019-02-01 3 This page is intentionally left blank. 4 Abstract 3D SAR tomography (TomoSAR) and 4D SAR differential tomography (Diff- TomoSAR) exploit multi-baseline SAR data stacks to provide an essential innovation of SAR Interferometry for many applications, sensing complex scenes with multiple scatterers mapped into the same SAR pixel cell. However, these are still influenced by DEM uncertainty, temporal decorrelation, orbital, tropospheric and ionospheric phase distortion and height blurring. In this thesis, these techniques are explored. As part of this exploration, the systematic procedures for DEM generation, DEM quality assessment, DEM quality improvement and DEM applications are first studied. Besides, this thesis focuses on the whole cycle of systematic methods for 3D & 4D TomoSAR imaging for height and deformation retrieval, from the problem formation phase, through the development of methods to testing on real SAR data. After DEM generation introduction from spaceborne bistatic InSAR (TanDEM- X) and airborne photogrammetry (Bluesky), a new DEM co-registration method with line feature validation (river network line, ridgeline, valley line, crater boundary feature and so on) is developed and demonstrated to assist the study of a wide area DEM data quality. This DEM co-registration method aligns two DEMs irrespective of the linear distortion model, which improves the quality of DEM vertical comparison accuracy significantly and is suitable and helpful for DEM quality assessment. A systematic TomoSAR algorithm and method have been established, tested, analysed and demonstrated for various applications (urban buildings, bridges, dams) to achieve better 3D & 4D tomographic SAR imaging results. These include applying Cosmo-Skymed X band single-polarisation data over the Zipingpu dam, Dujiangyan, Sichuan, China, to map topography; and using ALOS L band data in the San Francisco Bay region to map urban building and bridge. A new ionospheric correction method based on the tile method employing IGS TEC data, a split-spectrum and an ionospheric model via least squares are developed to correct ionospheric distortion to improve the accuracy of 3D & 4D tomographic SAR imaging. Meanwhile, a pixel by pixel orbit baseline estimation method is developed to address the research gaps of baseline estimation for 3D & 4D spaceborne SAR tomography imaging. Moreover, a SAR tomography imaging algorithm and a differential 5 tomography four-dimensional SAR imaging algorithm based on compressive sensing, SAR interferometry phase (InSAR) calibration reference to DEM with DEM error correction, a new phase error calibration and compensation algorithm, based on PS, SVD, PGA, weighted least squares and minimum entropy, are developed to obtain accurate 3D & 4D tomographic SAR imaging results. The new baseline estimation method and consequent TomoSAR processing results showed that an accurate baseline estimation is essential to build up the TomoSAR model. After baseline estimation, phase calibration experiments (via FFT and Capon method) indicate that a phase calibration step is indispensable for TomoSAR imaging, which eventually influences the inversion results. A super-resolution reconstruction CS based study demonstrates X band data with the CS method does not fit for forest reconstruction but works for reconstruction of large civil engineering structures such as dams and urban buildings. Meanwhile, the L band data with FFT, Capon and the CS method are shown to work for the reconstruction of large manmade structures (such as bridges) and urban buildings. 6 Impact Statement A new DEM co-registration algorithm co-aligns two DEMs, which improves the quality of DEM relative accuracy significantly and is suitable and helpful for DEM quality assessment. This method can also be used for merging and fusing bathymetry (seafloor) with land DEM data at the coast region to generate a future global DEM. In addition, this algorithm works well for finding the correct landing site and precise and safe planetary rover landing, which can be used for future planetary rover landing missions. More specifically, the algorithm can be integrated with IMU and DEM- producing sensors in Guidance, Navigation and Control (GNC) system for navigation in different environments (sea, land, air, space and deep space) for different applications. The DEM over the UK (in particular the TanDEM-X IDEM and the TanDEM-X DEM) quality report and statistical analysis results are useful for future DEM users and DEM makers. A new ionospheric correction and mapping method not only addresses the SAR ionospheric accuracy degradation problem, its high-resolution TEC data can also be obtained after processing, which (TEC data) can be used in many other application fields, like communications, radio astronomy, as well as many other terrestrial planets and their satellites (moons), with the same earth-like environment, and so on. The systematic TomoSAR and D-TomoSAR algorithm and methods to retrieve the 3D & 4D information can be potentially useful for many future applications (urban buildings, bridges, dams, forests, and icy regions on the Earth and the Moon) and missions. 7 This page is intentionally left blank. 8 Acknowledgements First and foremost, I would like to express my greatest thanks to my supervisors, Prof. Jan-Peter Muller and Dr Jonathan Rae. Individually, Peter, I thank you for your useful suggestions, excellent guidance, constant encouragement and generous support in my life and study throughout my PhD program in the UK and invaluable time during the writing up of this thesis. I also thank you for helping me to improve my English in each tutorial, all documents feedbacks, and supporting me to take English course to improve my English in Surrey University and UCL, and providing me with countless opportunities to take courses, training and conferences over the last four years. Jonny, I cannot thank you enough for your valuable advice, creative guidance, thought-provoking viewpoints, continuous support, constant encouragement and much of your time in tutorials and reading my thesis. I have been enormously fortunate to have you and Peter as my supervisors. In addition, I would like to express my greatest gratitude to my PhD panel chair, Dr Daisuke Kawata. I appreciate your continuous support, constant encouragement and invaluable advice provided throughout my PhD programme. I also thank you for being positive in my abilities and for being patient in listening and understanding me when I have most needed it. I am also grateful to my examiners, Prof. Shaun Quegan and Prof. Tim Wright, for constructive comments that improved this thesis. I would also like to thank the China Scholarships Council (CSC) and UCL MAPS Dean prize joint research scholarship for providing the financial support, allowing this work to be undertaken. I owe special thanks to a few individuals whose contribution to this project was in some way immense. First, I would like to thank Terri Freemantle from Space Catapult, Harwell space campus for arranging the provision of CORSAIR011 data. Besides, I would like to thank Prof. Tim Wright and Prof. Andy Hooper from the University of Leeds for organising COMET InSAR training workshop 2017 and providing code and data in this workshop and Dr David Bekaert from JPL NASA for providing SAR code. Meanwhile, I would like to thank Prof. Zhenhong Li for his valuable advice, thought- provoking viewpoints and providing GACOS data. Moreover, I would like to thank Prof. Stefano Tebaldini from Politecnico di Milano, Prof. Laurent Ferro-Famil from the University of Rennes for providing data and code and ESA for providing data and 9 organising the ESA 4th advanced course on radar polarimetry. I am grateful to Prof. Jingfa Zhang, Dr Qisong Jiao and Dr Hongbo Jiang from the Institute of Crustal Dynamics, China Earthquake Administration for 2017 fieldwork and collaborations. Moreover, I am grateful to Amy from the University of Colorado and National Snow and Ice Data Center of USA for providing ICESat data and code. I also gratefully acknowledge Dr Randolph Kirk, Elpitha Howington-Kraus from USGS for providing DEM code. Special mention and thanks must go to Prof. Shiyuan Hu, Prof. Miaozhong Xu, Prof. Haigang Sui and Prof. Kaiming Sun, my former supervisors at Wuhan University, for arousing my initial interest and guiding me into the space photogrammetry, remote sensing and GIS field back in 2005. I also would like to thank my former boss Prof. Yingcheng Li at the Chinese Academy of Surveying and Mapping for constant encouragement and generous support in my life and work from 2009 to 2014. There are too many people at the MSSL, UCL that I would like to say thanks to. Edward Malina, thank you for being there whenever I need your advice, help and everyday lift to MSSL during the second year of my PhD. Jason Hunt, thank you for the kindest help provided during the second year of my PhD too. I am grateful to Denis Gonzalez Caniulef, Ravindra Desai, Zakari Tsiga, Jennifer Y H Chan and Georgina Graham for their friendship, support, help and enjoyable time at Ariel House MSSL the first year when I am in the UK. Moreover, I also like to thank our group members Panagiotis Sidiropoulos, Yu Tao, Said Kharbouche, Edward Malina, Alistair Francis and Divya Persaud, Siting Xiong, Alfiah Rizky Diana Putri, Jacqueline Campbell, George Cann, Daoxi Zhang, Luyi Sun, Josh Veitch-Michaelis, Wil Poole for their help, support, useful discussion and all the good times at MSSL in the last 4 years. I am additionally grateful to Edward Malina, Alistair Francis and Divya Persaud for their time spending on proofreading of several chapters of this thesis.
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