257 research outputs found

    Three-Dimensional Nepal Earthquake Displacement Using Hybrid Genetic Algorithm Phase Unwrapping from Sentinel-1A Satellite

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    Introduction: Geophysicists had forewarned for decades that Nepal was exposed to a deadly earthquake, exceptionally despite its geology, urbanization and architecture. Gorkha earthquake is the most horrible natural disaster to crash into Nepal since the 1934 Nepal-Bihar earthquake. Gorkha earthquake occurred on April 25, 2015, at 11:56 NST and killed more than 10,000 people and injured more than 23,000 population. Objective: The main objective of this work is to utilize hybrid genetic algorithm for three-dimensional phase unwrapping of Nepal earthquake displacement using Sentinel-1A satellite. The three-dimensional best-path avoiding singularity loops (3DBPASL) algorithm was implemented to perform 3D Sentinel-1A satellite phase unwrapping. The hybrid genetic algorithm (HGA) was used to achieve 3DBPASL phase matching. Advancely, the errors in phase decorrelation were reduced by optimization of 3DBPASL using HGA. Results: The findings indicate a few cm of ground deformation and vertical northern of Kathmandu. Approximately, an area of 12,000 km2 has been drifted also the northern of Kathmandu. Further, each fringe of colour represents about 2.5 cm of deformation. The large amount of fringes indicates a large deformation pattern with ground motions of 3 m. Conclusion: In conclusion, HGA can be used to produce accurate 3D quake deformation using Sentinel-1A satellite

    Joint multi-baseline SAR interferometry

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    We propose a technique to provide interferometry by combining multiple images of the same area. This technique differs from the multi-baseline approach in literature as (a) it exploits all the images simultaneously, (b) it performs a spectral shift preprocessing to remove most of the decorrelation, and (c) it exploits distributed targets. The technique is mainly intended for DEM generation at centimetric accuracy, as well as for differential interferometry. The problem is framed in the contest of single-input multiple-output (SIMO) channel estimation via the cross-relations (CR) technique and the resulting algorithm provides significant improvements with respect to conventional approaches based either on independent analysis of single interferograms or multi-baselines phase analysis of single pixels of current literature, for those targets that are correlated in all the images, like for long-term coherent areas, or for acquisitions taken with a short revisit time (as those gathered with future satellite constellations)

    Multistatic SAR Imaging: Comparison of Simulation Results and Experimental Data

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    Synthetic aperture radar (SAR) systems in a multistatic configuration are a promising candidate for future Earth observation and reconnaissance radar systems. They overcome the sampling constraints inherent to single-channel SAR systems. Thus, a multistatic SAR system enables the acquisition of high-resolution images while maintaining wide-swath coverage. Employing several small satellites instead of a single large one, a cost-efficient system with graceful degradation characteristics can be envisaged. Additionally, such a constellation or swarm of sensors offers interferometric and tomographic capabilities, which a single-satellite system is not able to provide. This paper shows results of multistatic experiments obtained with TerraSAR-X and TanDEM-X and compares these results with theoretical simulations. The key parameters analyzed are the Doppler spectrum and the azimuth ambiguity suppression

    Spaceborne Polarimetric SAR Interferometry: Performance Analysis and Mission Concepts

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    Spaceborne polarimetric SAR interferometry enables quantitative measurements of important bio- and geophysical parameters of the Earth surface on a global scale. We will first give a short review about actual and planned spaceborne SAR missions that can provide the observation space required for the derivation of Pol-InSAR products. This overview includes both repeat pass mission scenarios like ALOS/PalSAR, TerraSAR-L and Radarsat II, as well as single-pass mission scenarios like a fully-polarimetric Interferometric Cartwheel or TanDEM- X. The Pol-InSAR performance of the suggested mission scenarios will then be analysed by introducing the new concept of a phase tube. This concept enables an optimization of the system parameters and a quantitative comparison between different sensor configurations. The performance analysis for the investigated repeat pass mission scenarios reveals that major limitations have to be expected from temporal decorrelation. Some suggestions will be made to alleviate this performance loss by appropriate orbit refinement. Furthermore, important aspects in the design of future Pol-InSAR sensors will be addressed and we demonstrate the potential benefits arising from the use of bi- and multistatic single pass sensor configurations

    Sparsity-driven coupled imaging and autofocusing for interferometric SAR

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    In this thesis, we present a new joint image enhancement and reconstruction method and a software processing tool for SAR Interferometry. First, we propose a sparsity-driven method for coupled image formation and autofocusing based on multi-channel data collected in interferometric synthetic aperture radar (IfSAR). Relative phase between SAR images contains valuable information. For example, it can be used to estimate the height of the scene in SAR Interferometry. However, this relative phase could be degraded when independent enhancement methods are used over SAR image pairs. Previously, Ramakrishnan, Ertin, and Moses proposed a coupled multi-channel image enhancement technique, based on a dual descent method, which exhibits better performance in phase preservation compared to independent enhancement methods. Their work involves a coupled optimization formulation that uses a sparsity enforcing penalty term as well as a constraint tying the multichannel images together to preserve the cross-channel information. In addition to independent enhancement, the relative phase between the acquisitions can be degraded due to other factors as well, such as platform location uncertainties, leading to phase errors in the data and defocusing in the formed imagery. The performance of airborne SAR systems can be affected severely by such errors. We ii propose an optimization formulation that combines Ramakrishnan et al.'s coupled IfSAR enhancement method with the sparsity-driven autofocus (SDA) approach of Önhon and Çetin to alleviate the effects of phase errors due to motion errors in the context of IfSAR imaging. Our method solves the joint optimization problem with a Lagrangian optimization method iteratively. In our preliminary experimental analysis, we have obtained results of our method on synthetic SAR images and compared its performance to existing methods. As a second contribution of this thesis, we have developed a software toolbox for end-to-end interferometric SAR processing. This toolbox is capable of performing the fundamental steps of SAR Interferometry Processing. The thesis contains the detailed explanation of the algorithms implemented in the SAR Interferometry Toolbox. Test results are also provided to demonstrate the performance of the Toolbox under different scenarios

    Interferometric Synthetic Aperture Sonar Signal Processing for Autonomous Underwater Vehicles Operating Shallow Water

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    The goal of the research was to develop best practices for image signal processing method for InSAS systems for bathymetric height determination. Improvements over existing techniques comes from the fusion of Chirp-Scaling a phase preserving beamforming techniques to form a SAS image, an interferometric Vernier method to unwrap the phase; and confirming the direction of arrival with the MUltiple SIgnal Channel (MUSIC) estimation technique. The fusion of Chirp-Scaling, Vernier, and MUSIC lead to the stability in the bathymetric height measurement, and improvements in resolution. This method is computationally faster, and used less memory then existing techniques

    Radar Imaging in Challenging Scenarios from Smart and Flexible Platforms

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