Synthetic aperture radar/LANDSAT MSS image registration

Algorithms and procedures necessary to merge aircraft synthetic aperture radar (SAR) and LANDSAT multispectral scanner (MSS) imagery were determined. The design of a SAR/LANDSAT data merging system was developed. Aircraft SAR images were registered to the corresponding LANDSAT MSS scenes and were the subject of experimental investigations. Results indicate that the registration of SAR imagery with LANDSAT MSS imagery is feasible from a technical viewpoint, and useful from an information-content viewpoint

An introduction to the interim digital SAR processor and the characteristics of the associated Seasat SAR imagery

Basic engineering data regarding the Interim Digital SAR Processor (IDP) and the digitally correlated Seasat synthetic aperature radar (SAR) imagery are presented. The correlation function and IDP hardware/software configuration are described, and a preliminary performance assessment presented. The geometric and radiometric characteristics, with special emphasis on those peculiar to the IDP produced imagery, are described

Elevation and Deformation Extraction from TomoSAR

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 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

Space Remote Sensing and Detecting Systems of Oceangoing Ships

This paper introduces the implementation of space remote sensing and detecting systems of oceangoing ships as an alternative to the Radio – Automatic Identification System (R-AIS), Satellite – Automatic Identification System (S-AIS), Long Range Identification and Tracking (LRIT), and other current vessel tracking systems. In this paper will be not included  a new project known as a Global Ship Tracking (GST) as an autonomous and discrete satellite network designed by the Space Science Centre (SSC) for research and postgraduate studies in Satellite Communication, Navigation and Surveillance (CNS) at Durban University of Technology (DUT). The ship detection from satellite remote sensing imagery system is a crucial application for maritime safety and security, which includes among others ship tracking, detecting and traffic surveillance, oil spill detection service, and discharge control, sea pollution monitoring, sea ice monitoring service, and protection against illegal fisheries activities. The establishment of a modern sea surface and ships monitoring system needs enhancement of the Satellite Synthetic Aperture Radar (SSAR) that is here discussed as a modern observation infrastructure integrated with Ships Surveillance and Detecting via SSAR TerraSAR-X Spacecraft, Ships Surveillance and Detecting via SSAR Radarsat Spacecraft and Vessels Detecting System (VDS) via SSAR

Theory and Design of a Highly Compressed Dropped-Channel Polarimetric Synthetic Aperture Radar

Compressed sensing (CS) is a recent mathematical technique that leverages the sparsity in certain sets of data to solve an underdetermined system and recover a full set of data from a sub-Nyquist set of measurements of the data. Given the size and sparsity of the data, radar has been a natural choice to apply compressed sensing to, typically in the fast-time and slow-time domains. Polarimetric synthetic aperture radar (PolSAR) generates a particularly large amount of data for a given scene; however, the data tends to be sparse. Recently a technique was developed to recover a dropped PolSAR channel by leveraging antenna crosstalk information and using compressed sensing. In this dissertation, we build upon the initial concept of the dropped-channel PolSAR CS in three ways. First, we determine a metric which relates the measurement matrix to the l2 recovery error. The new metric is necessary given the deterministic nature of the measurement matrix. We then determine a range of antenna crosstalk required to recover a dropped PolSAR channel. Second, we propose a new antenna design that incorporates the relatively high levels of crosstalk required by a dropped-channel PolSAR system. Finally, we integrate fast- and slow-time compression schemes into the dropped-channel model in order to leverage sparsity in additional PolSAR domains and overall increase the compression ratio. The completion of these research tasks has allowed a more accurate description of a PolSAR system that compresses in fast-time, slow-time, and polarization; termed herein as highly compressed PolSAR. The description of a highly compressed PolSAR system is a big step towards the development of prototype hardware in the future

Time Series Analysis of Surface Deformation Associated With Fluid Injection and Induced Seismicity in Timpson, Texas Using DInSAR Methods

In recent years, a rise in unconventional oil and gas production in North America has been linked to an increase in seismicity rate in these regions (Ellsworth, 2013). As fluid is pumped into deep formations, the state of stress within the subsurface changes, potentially reactivating pre-existing faults and/or causing subsidence or uplift of the surface. Therefore, hydraulic fracturing and/or fluid disposal injection can significantly increase the seismic hazard to communities and structures surrounding the injection sites (Barnhart et al., 2014). On 17th May 2012 an Mw4.8 earthquake occurred near Timpson, TX and has been linked with wastewater injection operations in the area (Shirzaei et al., 2016). This study aims to spatiotemporally relate, wastewater injection operations to seismicity near Timpson using differential interferometric synthetic aperture radar (DInSAR) analysis. Results are presented as a set of time series, produced using the Multidimensional Small Baseline Subset (MSBAS) InSAR technique, revealing two-dimensional surface deformation

First Analyses of Sentinel-1 Images for Maritime Surveillance

Sentinel-1 is the European Synthetic Aperture Radar (SAR) satellite operational since 3 October 2014. The SAR’s characteristics should make it suitable for maritime surveillance (ship detection), and it will routinely collect a large amount of maritime imagery over European and global seas. After its launch in April 2014, preliminary data have been made available to limited users in the satellite’s commissioning phase, and since the start of the operational phase data are available to the general public. These early data have been used to assess the quality of Sentinel-1 images and their suitability for ship detection. This was partly done by using the JRC’s ship detection software SUMO, after adaptation to ingest and process Sentinel-1 data. It is found that the sensor lives up to its specifications, thereby making it very useful for maritime surveillance thanks to its combination of wide swath and low noise at the medium resolution with which it will mostly be operated (“IW” and “EW” modes).JRC.G.3-Maritime affair