Single-pass polarimetric SAR interferometry for vessel classification

This paper presents a novel method for vessel classification based on single-pass polarimetric synthetic aperture radar (SAR) interferometry. It has been developed according to recent ship scattering studies that show that the polarimetric response of many types of vessels can be described by trihedral- and dihedral-like mechanisms. The adopted methodology is quite simple. The input interferometric data are decomposed in terms of the Pauli basis, and hence, one height image is derived for each simple mechanism. Then, the local maxima of these images are isolated, and a 3-D map of scatters is generated. The correlation of this map with the scattering distribution expected for a set of reference ships provides the final classification decision. The performance of the proposed method has been tested with the orbital SAR simulator developed at Universitat PolitÈcnica de Catalunya. Different vessel models have been processed with a sensor configuration similar to the incoming TanDEM-X system. The analysis of diverse vessel bearings, vessel speeds, and sea states shows that the map of scatters matches reasonably the geometry of ships allowing a correct identification even for adverse environmental conditions.Peer Reviewe

SARCASTIC v2.0 - High-performance SAR simulation for next-generation ATR systems

Synthetic aperture radar has been a mainstay of the remote sensing field for many years, with a wide range of applications across both civilian and military contexts. However, the lack of openly available datasets of comparable size and quality to those available for optical imagery has severely hampered work on open problems such as automatic target recognition, image understanding and inverse modelling. This paper presents a simulation and analysis framework based on the upgraded SARCASTIC v2.0 engine, along with a selection of case studies demonstrating its application to well-known and novel problems. In particular, we demonstrate that SARCASTIC v2.0 is capable of supporting complex phase-dependent processing such as interferometric height extraction whilst maintaining near-realtime performance on complex scenes

Innovative Techniques for the Retrieval of Earth’s Surface and Atmosphere Geophysical Parameters: Spaceborne Infrared/Microwave Combined Analyses

With the advent of the first satellites for Earth Observation: Landsat-1 in July 1972 and ERS-1 in May 1991, the discipline of environmental remote sensing has become, over time, increasingly fundamental for the study of phenomena characterizing the planet Earth. The goal of environmental remote sensing is to perform detailed analyses and to monitor the temporal evolution of different physical phenomena, exploiting the mechanisms of interaction between the objects that are present in an observed scene and the electromagnetic radiation detected by sensors, placed at a distance from the scene, operating at different frequencies. The analyzed physical phenomena are those related to climate change, weather forecasts, global ocean circulation, greenhouse gas profiling, earthquakes, volcanic eruptions, soil subsidence, and the effects of rapid urbanization processes. Generally, remote sensing sensors are of two primary types: active and passive. Active sensors use their own source of electromagnetic radiation to illuminate and analyze an area of interest. An active sensor emits radiation in the direction of the area to be investigated and then detects and measures the radiation that is backscattered from the objects contained in that area. Passive sensors, on the other hand, detect natural electromagnetic radiation (e.g., from the Sun in the visible band and the Earth in the infrared and microwave bands) emitted or reflected by the object contained in the observed scene. The scientific community has dedicated many resources to developing techniques to estimate, study and analyze Earth’s geophysical parameters. These techniques differ for active and passive sensors because they depend strictly on the type of the measured physical quantity. In my P.h.D. work, inversion techniques for estimating Earth’s surface and atmosphere geophysical parameters will be addressed, emphasizing methods based on machine learning (ML). In particular, the study of cloud microphysics and the characterization of Earth’s surface changes phenomenon are the critical points of this work

GNSS transpolar earth reflectometry exploriNg system (G-TERN): mission concept

The global navigation satellite system (GNSS) Transpolar Earth Reflectometry exploriNg system (G-TERN) was proposed in response to ESA's Earth Explorer 9 revised call by a team of 33 multi-disciplinary scientists. The primary objective of the mission is to quantify at high spatio-temporal resolution crucial characteristics, processes and interactions between sea ice, and other Earth system components in order to advance the understanding and prediction of climate change and its impacts on the environment and society. The objective is articulated through three key questions. 1) In a rapidly changing Arctic regime and under the resilient Antarctic sea ice trend, how will highly dynamic forcings and couplings between the various components of the ocean, atmosphere, and cryosphere modify or influence the processes governing the characteristics of the sea ice cover (ice production, growth, deformation, and melt)? 2) What are the impacts of extreme events and feedback mechanisms on sea ice evolution? 3) What are the effects of the cryosphere behaviors, either rapidly changing or resiliently stable, on the global oceanic and atmospheric circulation and mid-latitude extreme events? To contribute answering these questions, G-TERN will measure key parameters of the sea ice, the oceans, and the atmosphere with frequent and dense coverage over polar areas, becoming a “dynamic mapper”of the ice conditions, the ice production, and the loss in multiple time and space scales, and surrounding environment. Over polar areas, the G-TERN will measure sea ice surface elevation (<;10 cm precision), roughness, and polarimetry aspects at 30-km resolution and 3-days full coverage. G-TERN will implement the interferometric GNSS reflectometry concept, from a single satellite in near-polar orbit with capability for 12 simultaneous observations. Unlike currently orbiting GNSS reflectometry missions, the G-TERN uses the full GNSS available bandwidth to improve its ranging measurements. The lifetime would be 2025-2030 or optimally 2025-2035, covering key stages of the transition toward a nearly ice-free Arctic Ocean in summer. This paper describes the mission objectives, it reviews its measurement techniques, summarizes the suggested implementation, and finally, it estimates the expected performance.Peer ReviewedPostprint (published version

An Unsupervised Generative Neural Approach for InSAR Phase Filtering and Coherence Estimation

Phase filtering and pixel quality (coherence) estimation is critical in producing Digital Elevation Models (DEMs) from Interferometric Synthetic Aperture Radar (InSAR) images, as it removes spatial inconsistencies (residues) and immensely improves the subsequent unwrapping. Large amount of InSAR data facilitates Wide Area Monitoring (WAM) over geographical regions. Advances in parallel computing have accelerated Convolutional Neural Networks (CNNs), giving them advantages over human performance on visual pattern recognition, which makes CNNs a good choice for WAM. Nevertheless, this research is largely unexplored. We thus propose "GenInSAR", a CNN-based generative model for joint phase filtering and coherence estimation, that directly learns the InSAR data distribution. GenInSAR's unsupervised training on satellite and simulated noisy InSAR images outperforms other five related methods in total residue reduction (over 16.5% better on average) with less over-smoothing/artefacts around branch cuts. GenInSAR's Phase, and Coherence Root-Mean-Squared-Error and Phase Cosine Error have average improvements of 0.54, 0.07, and 0.05 respectively compared to the related methods.Comment: to be published in a future issue of IEEE Geoscience and Remote Sensing Letter

Geosynchronous synthetic aperture radar : design and applications

Synthetic Aperture Radar (SAR) imaging from geosynchronous orbit has significant potential advantages over conventional low-Earth orbit (LEO) radars, but also challenges to overcome. This thesis investigates both active and passive geosynchronous SAR configurations, presenting their different features and advantages. Following a system design trade-off that involved phase uncertainties, link budget, frequency and integration time, an L band bi-static configuration with 8-hour integration time that reuses the signal from a non-cooperative transmitter has been presented as a suitable solution. Cranfield Space Research Centre looked into this configuration and proposed the GeoSAR concept, an L band bi-static SAR based on the concept by Prati et al. (1998). It flies along a circular ground track orbit, reuses the signal coming from a noncooperative transmitter in GEO and achieves a spatial resolution of about 100 m. The present research contributes to the GeoSAR concept exploring the implications due to the 8-hour integration time and providing insights about its performance and its possible fields of application. Targets such as canopies change their backscattered phase on timescales of seconds due to their motion. On longer time scales, changes in dielectric properties of targets, Earth tides and perturbations in the structure of the atmosphere contribute to generate phase fluctuations in the collected signals. These phenomena bring temporal decorrelation and cause a reduction in SAR coherent integration gain. They have to be compensated for if useful images are to be provided. A SAR azimuth simulator has been developed to study the influence of temporal decorrelation on GeoSAR point spread function. The analysis shows that ionospheric delay is the major source of decorrelation; other effects, such as tropospheric delay and Earth tides, have to be dealt with but appear to be easier to handle. Two different options for GeoSAR interferometry have been discussed. The system is well suited to differential interferometry, due to the short perpendicular baseline induced by the geometry. A GeoSAR has advantages over a Low Earth Orbit (LEO) SAR system to monitor processes with significant variability over daily or shorter timescales (e.g. soil moisture variation). This potential justifies further study of the concept.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Subsurface radar imaging from space

© Cranfield University, 2018Ground Penetrating Radar (GPR) and Synthetic Aperture Radar (SAR) are two widely used techniques for acquiring radar images. GPR, as its name suggests, produces radar images of the below ground environment. SAR is a remote sensing technique which allows moving radar systems to produce radar images with dramatically improved resolutions over conventional radar systems. Despite their benefits, both GPR and SAR suffer from certain limitations. In the case of GPR, the radar system has to be in close proximity with the subsurface volume being surveyed, which limits the process to relatively small areas that are easily accessible. SAR allows large areas to be surveyed rapidly from large distances, but cannot distinguish buried objects from surface objects. This thesis focuses on a radar technique that offers the opportunity to overcome these limitations and allow subsurface radar imaging of large areas using radar data gathered by remote sensing systems. This novel technique is known as Virtual Bandwidth SAR (VB-SAR). VB-SAR utilises changes in soil moisture over a series of SAR images to differentiate buried objects from objects on the surface. In addition to this differentiation, VB-SAR also allows extremely high (centimetre scale) subsurface range resolutions to be obtained from SAR images with range resolutions measured in metres. This research has experimentally demonstrated the basic feasibility of performing remote subsurface radar imaging with the VB-SAR scheme. Within the laboratory environment a buried target has been successfully imaged using VB-SAR and the fundamentals of VB-SAR have been verified. Dramatic increases in subsurface range resolutions have been demonstrated, as has the ability of the VB-SAR scheme to work correctly over a range of radar frequencies, observation angles and polarisations. This laboratory work has been enabled by use of the Tomographic Profiling (TP) imaging scheme. TP is a synthetic aperture based imaging algorithm, but unlike conventional SAR TP produces images with a constant look angle over the entire imaging scene. This enabled the performance of the VB-SAR imaging scheme to be easily evaluated over a range of look angles using a single radar dataset and simplified the experimental setup. In addition to the experimental work, simulation exercises have been conducted and image processors have been implemented. Simulation, using a simulator created as part of this work, has allowed testing of the VB-SAR scheme in a range of scenarios (sidelooking SAR, different soils, multiple buried targets). The image processor work has implemented a high performance TP processor and a practical VB-SAR imager

Geosynchronous synthetic aperture radar : design and applications

Synthetic Aperture Radar (SAR) imaging from geosynchronous orbit has significant potential advantages over conventional low-Earth orbit (LEO) radars, but also challenges to overcome. This thesis investigates both active and passive geosynchronous SAR configurations, presenting their different features and advantages. Following a system design trade-off that involved phase uncertainties, link budget, frequency and integration time, an L band bi-static configuration with 8-hour integration time that reuses the signal from a non-cooperative transmitter has been presented as a suitable solution. Cranfield Space Research Centre looked into this configuration and proposed the GeoSAR concept, an L band bi-static SAR based on the concept by Prati et al. (1998). It flies along a circular ground track orbit, reuses the signal coming from a noncooperative transmitter in GEO and achieves a spatial resolution of about 100 m. The present research contributes to the GeoSAR concept exploring the implications due to the 8-hour integration time and providing insights about its performance and its possible fields of application. Targets such as canopies change their backscattered phase on timescales of seconds due to their motion. On longer time scales, changes in dielectric properties of targets, Earth tides and perturbations in the structure of the atmosphere contribute to generate phase fluctuations in the collected signals. These phenomena bring temporal decorrelation and cause a reduction in SAR coherent integration gain. They have to be compensated for if useful images are to be provided. A SAR azimuth simulator has been developed to study the influence of temporal decorrelation on GeoSAR point spread function. The analysis shows that ionospheric delay is the major source of decorrelation; other effects, such as tropospheric delay and Earth tides, have to be dealt with but appear to be easier to handle. Two different options for GeoSAR interferometry have been discussed. The system is well suited to differential interferometry, due to the short perpendicular baseline induced by the geometry. A GeoSAR has advantages over a Low Earth Orbit (LEO) SAR system to monitor processes with significant variability over daily or shorter timescales (e.g. soil moisture variation). This potential justifies further study of the concept.EThOS - Electronic Theses Online ServiceGBUnited Kingdo