Automatic refocus and feature extraction of single-look complex SAR signatures of vessels

In recent years, spaceborne synthetic aperture radar ( SAR) technology has been considered as a complement to cooperative vessel surveillance systems thanks to its imaging capabilities. In this paper, a processing chain is presented to explore the potential of using basic stripmap single-look complex ( SLC) SAR images of vessels for the automatic extraction of their dimensions and heading. Local autofocus is applied to the vessels' SAR signatures to compensate blurring artefacts in the azimuth direction, improving both their image quality and their estimated dimensions. For the heading, the orientation ambiguities of the vessels' SAR signatures are solved using the direction of their ground-range velocity from the analysis of their Doppler spectra. Preliminary results are provided using five images of vessels from SLC RADARSAT-2 stripmap images. These results have shown good agreement with their respective ground-truth data from Automatic Identification System ( AIS) records at the time of the acquisitions.Postprint (published version

Bayesian statistical analysis of ground-clutter for the relative calibration of dual polarization weather radars

A new data processing methodology, based on the statistical analysis of ground-clutter echoes and aimed at investigating the stability of the weather radar relative calibration, is presented. A Bayesian classification scheme has been used to identify meteorological and/or ground-clutter echoes. The outcome is evaluated on a training dataset using statistical score indexes through the comparison with a deterministic clutter map. After discriminating the ground clutter areas, we have focused on the spatial analysis of robust and stable returns by using an automated region-merging algorithm. The temporal series of the ground-clutter statistical parameters, extracted from the spatial analysis and expressed in terms of percentile and mean values, have been used to estimate the relative clutter calibration and its uncertainty for both co-polar and differential reflectivity. The proposed methodology has been applied to a dataset collected by a C-band weather radar in southern Italy

Electronic scan weather radar: scan strategy and signal processing for volume targets

2013 Fall.Includes bibliographical references.Following the success of the WSR-88D network, considerable effort has been directed toward searching for options for the next generation of weather radar technology. With its superior capability for rapidly scanning the atmosphere, electronically scanned phased array radar (PAR) is a potential candidate. A network of such radars has been recommended for consideration by the National Academies Committee on Weather Radar Technology beyond NEXRAD. While conventional weather radar uses a rotating parabolic antenna to form and direct the beam, a phased array radar superimposes outputs from an array of many similar radiating elements to yield a beam that is scanned electronically. An adaptive scan strategy and advanced signal designs and processing concepts are developed in this work to use PAR effectively for weather observation. An adaptive scan strategy for weather targets is developed based on the space-time variability of the storm under observation. Quickly evolving regions are scanned more often and spatial sampling resolution is matched to spatial scale. A model that includes the interaction between space and time is used to extract spatial and temporal scales of the medium and to define scanning regions. The temporal scale constrains the radar revisit time while the measurement accuracy controls the dwell time. These conditions are employed in a task scheduler that works on a ray-by-ray basis and is designed to balance task priority and radar resources. The scheduler algorithm also includes an optimization procedure for minimizing radar scan time. In this research, a signal model for polarimetric phased array weather radar (PAWR) is presented and analyzed. The electronic scan mechanism creates a complex coupling of horizontal and vertical polarizations that produce the bias in the polarimetric variables retrieval. Methods for bias correction for simultaneous and alternating transmission modes are proposed. It is shown that the bias can be effectively removed; however, data quality degradation occurs at far off boresight directions. The effective range for the bias correction methods is suggested by using radar simulation. The pulsing scheme used in PAWR requires a new ground clutter filtering method. The filter is designed to work with a signal covariance matrix in the time domain. The matrix size is set to match the data block size. The filter's design helps overcome limitations of spectral filtering methods and make efficient use of reducing ground clutter width in PAWR. Therefore, it works on modes with few samples. Additionally, the filter can be directly extended for staggered PRT waveforms. Filter implementation for polarimetric retrieval is also successfully developed and tested for simultaneous and alternating staggered PRT. The performance of these methods is discussed in detail. It is important to achieve high sensitivity for PAWR. The use of low-power solid state transmitters to keep costs down requires pulse compression technique. Wide-band pulse compression filters will partly reduce the system sensitivity performance. A system for sensitivity enhancement (SES) for pulse compression weather radar is developed to mitigate this issue. SES uses a dual-waveform transmission scheme and an adaptive pulse compression filter that is based on the self-consistency between signals of the two waveforms. Using SES, the system sensitivity can be improved by 8 to 10 dB

Data Requirements for Oceanic Processes in the Open Ocean, Coastal Zone, and Cryosphere

The type of information system that is needed to meet the requirements of ocean, coastal, and polar region users was examined. The requisite qualities of the system are: (1) availability, (2) accessibility, (3) responsiveness, (4) utility, (5) continuity, and (6) NASA participation. The system would not displace existing capabilities, but would have to integrate and expand the capabilities of existing systems and resolve the deficiencies that currently exist in producer-to-user information delivery options

Sentinel-1 data exploitation for terrain deformation monitoring

Persistent Scatterer interferometry (PSI) is a group of advanced differential interferometric Synthetic Aperture Radar (SAR) techniques used to measure and monitor terrain deformation. Sentinel-1 has improved the data acquisition throughout and, compared to previous sensors, increased considerably the Differential Interferometric SAR (DInSAR) and PSI deformation monitoring potential. The effect of the refractive atmosphere on the interferometric phase and phase unwrapping ambiguity are two critical issues of InSAR. The low density of Persistent Scatterer (PS) in non-urban areas, another critical issue, has inspired the development of alternative approaches and refinement of the PS chains. Along with the efforts to develop methods to mitigate the three above-mentioned problems, the work presented in this thesis also deals with the presence of a new signal in multilooked interferograms which cannot be explained by noise, atmospheric or earth surface topography changes. This paper describes a method for atmospheric phase screen estimation using rain station weather data and three different data driven procedures to obtain terrain deformation maps. These approaches aim to exploit Sentinel-1 highly coherent interferograms and their short revisit time. The first method called the splitting makes uses of the power spectrum of the interferograms to split the signals into high and low frequency, and following a mutually exclusive consecutive processing chain for the two sets. This approach has resulted in greater density of PSs with decreased phase unwrapping errors. The second approach, called Direct Integration (DI), aims at providing a very fast and straightforward approach to screen wide areas and easily detect active areas. This approach fully exploits the coherent interferograms from the consecutive images provided by Sentinel-1 resulting in a very high sampling density. However, it lacks robustness and its usability lays on the operator experience. The third method, called PSIG (Persistent Scatterer Interferometry Geomatics) short temporal baseline, provides a constrained application of the PSIG chain, the CTTC approach to the PSI. It uses short temporal baseline interferograms and do not assume any deformation model for point selection. It is also quite a straightforward approach and a perfect complement to the direct integration approach. It improves the performances of the standard PSIG approach, increasing the PS density and providing robust measurements. The effectiveness of the approaches is illustrated through analyses performed on different test sites.La técnica Persistent Scatterer Interferometry (PSI) es un grupo de técnicas avanzadas de radar de apertura sintética interferométrica diferencial (SAR) que se utiliza para medir y monitorear losmovimientos del terreno. Sentinel-1 ha mejorado sensiblemente la adquisición de datos y, en comparación con los sensores SAR anteriores, ha aumentado considerablemente el potencial uso de la interferometría diferencial SAR y del PSI para medir y monitorizar desplazamientos del terreno. El efecto de la atmósfera sobre la fase interferométrica y la naturaleza ambigua de esta son dos cuestiones críticas de InSAR. Además, la baja densidad de Persistent Scatterer (PSs) en áreas no urbanas, es otro tema crítico que ha inspirado el desarrollo de enfoques alternativos y el refinamiento de las cadenas PS existentes. Junto con los esfuerzos por desarrollar métodos para mitigar los tres problemas antes mencionados, el trabajo presentado en esta tesis también aborda la presencia de una nueva señal en interferogramas multilooked que no puede explicarse por cambios de ruido, atmosféricos o topográficos de la superficie terrestre. Esta tesis describe un método para la estimación de la fase atmosférica utilizando datos meteorológicos adquiridos in-situ y tres aproximaciones diferentes basadas en datos Sentinel-1 para obtener mapas de deformación del terreno. Estos enfoques tienen como objetivo explotar los interferogramas altamente coherentes proporcionados por Sentinel-1 gracias a su corto tiempo de revisita. El primer método llamado división hace uso de filtros en el dominico frecuencial de los interferogramas para dividir las señales en alta y baja frecuencia, y siguiendo una cadena de procesamiento consecutiva independiente para cada clase. Este enfoque ha dado como resultado una mejora substancial de PS minimizando los errores debidos al desenrollado de fase. El segundo enfoque, llamado Integración Directa (DI), tiene como objetivo proporcionar un enfoque muy rápido y sencillo para examinar áreas amplias y detectar fácilmente áreas activas. Este enfoque aprovecha al máximo los interferogramas coherentes de las imágenes consecutivas proporcionadas por Sentinel-1, lo que da como resultado una densidad de muestreo muy alta. Sin embargo, carece de robustez y su usabilidad depende de la experiencia del operador. El tercer método, llamado PSIG (Persistent Scatterer Interferometry Geomatics) de línea de base temporal corta, proporciona una aplicación restringida de la cadena PSIG, el enfoque CTTC para el PSI. Utiliza interferogramas de línea base temporales cortos y no asume ningún modelo de deformación para la selección de puntos. Su uso es complementario al enfoque de integración directa proporcionando robustez en las zonas. Mejora el rendimiento del enfoque estándar de PSIG, aumentando la densidad de PS y proporcionando mediciones robustas. La efectividad de los enfoques se ilustra a través de análisis realizados en diferentes sitios de prueba.Postprint (published version

Quantitative Analysis of Rapid-Scan Phased Array Weather Radar Benefits and Data Quality Under Various Scan Conditions

Currently, NEXRAD provides weather radar coverage for the contiguous United States. It is believed that a replacement system for NEXRAD will be in place by the year 2040, where a major goal of such a system is to provide improved temporal resolution compared to the 5-10-min updates of NEXRAD. In this dissertation, multiple projects are undertaken to help achieve the goals of improved temporal resolution, and to understand possible scanning strategies and radar designs that can meet the goal of improved temporal resolution while either maintaining (or improving) data quality. Chapter 2 of this dissertation uses a radar simulator to simulate the effect of various scanning strategies on data quality. It is found that while simply reducing the number of pulses per radial decreases data quality, other methods such as beam multiplexing and radar imaging/digital beamforming offer significant promise for improving data quality and/or temporal resolution. Beam multiplexing is found to offer a speedup factor of 1.7-2.9, while transmit beam spoiling by 10 degrees in azimuth can offer speedup factors up to ~4 in some regions. Due to various limitations, it is recommended that these two methods be used judiciously for rapid-scan applications. Chapter 3 attempts to quantify the benefits of a rapid-scan weather radar system for tornado detection. The first goal of Chapter 3 is to track the development of a common tornado signature (tornadic debris signature, or TDS) and relate it to developments in tornado strength. This is the first study to analyze the evolution of common tornado signatures at very high temporal resolution (6 s updates) by using a storm-scale tornado model and a radar emulator. This study finds that the areal extent of the TDS is correlated with both debris availability and with tornado strength. We also find that significant changes in the radar moment variables occur on short (sub-1-min) timescales. Chapter 3 also shows that the calculated improvement in tornado detection latency time (137-207 s) is greater than that provided by theory alone (107 s). Together, the two results from Chapter 3 emphasize the need for sub-1-min updates in some applications such as tornado detection. The ability to achieve these rapid updates in certain situations will likely require a combination of advanced scanning strategies (such as those mentioned in Chapter 2) and adaptive scanning. Chapter 4 creates an optimization-based model to adaptively reallocate radar resources for the purpose of improving data quality. This model is primarily meant as a proof of concept to be expanded to other applications in the future. The result from applying this model to two real-world cases is that data quality is successfully improved in multiple areas of enhanced interest, at the expense of worsening data quality in regions where data quality is not as important. This model shows promise for using adaptive scanning in future radar applications. Together, these results can help the meteorological community understand the needs, challenges, and possible solutions to designing a replacement system for NEXRAD. All of the techniques studied herein either rely upon (or are most easily achieved by) phased array radar (PAR), which further emphasizes the utility of PAR for achieving rapid updates with sufficient data quality. It is hoped that the results in this dissertation will help guide future decisions about requirements and design specifications for the replacement system for NEXRAD

Selection of the key earth observation sensors and platforms focusing on applications for Polar Regions in the scope of Copernicus system 2020-2030

An optimal payload selection conducted in the frame of the H2020 ONION project (id 687490) is presented based on the ability to cover the observation needs of the Copernicus system in the time period 2020–2030. Payload selection is constrained by the variables that can be measured, the power consumption, and weight of the instrument, and the required accuracy and spatial resolution (horizontal or vertical). It involved 20 measurements with observation gaps according to the user requirements that were detected in the top 10 use cases in the scope of Copernicus space infrastructure, 9 potential applied technologies, and 39 available commercial platforms. Additional Earth Observation (EO) infrastructures are proposed to reduce measurements gaps, based on a weighting system that assigned high relevance for measurements associated to Marine for Weather Forecast over Polar Regions. This study concludes with a rank and mapping of the potential technologies and the suitable commercial platforms to cover most of the requirements of the top ten use cases, analyzing the Marine for Weather Forecast, Sea Ice Monitoring, Fishing Pressure, and Agriculture and Forestry: Hydric stress as the priority use cases.Peer ReviewedPostprint (published version

Vehicle Sensing and Communications using LED Headlights to Enhance the Performance of Intelligent Transportation Systems: Proof of Concept, Implementation, and Applications

This project investigates the use of vehicle light-emitting diode (LED) headlamp devices for improving the accuracy and reliability of traffic (sensing and communication) data measurements required for developing effective intelligent transportation systems (ITS) technologies and solutions. Vehicular communication and sensing technologies are mainly based on conventional radio frequency (RF) or laser technologies. These systems suffer from several issues such as RF interference and poor performance in scenarios where the incidence angle between the speed detector and the vehicle is rapidly varying. Introducing a new sensing technology will add diversity to these systems and enhance the reliability of the real-time data. In this project, we proposed and investigated a novel speed estimation sensing system named “Visible Light Detection and Ranging (ViLDAR)” (patent pending). ViLDAR utilizes visible light-sensing technology to measure the variation of the vehicle’s headlamp light intensity to estimate the vehicle speed. Similarly, visible light sensing technology is used for data communication purposes, where the vehicle headlamp is utilized for wireless data transmission purposes. This project outlines the ViLDAR system simulations, implementation including hardware and software components, experimental evaluation in both laboratory and outdoor environments. The experimental measurement settings of the ViLDAR experiments are detailed. Encouraging results for both sensing and communication scenarios are obtained. The outcome of this proof-of-concept study both in the laboratory and outdoor validates the merit of the proposed technology in speed estimation (sensing) and data communication. The outcomes of this project will inspire a wide and diverse range of researchers, scientists and practitioners from the ITS community to explore this new and exciting technology. This project built initial steps in exploring this new sensing and communication modality using vehicle headlamps, leaving open a wide field for exploration and novel research