Ship detection on open sea and coastal environment

Synthetic Aperture Radar (SAR) is a high-resolution ground-mapping technique with the ability to effectively synthesize a large radar antenna by processing the phase of a smaller radar antenna on a moving platform like an airplane or a satellite. SAR images, due to its properties, have been the focus of many applications such as land and sea monitoring, remote sensing, mapping of surfaces, weather forecasting, among many others. Their relevance is increasing on a daily basis, thus it’s crucial to apply the best suitable method or technique to each type of data collected. Several techniques have been published in the literature so far to enhance automatic ship detection using Synthetic Aperture Radar (SAR) images, like multilook imaging techniques, polarization techniques, Constant False Alarm Rate (CFAR) techniques, Amplitude Change Detection (ACD) techniques among many others. Depending on how the information is gathered and processed, each technique presents different performance and results. Nowadays there are several ongoing SAR missions, and the need to improve ship detection, oil-spills or any kind of sea activity is fundamental to preserve and promote navigation safety as well as constant and accurate monitoring of the surroundings, for example, detection of illegal fishing activities, pollution or drug trafficking. The main objective of this MSc dissertation is to study and implement a set of algorithms for automatic ship detection using SAR images from Sentinel-1 due to its characteristics as well as its ease access. The dissertation organization is as follows: Chapter 1 presents a brief introduction to the theme of this dissertation and its aim, as well as its structure; Chapter 2 summarizes a variety of fundamental key points from historical events and developments to the SAR theory, finishing with a summary of some well-known ship detection methods; Chapter 3 presents a basic guideline to choose the best ship detection technique depending on the data type and operational scenario; Chapter 4 focus on the CFAR technique detailing the implemented algorithms. This technique was selected, given the data set available for testing in this work; Chapter 5 presents the results obtained using the implemented algorithms; Chapter 6 presents the conclusions, final remarks and future work

Oil spill and ship detection using high resolution polarimetric X-band SAR data

Among illegal human activities, marine pollution and target detection are the key concern of Maritime Security and Safety. This thesis deals with oil spill and ship detection using high resolution X-band polarimetric SAR (PolSAR). Polarimetry aims at analysing the polarization state of a wave field, in order to obtain physical information from the observed object. In this dissertation PolSAR techniques are suggested as improvement of the current State-of-the-Art of SAR marine pollution and target detection, by examining in depth Near Real Time suitability

Radar Technology

In this book “Radar Technology”, the chapters are divided into four main topic areas: Topic area 1: “Radar Systems” consists of chapters which treat whole radar systems, environment and target functional chain. Topic area 2: “Radar Applications” shows various applications of radar systems, including meteorological radars, ground penetrating radars and glaciology. Topic area 3: “Radar Functional Chain and Signal Processing” describes several aspects of the radar signal processing. From parameter extraction, target detection over tracking and classification technologies. Topic area 4: “Radar Subsystems and Components” consists of design technology of radar subsystem components like antenna design or waveform design

AN ARTIFICIAL INTELLIGENCE APPROACH TO THE PROCESSING OF RADAR RETURN SIGNALS FOR TARGET DETECTION

Most of the operating vessel traffic management systems experience problems, such as track loss and track swap, which may cause confusion to the traffic regulators and lead to potential hazards in the harbour operation. The reason is mainly due to the limited adaptive capabilities of the algorithms used in the detection process. The decision on whether a target is present is usually based on the magnitude of the returning echoes. Such a method has a low efficiency in discriminating between the target and clutter, especially when the signal to noise ratio is low. The performance of radar target detection depends on the features, which can be used to discriminate between clutter and targets. To have a significant improvement in the detection of weak targets, more obvious discriminating features must be identified and extracted. This research investigates conventional Constant False Alarm Rate (CFAR) algorithms and introduces the approach of applying ar1ificial intelligence methods to the target detection problems. Previous research has been unde11aken to improve the detection capability of the radar system in the heavy clutter environment and many new CFAR algorithms, which are based on amplitude information only, have been developed. This research studies these algorithms and proposes that it is feasible to design and develop an advanced target detection system that is capable of discriminating targets from clutters by learning the .different features extracted from radar returns. The approach adopted for this further work into target detection was the use of neural networks. Results presented show that such a network is able to learn particular features of specific radar return signals, e.g. rain clutter, sea clutter, target, and to decide if a target is present in a finite window of data. The work includes a study of the characteristics of radar signals and identification of the features that can be used in the process of effective detection. The use of a general purpose marine radar has allowed the collection of live signals from the Plymouth harbour for analysis, training and validation. The approach of using data from the real environment has enabled the developed detection system to be exposed to real clutter conditions that cannot be obtained when using simulated data. The performance of the neural network detection system is evaluated with further recorded data and the results obtained are compared with the conventional CFAR algorithms. It is shown that the neural system can learn the features of specific radar signals and provide a superior performance in detecting targets from clutters. Areas for further research and development arc presented; these include the use of a sophisticated recording system, high speed processors and the potential for target classification

Ground moving target indication with synthetic aperture radars for maritime surveillance

The explosive growth of shipping traffic all over the World, with around three quarters of the total trade goods and crude oil transported by sea, has raised newly emerging concerns (economical, ecological, social and geopolitical). Geo-information (location and speed) of ocean-going vessels is crucial in the maritime framework, playing a key role in the related environmental monitoring, fisheries management and maritime/coastal security. In this scenario space-based synthetic aperture radar (SAR) remote sensing is a potential tool for globally monitoring the oceans and seas, providing two-dimensional high-resolution imaging capabilities in all-day and all-weather conditions. The combination of ground moving target indication (GMTI) modes with multichannel spaceborne SAR systems represents a powerful apparatus for surveillance of maritime activities. The level of readiness of such a technology for road traffic monitoring is still low, and for the marine scenario is even less mature. Some of the current space-based SAR missions include an experimental GMTI mode with reduced detection capabilities, especially for small and slow moving targets. In this framework, this doctoral dissertation focuses on the study and analysis of the GMTI limitations of current state-of-the-art SAR missions when operating over maritime scenarios and the proposal of novel and optimal multichannel SAR-GMTI architectures, providing subclutter visibility of small (reduced reflectivity) slow moving vessels. This doctoral activity carries out a transversal analysis embracing system-architecture proposal and optimization, processing strategies assessment, performance evaluation, sea/ocean clutter characterization and adequate calibration methodologies suggestion. Firstly, the scarce availability of multichannel SAR-GMTI raw data and the related restrictions to access it have raised the need to implement flexible simulation tools for SAR-GMTI performance evaluation and mission. These simulation tools allow the comparative study and evaluation of the SAR-GMTI mode operated with current SAR missions, showing the reduced ability of these missions to detect small and slow boats in subclutter visibility. Improved performance is achieved with the new multichannel architecture based on non-uniformly distributed receivers (with external deployable antennas), setting the ground for future SAR-GMTI mission development. Some experimental multichannel SAR-GMTI data sets over the sea and acquired with two instruments, airborne F-SAR and spaceborne TerraSAR-X (TSX) platforms, have been processed to evaluate their detection capabilities as well as the adequate processing strategies (including channel balancing). This doctoral activity presents also a preliminary characterization of the sea clutter returns imaged by the spaceborne TSX instrument in a three-level basis, i.e., radiometric, statistical and polarimetric descriptions using experimental polarimetric data. This study has shown that the system-dependent limitations, such as thermal noise and temporal decorrelation, play a key role in the appropriate interpretation of the data and so should be properly included in the physical backscattering models of the sea. Current and most of the upcoming SAR missions are based on active phase array antennas (APAA) technology for the operation of multiple modes of acquisitions. The related calibration is a complex procedure due to the high number of different beams to be operated. Alternative internal calibration methodologies have been proposed and analyzed in the frame of this doctoral thesis. These approaches improved the radiometric calibration performance compared to the conventional ones. The presented formulation of the system errors as well as the proposed alternative strategies set the path to extrapolate the analysis for multichannel SAR systems.L'increment continu del tràfic marítim arreu del món, amb gairebé tres quartes parts del total de mercaderies i cru transportats per mar, porta associats uns impactes canviants a nivell econòmic, ambiental, social i geopolític. La geo-informació (localització i velocitat) dels vaixells té un paper fonamental en el monitoratge ambiental, la gestió de la pesca i la seguretat marítima/costanera. Els radars d'obertura sintètica (SAR, sigles en anglès) embarcats en satèl·lits són una eina molt potent per al monitoratge global dels oceans i dels mars, gràcies a la seva capacitat de generar imatges d'alta resolució amb independència de les condicions meteorològiques i de la llum solar. La detecció de blancs mòbils terrestres (GMTI, sigles en anglès) combinada amb sistemes multicanal SAR és fonamental per a la vigilància de les activitats marítimes. El nivell de maduresa d'aquesta tecnologia per monitorar tràfic rodat és baix, però per al cas marítim encara ho és més. Algunes missions SAR orbitals inclouen el mode GMTI, però amb unes capacitats de detecció reduïdes, especialment per a blancs petits i lents. En aquest marc, la tesi doctoral es centra en l'estudi i anàlisi de les limitacions GMTI dels actuals sistemes SAR operant en entorns marítims, proposant noves configuracions SAR-GMTI multicanal optimitzades per a la detecció de vaixells petits (emmascarats pels retrons radar del mar) i que es mouen lentament. La present dissertació doctoral du a terme un estudi transversal que abasta des de la proposta i optimització de sistemes/configuracions, passant per l'avaluació de les tècniques de processat, fins a l'estudi del rendiment de la missió, caracterització del mar i la valoració de noves metodologies de calibratge. En primer terme, diverses eines de simulació flexibles s'han implementat per poder avaluar les capacitats GMTI de diferents missions tenint en compte la poca disponibilitat de dades multicanal SAR-GMTI. Aquests simuladors permeten l'estudi comparatiu de les capacitats GMTI de les missions SAR orbitals actuals, demostrant les seves reduïdes opcions per identificar vaixells emmascarats pels retorns del mar. En el marc de l'activitat de recerca s'han processat dades experimentals SAR-GMTI multicanal de sistemes aeris (F-SAR) i orbitals (TerraSAR-X), per tal d'avaluar les seves capacitats de detecció de blancs mòbils sobre entorns marítims, proposant les estratègies de processat i calibratge més adients. Com a part de l'activitat de recerca doctoral, s'ha portat a terme una caracterització preliminar dels retorns radar del mar adquirits amb el sensor orbital TerraSAR-X, amb tres nivells d'anàlisi (radiomètric, estadístic i polarimètric). Aquest estudi demostra que aspectes com el soroll tèrmic i la decorrelació temporal, dependents del propi sensor i de l'entorn dinàmic del mar, poden limitar la correcta interpretació de les dades, i per tant, s'han d'incloure en els models físics dels mecanismes de dispersió del mar. Les missions SAR tant actuals com futures es basen en l'explotació de la tecnologia de les agrupacions d'antenes de fase activa (APAA) per operar diferents modes d'adquisició. El procés de calibratge associat és molt complex atès el gran nombre de feixos que es poden utilitzar. En el marc de la tesi doctoral s'han proposat i avaluat metodologies alternatives de calibratge intern per aquests sistemes, amb un millor rendiment en comparació amb les tècniques convencionals. Aquestes estratègies de calibratge, juntament amb la corresponent formulació dels errors de sistema, estableixen les bases per a l'estudi i avaluació en sistemes multicanal SA

Ocean Remote Sensing with Synthetic Aperture Radar

The ocean covers approximately 71% of the Earth’s surface, 90% of the biosphere and contains 97% of Earth’s water. The Synthetic Aperture Radar (SAR) can image the ocean surface in all weather conditions and day or night. SAR remote sensing on ocean and coastal monitoring has become a research hotspot in geoscience and remote sensing. This book—Progress in SAR Oceanography—provides an update of the current state of the science on ocean remote sensing with SAR. Overall, the book presents a variety of marine applications, such as, oceanic surface and internal waves, wind, bathymetry, oil spill, coastline and intertidal zone classification, ship and other man-made objects’ detection, as well as remotely sensed data assimilation. The book is aimed at a wide audience, ranging from graduate students, university teachers and working scientists to policy makers and managers. Efforts have been made to highlight general principles as well as the state-of-the-art technologies in the field of SAR Oceanography

Aeronautical engineering: A continuing bibliography with indexes (supplement 292)

This bibliography lists 675 reports, articles, and other documents recently introduced into the NASA scientific and technical information system database. Subject coverage includes the following: design, construction and testing of aircraft and aircraft engines; aircraft components, equipment, and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics

COMBAT SYSTEMS Volume 1. Sensor Elements Part I. Sensor Functional Characteristics

This document includes: CHAPTER 1. SIGNATURES, OBSERVABLES, & PROPAGATORS. CHAPTER 2. PROPAGATION OF ELECTROMAGNETIC RADIATION. I. – FUNDAMENTAL EFFECTS. CHAPTER 3. PROPAGATION OF ELECTROMAGNETIC RADIATION. II. – WEATHER EFFECTS. CHAPTER 4. PROPAGATION OF ELECTROMAGNETIC RADIATION. III. – REFRACTIVE EFFECTS. CHAPTER 5. PROPAGATION OF ELECTROMAGNETIC RADIATION IV. – OTHER ATMOSPHERIC AND UNDERWATER EFFECTS. CHAPTER 6. PROPAGATION OF ACOUSTIC RADIATION. CHAPTER 7. NUCLEAR RADIATION: ITS ORIGIN AND PROPAGATION. CHAPTER 8. RADIOMETRY, PHOTOMETRY, & RADIOMETRIC ANALYSIS. CHAPTER 9. SENSOR FUNCTIONS. CHAPTER 10. SEARCH. CHAPTER 11. DETECTION. CHAPTER 12. ESTIMATION. CHAPTER 13. MODULATION AND DEMODULATION. CHAPTER 14. IMAGING AND IMAGE-BASED PERCEPTION. CHAPTER 15. TRACKING. APPENDIX A. UNITS, PHYSICAL CONSTANTS, AND USEFUL CONVERSION FACTORS. APPENDIX B. FINITE DIFFERENCE AND FINITE ELEMENT TECHNIQUES. APPENDIX C. PROBABILITY AND STATISTICS. INDEX TO VOLUME 1. Note by author: Note: Boldface entries in the table of contents are not yet completed