A Priori Knowledge-Based Post-Doppler STAP for Traffic Monitoring with Airborne Radar

Die Verkehrsüberwachung gewinnt aufgrund des weltweiten Anstiegs der Verkehrsteilnehmer immer mehr an Bedeutung. Sicherer und effizierter Straßenverkehr erfordert detaillierte Verkehrsinformationen. Häufig sind diese lediglich stationär, räumlich stark begrenzt und meist nur auf Hauptverkehrsstraßen verfügbar. In dieser Hinsicht ist ein Ausfall des Telekommunikationsnetzes, beispielsweise im Falle einer Katastrophe, und der damit einhergehende Informationsverlust als kritisch einzustufen. Flugzeuggetragene Radarsysteme mit synthetischer Apertur (eng. Synthetic Aperture Radar - SAR) können für dieses Szenario eine Lösung darstellen, da sie großflächig hochauflösende Bilder generieren können, unabhängig von Tageslicht und Witterungsbedingungen. Sie ermöglichen aufgrund dieser Charakteristik die Detektion von Bewegtzielen am Boden (eng. ground moving target indication – GMTI). Moderne GMTI-Algorithmen und -Systeme, die prinzipiell für die Verkehrsüberwachung verwendbar sind, wurden in der Literatur bereits diskutiert. Allerdings ist die Robustheit dieser Systeme oft mit hohen Kosten, hoher Hardwarekomplexität und hohem Rechenaufwand verbunden. Diese Dissertation stellt einen neuartigen GMTI-Prozessor vor, der auf dem Radar-Mehrkanalverfahren post-Doppler space-time adaptive processing (PD STAP) basiert. Durch die Überlagerung einer Straßenkarte mit einem digitalen Höhenmodell ist es mithilfe des PD STAP möglich, Falschdetektionen zu erkennen und auszuschließen sowie die detektierten Fahrzeuge ihren korrekten Straßenpositionen zu zuordnen. Die präzisen Schätzungen von Position, Geschwindigkeit und Bewegungsrichtung der Fahrzeuge können mit vergleichsweise geringerer Hardware-Komplexität zu niedrigeren Kosten durchgeführt werden. Ferner wird im Rahmen dieser Arbeit ein effizienter Datenkalibrierungsalgorithmus erläutert, der das Ungleichgewicht zwischen den Empfangskanälen sowie die Variation des Dopplerschwerpunkts über Entfernung und Azimut korrigiert und so das Messergebnis verbessert. Darüber hinaus werden neue und automatisierte Strategien zur Erhebung von Trainingsdaten vorgestellt, die für die Schätzung der Clutter-Kovarianzmatrix wegen ihres direkten Einflusses auf die Clutter-Unterdrückung und Zieldetektion essentiell für PD STAP sind. Der neuartige PD STAP Prozessor verfügt über drei verschiedene Betriebsarten, die für militärische und zivile Anwendungen geeignet sind, darunter ein schneller Verarbeitungsalgorithmus der das Potential für eine zukünftige Echtzeit-Verkehrsüberwachung hat. Alle Betriebsarten wurden erfolgreich mit Radar-Mehrkanaldaten des flugzeuggetragenen F-SAR-Radarsensors des DLR getestet

The University Defence Research Collaboration In Signal Processing

This chapter describes the development of algorithms for automatic detection of anomalies from multi-dimensional, undersampled and incomplete datasets. The challenge in this work is to identify and classify behaviours as normal or abnormal, safe or threatening, from an irregular and often heterogeneous sensor network. Many defence and civilian applications can be modelled as complex networks of interconnected nodes with unknown or uncertain spatio-temporal relations. The behavior of such heterogeneous networks can exhibit dynamic properties, reflecting evolution in both network structure (new nodes appearing and existing nodes disappearing), as well as inter-node relations. The UDRC work has addressed not only the detection of anomalies, but also the identification of their nature and their statistical characteristics. Normal patterns and changes in behavior have been incorporated to provide an acceptable balance between true positive rate, false positive rate, performance and computational cost. Data quality measures have been used to ensure the models of normality are not corrupted by unreliable and ambiguous data. The context for the activity of each node in complex networks offers an even more efficient anomaly detection mechanism. This has allowed the development of efficient approaches which not only detect anomalies but which also go on to classify their behaviour

The University Defence Research Collaboration In Signal Processing: 2013-2018

Signal processing is an enabling technology crucial to all areas of defence and security. It is called for whenever humans and autonomous systems are required to interpret data (i.e. the signal) output from sensors. This leads to the production of the intelligence on which military outcomes depend. Signal processing should be timely, accurate and suited to the decisions to be made. When performed well it is critical, battle-winning and probably the most important weapon which you’ve never heard of. With the plethora of sensors and data sources that are emerging in the future network-enabled battlespace, sensing is becoming ubiquitous. This makes signal processing more complicated but also brings great opportunities. The second phase of the University Defence Research Collaboration in Signal Processing was set up to meet these complex problems head-on while taking advantage of the opportunities. Its unique structure combines two multi-disciplinary academic consortia, in which many researchers can approach different aspects of a problem, with baked-in industrial collaboration enabling early commercial exploitation. This phase of the UDRC will have been running for 5 years by the time it completes in March 2018, with remarkable results. This book aims to present those accomplishments and advances in a style accessible to stakeholders, collaborators and exploiters

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

Multi-attribute tradespace exploration for survivability

Thesis (Ph. D.)--Massachusetts Institute of Technology, Engineering Systems Division, 2009.Cataloged from PDF version of thesis.Includes bibliographical references (p. 235-249).Survivability is the ability of a system to minimize the impact of a finite-duration disturbance on value delivery (i.e., stakeholder benefit at cost), achieved through (1) the reduction of the likelihood or magnitude of a disturbance, (2) the satisfaction of a minimally acceptable level of value delivery during and after a disturbance, and/or (3) a timely recovery. Traditionally specified as a requirement in military systems, survivability is an increasingly important consideration for all engineering systems given the proliferation of natural and artificial threats. Although survivability is an emergent system property that arises from interactions between a system and its environment, conventional approaches to survivability engineering are reductionist in nature. Furthermore, current methods neither accommodate dynamic threat environments nor facilitate stakeholder communication for conducting trade-offs among system lifecycle cost, mission utility, and operational survivability. Multi-Attribute Tradespace Exploration (MATE) for Survivability is introduced as a system analysis methodology to improve the generation and evaluation of survivable alternatives during conceptual design. MATE for Survivability applies decision theory to the parametric modeling of thousands of design alternatives across representative distributions of disturbance environments. To improve the generation of survivable alternatives, seventeen empirically-validated survivability design principles are introduced. The general set of design principles allows the consideration of structural and behavioral strategies for mitigating the impact of disturbances over the lifecycle of a given encounter.(cont.) To improve the evaluation of survivability, value-based metrics are introduced for the assessment of survivability as a dynamic, continuous, and path-dependent system property. Two of these metrics, time-weighted average utility loss and threshold availability, are used to evaluate survivability based on the relationship between stochastic utility trajectories of system state and stakeholder expectations across nominal and perturbed environments. Finally, the survivability "tear(drop)" tradespace is introduced to enable the identification of inherently survivable architectures that efficiently balance performance metrics of cost, utility, and survivability. The internal validity and prescriptive value of the design principles, metrics, and tradespaces comprising MATE for Survivability are established through applications to the designs of an orbital transfer vehicle and a satellite radar system.by Matthew G. Richards.Ph.D

Surveillance Planning against Smart Insurgents in Complex Terrain

This study is concerned with finding a way to solve a surveillance system allocation problem based on the need to consider intelligent insurgency that takes place in a complex geographical environment. Although this effort can be generalized to other situations, it is particularly geared towards protecting military outposts in foreign lands. The technological assets that are assumed available include stare-devices, such as tower-cameras and aerostats, as well as manned and unmanned aerial systems. Since acquiring these assets depends on the ability to control and monitor them on the target terrain, their operations on the geo-location of interest ought to be evaluated. Such an assessment has to also consider the risks associated with the environmental advantages that are accessible to a smart adversary. Failure to consider these aspects might render the forces vulnerable to surprise attacks. The problem of this study is formulated as follows: given a complex terrain and a smart adversary, what types of surveillance systems, and how many entities of each kind, does a military outpost need to adequately monitor its surrounding environment? To answer this question, an analytical framework is developed and structured as a series of problems that are solved in a comprehensive and realistic fashion. This includes digitizing the terrain into a grid of cell objects, identifying high-risk spots, generating flight tours, and assigning the appropriate surveillance system to the right route or area. Optimization tools are employed to empower the framework in enforcing constraints--such as fuel/battery endurance, flying assets at adequate altitudes, and respecting the climbing/diving rate limits of the aerial vehicles--and optimizing certain mission objectives--e.g. revisiting critical regions in a timely manner, minimizing manning requirements, and maximizing sensor-captured image quality. The framework is embedded in a software application that supports a friendly user interface, which includes the visualization of maps, tours, and related statistics. The final product is expected to support designing surveillance plans for remote military outposts and making critical decisions in a more reliable manner

Electronic countermeasures applied to passive radar

Passive Radar (PR) is a form of bistatic radar that utilises existing transmitter infrastructure such as FM radio, digital audio and video broadcasts (DAB and DVB-T/T2), cellular base station transmitters, and satellite-borne illuminators like DVB-S instead of a dedicated radar transmitter. Extensive research into PR has been performed over the last two decades across various industries with the technology maturing to a point where it is becoming commercially viable. Nevertheless, despite the abundance of PR literature, there is a scarcity of open literature pertaining to electronic countermeasures (ECM) applied to PR. This research makes the novel contribution of a comprehensive exploration and validation of various ECM techniques and their effectiveness when applied to PR. Extensive research has been conducted to assess the inherent properties of the lluminators of Opportunity to identify their possible weaknesses for the purpose of applying targeted ECM. Similarly, potential jamming signals have also been researched to evaluate their effectiveness as bespoke ECM signals. Whilst different types of PR exist, this thesis focuses specifically on ECM applied to FM radio and DVB-T2 based PR. The results show noise jamming to be effective against FM radio based PR where jamming can be achieved with relatively low jamming power. A waveform study is performed to determine the optimal jamming waveform for an FM radio based PR. The importance of an effective direct signal interference (DSI) canceller is also shown as a means of suppressing the jamming signal. A basic overview of counter-ECM (ECCM) is discussed to counter potential jamming of FM based PR. The two main processing techniques for DVB-T2 based PR, mismatched and inverse filtering, have been investigated and their performance in the presence of jamming evaluated. The deterministic components of the DVB-T2 waveform are shown to be an effective form of attack for both mismatched filtering and inverse filtering techniques. Basic ECCM is also presented to counter potential pilot attacks on DVB-T2 based PR. Using measured data from a PR demonstrator, the application and effectiveness of each jamming technique is clearly demonstrated, evaluated and quantified

Technique-Based Exploitation Of Low Grazing Angle SAR Imagery Of Ship Wakes

The pursuit of the understanding of the effect a ship has on water is a field of study that is several hundreds of years old, accelerated during the years of the industrial revolution where the efficiency of a ship’s engine and hull determined the utility of the burgeoning globally important sea lines of communication. The dawn of radar sensing and electronic computation have expanding this field of study still further where new ground is still being broken. This thesis looks to address a niche area of synthetic aperture radar imagery of ship wakes, specifically the imaging geometry utilising a low grazing angle, where significant non-linear effects are often dominant in the environment. The nuances of the synthetic aperture radar processing techniques compounded with the low grazing angle geometry to produce unusual artefacts within the imagery. It is the understanding of these artefacts that is central to this thesis. A sub-aperture synthetic aperture radar technique is applied to real data alongside coarse modelling of a ship and its wake before finally developing a full hydrodynamic model for a ship’s wake from first principles. The model is validated through comparison with previously developed work. The analysis shows that the resultant artefacts are a culmination of individual synthetic aperture radar anomalies and the reaction of the radar energy to the ambient sea surface and spike events

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