Introduction. For hardware used in radar systems of today, technology is evolving in an increasing rate. For existing software in radar systems, relying on specific drivers or hardware, this quickly becomes a problem. When hardware required is no longer produced or outdated, compatibility problems emerges between the new hardware and existing software. This research will focus on exploring if the virtualization technology can be helpful in solving this problem. Would it be possible to address the compatibility problem with the help of hypervisor solutions, while also maintaining high performance? Objectives. The aim with this research is to explore the virtualization technology with focus on hypervisors, to improve the way that hardware and software cooperate within a radar system. The research will investigate if it is possible to solve compatibility problems between new hardware and already existing software, while also analysing the performance of virtual solutions compared to non-virtualized. Methods. The proposed method is an experiment were the two hypervisors Xen and KVM will analysed. The hypervisors will be running on two different systems. A native environment with similarities to a radar system will be built and then compared with the same system, but now with hypervisor solutions applied. Research around the area of virtualization will be conducted with focus on security, hypervisor features and compatibility. Results. The results will present a proposed virtual environment setup with the hypervisors installed. To address the compatibility issue, an old operating system has been used to prove that implemented virtualization works. Finally performance results are presented for the native environment compared against a virtual environment. Conclusions. From results gathered with benchmarks, we can see that the individual performance might vary, which is to be expected when used on different hardware. A virtual setup has been built, including Xen and KVM hypervisors, together with NAS communication. Running an old operating system as a virtual guest, compatibility has been proven to exist between software and hardware using KVM as the virtual solution. From the results gathered, KVM seems like a good solution to investigate more.

Med den nya omvärldsutvecklingen där NATO moderniserar sitt missilförsvar i Europa samt att Ryssland har placerat taktiska ballistiska robotar i Kaliningrad påverkade Sveriges behov till att anskaffa förmågan att bekämpa ballistiska robotar. Sverige har därför anskaffat Patriotsystemet, dock utan att tillföra ett radarsystem för att invisa ballistiska robotar till luftvärnsförbandet. Missilförsvar är ett väl utforskat område, allt från bekämpningsförlopp till hur en sensorkedja ska se ut. Forskningen tar däremot inte upp vilka förutsättningar ett nyanskaffat radarsystem behöver innefatta för att bidra till att invisa ballistiska robotar för luftvärnsförbanden. I uppsatsen genomfördes en modellering, teknisk analys, där teorin missilförsvar en kedja av event nyttjades för att härleda krav på radarprestanda. En analys om hur organisationerna idag nyttjar radarsystem och hur de tekniska och taktiska kraven påverkar organisationen genomfördes med konceptet militär nytta. Resultatet visar att organisationen där radarsystemet tillförs behövde kompletteras med ett sensorkompani och säkerhetsförband för att uppfylla kravet till invisning. Mot bakgrunden av det scenario som togs fram för undersökning visar den tekniska analysen att radarn vara fordonsburen samt ha en räckvidd på 500 km och en höjdtäckning på 50 km. Den måste även vara kompatibel med Patriotsystemet samt en sensorkedja för strategiskt partnerskap. / With the new developments in international affairs, where NATO modernizes its missile defense system in Europe and Russia has placed tactical ballistic missiles in Kaliningrad, Sweden needs to acquire the ability to combat ballistic missiles. Sweden has therefore acquired the Patriot system, however without adding an early warning radar for the Air defense against ballistic missile. Missile defense is a well-explored area, ranging from missile defense events to how a sensor chain should function. The research does not, however, discuss the abilities an acquired radar system needs to help guide ballistic missiles for Air defense units. In this essay, a modeling and a technical analysis based on the theory Missile defense a chain of events are used to conclude requirements for radar performance. An analysis of how the organizations use radar systems today and how the technical requirements affect the organizations was implemented with the concept Military utility. The result indicates the organization there the radar system will be implemented needs to be reinforced with a sensor company and a security unit to meet the requirement for guidance. The background of the scenario that has been developed for the analysis shows that the radar should be integrated to a vehicle, have a range of 500 kilometers and a height coverage of 50 kilometers. Battle management systems must also be compatible with the Patriot system and the sensor chain for strategic partnership.

Die Datenerfassung für Wetterprognosen basiert bis heute auf konventionellen Radarsystemen, die mit einer verhältnismäßig hohen Leistung arbeiten und für große Reichweiten ausgelegt sind. Da jedoch Wetterphänomene primär in Bodennähe auftreten und deren ausschlaggebenden Charakteristika ebendort zu detektieren sind, bringt dieses einige Nachteile mit sich. Hierzu zählen z.B. Einschränkungen bezüglich der räumlichen Auflösung und der Aktualisierungsrate, die stark eingeschränkten Möglichkeiten der flächendeckenden Erfassung bodennaher Effekte, aber auch die nicht voll polarimetrischen Detektionsmöglichkeiten bestehender Systeme. Die vorliegende Arbeit stellt den Ansatz des 'Digital Beamforming Weather Radar' (DB-WR) vor, welcher die beschriebenen Nachteile maßgeblich reduziert bzw. vermeidet. Die Systemarchitektur basiert hierbei auf engmaschigen Netzwerken von Phased-Array Radargeräten mit signifikant geringeren Reichweiten und Sendeleistungen. Grundlage hierfür bilden polarimetrische Sende-Empfangsmodule ('Software-Defined Radars'), welche die Realisierung der neuartigen 'Arbiträren Polarimetrischen Multiparameter Intrapulsmodulation' (APMIM), einem Verfahren welches beliebige Modulationen innerhalb des Sendepulses zulässt, ermöglichen. Der Fokus richtet sich diesbezüglich auf die Umsetzung eines breitbandigen Stand-Alone Experimentalsystems für diese neuartige Wetterradartechnologie, mit dem das Systemkonzept des DBWR getestet und die Möglichkeiten der APMIM in Kombination mit einer multiplen Empfangssignalauswertung evaluiert werden können. Darüber hinaus werden die Möglichkeiten dieses Experimentalsystems veranschaulicht und die Funktionalitäten in entsprechenden Messungen verifiziert. / Data acquisition for weather forecasts is still based on conventional radar systems, which operate at a relatively high power and are designed for long ranges. However, since weather phenomena primarily occur near the ground and their decisive characteristics have to be detected there, this brings with it a number of disadvantages. These include, for example, limitations with respect to spatial resolution and update rate, the severely restricted possibilities of area-wide detection of near-ground effects, but also the not fully polarimetric detection capabilities of existing systems. This dissertation presents the Digital Beamforming Weather Radar (DBWR) approach, which significantly reduces or avoids the described drawbacks. The system architecture is based on close-meshed networks of phased-array radars with significantly lower ranges and transmission powers. The basis for this is formed by polarimetric transmit-receive modules ('Software-Defined Radars'), which enable the realization of the novel 'Arbitrary Polarimetric Multiparameter Intrapulse Modulation' (APMIM), a method which allows arbitrary modulations within the transmit pulse. In this respect, the focus is on the implementation of a broadband stand-alone experimental system for this novel weather radar technology, with which the system concept of the DBWR can be tested and the possibilities of the APMIM in combination with a multiple received signal evaluation can be evaluated. Furthermore, the capabilities of this experimental system are illustrated and the functionalities are verified in corresponding measurements.

Military systems are often part of critical operations where unplanned downtime should be avoided at all costs. Using modern machine learning algorithms it could be possible to predict when, where, and at what time a fault is likely to occur which enables time for ordering replacement parts and scheduling maintenance. This thesis is a proof of concept study for anomaly detection in monitoring data, i.e., sensor data from a ground based radar system as an initial experiment to showcase predictive maintenance. The data in this thesis was generated by a Giraffe 4A during normal operation, i.e., no anomalous data with known failures was provided. The problem setting is originally an unsupervised machine learning problem since the data is unlabeled. Speculative binary labels are introduced (start-up state and steady state) to approximate a classification accuracy. The system is functioning correctly in both phases but the monitoring data looks differently. By showing that the two phases can be distinguished, it is possible to assume that anomalous data during break down can be detected as well.  Three different machine learning classifiers, i.e., two unsupervised classifiers, K-means clustering and isolation forest and one supervised classifier, logistic regression are evaluated on their ability to detect the start-up phase each time the system is turned on. The classifiers are evaluated graphically and based on their accuracy score. All three classifiers recognize a start up phase for at least four out of seven subsystems. By only analyzing their accuracy score it appears that logistic regression outperforms the other models. The collected results manifests the possibility to distinguish between start-up and steady state both in a supervised and unsupervised setting. To select the most suitable classifier, further experiments on larger data sets are necessary. / Militära system är ofta en del av kritiska operationer där oplanerade driftstopp bör undvikas till varje pris. Med hjälp av moderna maskininlärningsalgoritmer kan det vara möjligt att förutsäga när och var ett fel kommer att inträffa. Detta möjliggör tid för beställning av reservdelar och schemaläggning av underhåll. Denna uppsats är en konceptstudie för detektion av anomalier i övervakningsdata från ett markbaserat radarsystem som ett initialt experiment för att studera prediktivt underhåll. Datat som används i detta arbete kommer från en Saab Giraffe 4A radar under normal operativ drift, dvs. ingen avvikande data med kända brister tillhandahölls. Problemställningen är ursprungligen ett oövervakat maskininlärningsproblem eftersom datat saknar etiketter. Spekulativa binära etiketter introduceras (uppstart och stabil fas) för att uppskatta klassificeringsnoggrannhet. Systemet fungerar korrekt i båda faserna men övervakningsdatat ser annorlunda ut. Genom att visa att de två faserna kan urskiljas, kan man anta att avvikande data också går att detektera när fel uppstår.  Tre olika klassificeringsmetoder dvs. två oövervakade maskininlärningmodeller, K-means klustring och isolation forest samt en övervakad modell, logistisk regression utvärderas utifrån deras förmåga att upptäcka uppstartfasen varje gång systemet slås på. Metoderna utvärderas grafiskt och baserat på deras träffsäkerhet. Alla tre metoderna känner igen en startfas för minst fyra av sju delsystem. Genom att endast analysera deras noggrannhetspoäng, överträffar logistisk regression de andra modellerna. De insamlade resultaten demonstrerar möjligheten att skilja mellan uppstartfas och stabil fas, både i en övervakad och oövervakad miljö. För att välja den bästa metoden är det nödvändigt med ytterligare experiment på större datamängder.

Diese Diplomarbeit stellt den Entwurf eines frequenzmodulierten Dauerstrichradars (FMCW) mit ultrabreitbandigem Frequenzbereich von 50 MHz bis 3 GHz unter Verwendung kommerziell verfügbarer Komponenten (COTS) für die Anwendung als Bodenradar in einer Mondlandeeinheit dar. Dazu werden dem Stand der Technik entsprechende Topologien zur Erzeugung ultrabreitbandiger Signale aufgezeigt und analysiert. Die theoretischen Hintergründe einer Aufteilung des Frequenzsweeps und der späteren Zusammensetzung des Beatsignals werden behandelt. Die Entwürfe der Schaltung, des Layouts und der Software werden erläutert. Bei der Charakterisierung des Radarsystems stellt sich heraus, dass die geforderten Eigenschaften unter dem Einfluss eines Temperaturbereichs von −40 °C bis 75 °C bzw. bei Bestrahlung mit einer Gesamtdosis bis 168 Gy erreicht werden können und die Verwendung von modernen COTS Komponenten die Performance nicht einschränkt. Abschließend werden Verbesserungsvorschläge für Hard- und Software gegeben, welche sich während der Arbeit mit dem System ergeben haben. / This thesis presents the design of a miniature frequency modulated continuous wave (FMCW) radar with a frequency range of 50 MHz to 3 GHz using only commercial off the shelf (COTS) components. The system is intended for use as ground penetrating radar (GPR) as part of a lunar lander. State of the art topologies for ultra wideband signal synthesis are presented and compared. The theoretical background of split frequency ramps and the thus required stitching of baseband signals is discussed. The schematic design, layout and software development is described. The characterization of the radar system shows that the specification is met within a temperature range of −40 °C to 75 °C and while exposition to radiation with an accumulated dose of up to 168 Gy. The use of COTS components does not impair the performance. Finally suggestions for hard- and software improvements are given, that resulted from working with the radar system.