Le travail présenté dans ce manuscrit porte sur le développement d’un simulateur de cible (RTS) pour radars automobiles 77 GHz. Afin de proposer des véhicules toujours plus sûrs, les constructeurs automobiles développent des systèmes ADAS de plus en plus performants. On assiste aujourd’hui à la démocratisation des radars automobiles d’alerte à la collision et de régulation de distance. La généralisation de tels systèmes sur des véhicules de série va nécessiter le recours accru à des moyens de tests, chez les constructeurs et dans les centres de contrôle technique. Pour pouvoir tester et calibrer les radars, il est nécessaire d’utiliser des RTS. Ces appareils permettent de simuler les scénarios rencontrés par le radar, ceux-ci devenant plus complexes avec le développement des voitures autonomes. Une cible est définie par trois paramètres : une vitesse, une distance et une SER. Afin de répondre à des exigences drastiques, Autocruise développe ses propres RTS pour des bancs de test de production et de R&D. Ils doivent s’adapter à tout radar fonctionnant sur la bande 76 – 81 GHz, avec différentes modulations et une bande de fréquence supérieure à 800 MHz. Le système doit être à bas coût, de faibles dimensions et flexible pour être intégré dans différentes applications. Le principal verrou technologique est la réalisation d’une ligne à retard variable, capable de simuler des distances comprises entre 1 m et 250 m, avec une résolution de 0,2 m et permettre le contrôle de la SER. Un compromis devra être trouvé afin de répondre aux spécifications. L’étude a montré l’impossibilité de couvrir l’ensemble de la plage de distances avec une seule technologie. Une architecture hybride est indispensable. Une ligne à retard hybride reconfigurable large bande est présentée. / The work presented in this thesis concerns the development of an automotive radar target simulator for 77 GHz radar sensors. In order to continue offering safer vehicles, manufacturers develop more and more performant ADAS systems. We are witnessing a democratization of automotive radar sensors for adaptive cruise control and collision warning. The generalization of such systems on standard cars will require an increased use of test devices both at the manufacturers and in technical control centers. To test and calibrate radars, it is necessary to use Radar Target Simulators (RTS). These devices enable to simulate situations encountered by the radar. Furthermore, these scenarios are becoming increasingly complex with the arrival of autonomous vehicles. A target is defined by three parameters: distance, velocity and radar cross-section (RCS). In order to meet drastic requirements, ZF TRW Autocruise develops its own RTS for production test benches and R&D. RTS must adapt to all radars within a 76 – 81 GHz frequency band, with different modulations and a frequency bandwidth higher than 800 MHz. The system must present the advantages of being a low-cost system, with small dimensions and flexible to be integrated in different applications. The major blocking point is the design of a reconfigurable delay line, able to simulate distances between 1 m and 250 m with a resolution of 0.2 m on a large frequency band and also allowing control of RCS. A compromise will have to be found in order to meet the different specifications. The study showed the impossibility to cover the entire range of distances with one single technology. A hybrid architecture is necessary. A hybrid, tunable, wideband delay line is at study.

This thesis deals with the design of lens antennas for automotive radar in 77 GHz bandwidth. The work explains methods of designing waveguides as well as horn antennas and dielectric lens. A simulation of three designed horn antennas is performed in CST Microwave Studio. Antennas with spherical and hyperbolical lens are simulated as well and subsequently optimized for maximal gain. The thesis also investigates effects of the lens permittivity on its properties. Furthermore, the work deals with a design of an antenna system with minimalized antenna coupling. Nylon, ABS and photopolymer lens are designed and compared afterwards. ABS and photopolymer lens were produced by 3D print

Le développement des radars automobiles, à la bande de fréquences 76-77 GHz, a connu une croissance importante au cours de la dernière décennie. Les développements en cours doivent faire face à deux grands défis. Le premier défi est la réduction du coût pour équiper plus de catégories de voitures avec ces radars. Le deuxième défi est l'amélioration des performances du radar afin de satisfaire les demandes croissantes des autorités de sécurité routière et d'équiper la voiture autonome. L'émetteur-récepteur radar automobile constitue le cœur du système. Par conséquent, une pression importante est exercée sur les fournisseurs de semi-conducteurs pour développer des radars de nouvelle génération avec des performances supérieures et à un coût inférieur par rapport aux générations précédentes. Améliorer les performances de l'émetteur-récepteur passe par par l'amélioration de ces quatre paramètres : le facteur de bruit, le niveau de puissance de l'émetteur, le bruit de phase et la dissipation thermique. La réduction de coût peut être obtenue en réduisant le temps de test, les tailles de la puce et du PCB et le coût du boitier. Dans ce travail, nous proposons une réduction du coût du boitier et de la taille du PCB, en plus de l'amélioration de la dissipation thermique grâce à une encapsulation intégré au niveau plaquette (FI-WLP pour Fan-In Wafer Level Package). Le boitier WLCSP (Wafer Level Chip Scale Package), le plus connu FI-WLP, a été choisi pour cette application. C'est la première fois dans l'histoire des semi-conducteurs que le FI-WLP est utilisé pour du Silicium à des fréquences aussi élevées. Le premier chapitre décrit le système radar et ses principaux composants. Il met l'accent sur la contribution de l'émetteur-récepteur, puis le boitier, sur les performances du radar. Le deuxième chapitre fournit une méthodologie pour la modélisation électromagnétiques et la validation expérimentale de ces modèles, appliquée à des structures passives sur puce. Des innovations, améliorant significativement les performances électriques du boitier WLCSP, sont révélées dans le troisième chapitre. La caractérisation du WLCSP est en soi un défi. De nouvelles méthodologies de caractérisation de ce boitier sont alors proposées dans le même chapitre. Par la suite, un nouveau mélangeur encapsulé en WLCSP est conçu et présenté dans le quatrième chapitre. Le facteur de bruit obtenu est à l'état de l'art, malgré l'utilisation du très contraignant boitier FI-WLP. Tous les résultats de simulation de la transition WLCSP et du mélangeur sont validés par des mesures. Cette caractérisation confirme les excellentes performances attendues du boitier et du circuit conçus. / The development of automotive radars, at the frequency band 76-77 GHz, has experienced a significant growth over the last decade. Ongoing developments have to cope with two main challenges. The first challenge is reducing the cost to equip more car categories with these radars. The second challenge is to improve radar performance in order to satisfy the increasing demands of the road safety authorities and to equip the autonomous car. The automotive radar transceiver is the masterpiece of the system. Therefore, significant pressure is exerted on the semiconductor suppliers to develop next generation radars with superior performances and at lower cost than previous generations. Improving the radar transceiver performances requires improving these four main parameters: Noise Figure (NF), Power Amplifier (PA) power, Phase Noise (PN) and heat dissipation. Lowering the cost can be achieved by reducing test time, chip and PCB sizes, and wafers and package costs. We propose, in this work, a reduction of package cost and PCB size and improvement of heat dissipation by using a FI-WLP. The Wafer Level Chip Scale Package (WLCSP), the best known FI-WLP, was chosen for this application. It is the first time, in Silicon semiconductors history, that a FI-WLP is used at such high frequencies. The first chapter describes the radar system in general and its main components. It focuses on the contribution of the transceiver then the package to the radar performances. The second chapter provides a methodology for EM models validation based on the modeling and experimental validation of passive structures on-chip. Innovations, significantly improving the WLCSP electrical performances, are revealed in the third chapter. The characterization of WLP is, itself, a challenge and novel methodologies to perform it are proposed in the same chapter. Thereafter, a new WLCSP packaged mixer, where block core and RF input matching are co-optimized, is designed and presented in the fourth chapter. The obtained NF is at the state-of-the-art, whereas the very constraining FI-WLP is used. All WLCSP transition and mixer simulation results are validated through measurement. This characterization confirms the excellent performances expected from this novel package and circuit designs.

This thesis presents significant advancements in the field of driver’s chest localization and breathing detection using FMCW radar. It introduces a neural network model for predicting the 3D location of the driver’s chest and a novel algorithm for detecting breathing patterns and localizing the chest position. These scientific breakthroughs contribute to the development of an adaptive safety system for level 3 and above autonomous driving within the IFAS project (FKZ 19A19009E).

En réponse au nombre toujours élevé de décès provoqués par les accidents routiers, l'industrie automobile a fait de la sécurité un sujet majeur de son activité global. Les radars automobiles qui étaient de simples capteurs pour véhicule de confort, sont devenus des éléments essentiels de la norme de sécurité routière. Le domaine de l’automobile est un domaine très exigent en terme de sécurité et les radars automobiles doivent avoir des performances de détection très élevées et doivent répondre à des nombreuses contraintes telles que la facilité de production et/ou le faible coût. Cette thèse concerne le développement d’algorithmes pour la détection et la localisation de piétons et de cyclistes pour des radars automobiles de nouvelle génération. Nous avons proposé une architecture de réseau d'antennes non uniforme optimale et des méthodes d'estimation spectrale à haute résolution permettant d’estimer avec précision la position angulaire des objets à partir de la direction d'arrivée (DoA) de leur réponse. Ces techniques sont adaptées à l'architecture du réseau d'antennes proposé et les performances sont évaluées à l'aide de données radar automobiles simulées et réelles acquises dans le cadre de scénarios spécifiques. Nous avons également proposé un détecteur de cible de collision, basé sur la décomposition en sous-espaces Doppler, dont l'objectif principal est d'identifier des cibles latérales dont les caractéristiques de trajectoire représentent potentiellement un danger de collision. Une méthode de calcul d'attribut de cible est également développée et un algorithme de classification est proposé pour discriminer les piétons, cyclistes et véhicules. Les différents algorithmes sont évalués et validés à l'aide de données radar automobiles réelles sur plusieurs scenarios. / In response to the persistently high number of deaths provoked by road crashes, the automotive industry has promoted safety as a major topic in their global activity. Automotive radars have been transformed from being simple sensors for comfort vehicle, to becoming essential elements of safety standard. The design of new generations automotive radars has to face various constraints and generally proposes a compromise between reliability, robustness, manufacturability, high-performance and low cost. The main objective of this PhD thesis is to design algorithms for the detection and localization of pedestrians and cyclists using new generation automotive radars. We propose an optimal non-uniform antenna array architecture and some high resolution spectral estimation methods to accurately estimate the position of objects from the direction of arrival (DOA) of their responses to the radar. These techniques are adapted to the proposed antenna array architecture and the performance is evaluated using both simulated and real automotive radar data, acquired in the frame of specific scenarios. We propose a collision target detector, based on the orthogonality of angle-Doppler subspaces, whose main goal is to identify lateral targets, whose trajectory features represent potentially a danger of collision. A target attribute calculation method is also developed and classification algorithm is proposed to classify pedestrian, cyclists and vehicles. This classification algorithm is evaluated and validated using real automotive radar data with several scenarios.

Die sensorbasierte Erfassung des Nahfeldes im Kontext des hochautomatisierten Fahrens erfährt einen spürbaren Trend bei der Integration von Radarsensorik. Fortschritte in der Mikroelektronik erlauben den Einsatz von hochauflösenden Radarsensoren, die durch effiziente Verfahren sowohl im Winkel als auch in der Entfernung und im Doppler die Messgenauigkeit kontinuierlich ansteigen lassen. Dadurch ergeben sich neuartige Möglichkeiten bei der Bestimmung der geometrischen und kinematischen Beschaffenheit ausgedehnter Ziele im Fahrzeugumfeld, die zur gezielten Entwicklung von automotiven Sicherheitssystemen herangezogen werden können. Im Rahmen dieser Arbeit werden ungeschützte Verkehrsteilnehmer wie Fußgänger und Radfahrer mittels eines hochauflösenden Automotive-Radars analysiert. Dabei steht die Erscheinung des Mikro-Doppler-Effekts, hervorgerufen durch das hohe Maß an kinematischen Freiheitsgraden der Objekte, im Vordergrund der Betrachtung. Die durch den Mikro-Doppler-Effekt entstehenden charakteristischen Radar-Signaturen erlauben eine detailliertere Perzeption der Objekte und können in direkten Zusammenhang zu ihren aktuellen Bewegungszuständen gesetzt werden. Es werden neuartige Methoden vorgestellt, die die geometrischen und kinematischen Ausdehnungen der Objekte berücksichtigen und echtzeitfähige Ansätze zur Klassifikation und Verhaltensindikation realisieren. Wird ein ausgedehntes Ziel (z.B. Radfahrer) von einem Radarsensor detektiert, können aus dessen Mikro-Doppler-Signatur wesentliche Eigenschaften bezüglich seines Bewegungszustandes innerhalb eines Messzyklus erfasst werden. Die Geschwindigkeitsverteilungen der sich drehenden Räder erlauben eine adaptive Eingrenzung der Tretbewegung, deren Verhalten essentielle Merkmale im Hinblick auf eine vorausschauende Unfallprädiktion aufweist. Ferner unterliegen ausgedehnte Radarziele einer Orientierungsabhängigkeit, die deren geometrischen und kinematischen Profile direkt beeinflusst. Dies kann sich sowohl negativ auf die Klassifikations-Performance als auch auf die Verwertbarkeit von Parametern auswirken, die eine Absichtsbekundung des Radarziels konstituieren. Am Beispiel des Radfahrers wird hierzu ein Verfahren vorgestellt, das die orientierungsabhängigen Parameter in Entfernung und Doppler normalisiert und die gemessenen Mehrdeutigkeiten kompensiert. Ferner wird in dieser Arbeit eine Methodik vorgestellt, die auf Grundlage des Mikro- Doppler-Profils eines Fußgängers dessen Beinbewegungen über die Zeit schätzt (Tracking) und wertvolle Objektinformationen hinsichtlich seines Bewegungsverhaltens offenbart. Dazu wird ein Bewegungsmodell entwickelt, das die nichtlineare Fortbewegung des Beins approximiert und dessen hohes Maß an biomechanischer Variabilität abbildet. Durch die Einbeziehung einer wahrscheinlichkeitsbasierten Datenassoziation werden die Radar-Detektionen ihren jeweils hervorrufenden Quellen (linkes und rechtes Bein) zugeordnet und eine Trennung der Gliedmaßen realisiert. Im Gegensatz zu bisherigen Tracking-Verfahren weist die vorgestellte Methodik eine Steigerung in der Genauigkeit der Objektinformationen auf und stellt damit einen entscheidenden Vorteil für zukünftige Fahrerassistenzsysteme dar, um deutlich schneller auf kritische Verkehrssituationen reagieren zu können.:1 Introduction 1 1.1 Automotive environmental perception 2 1.2 Contributions of this work 4 1.3 Thesis overview 6 2 Automotive radar 9 2.1 Physical fundamentals 9 2.1.1 Radar cross section 9 2.1.2 Radar equation 10 2.1.3 Micro-Doppler effect 11 2.2 Radar measurement model 15 2.2.1 FMCW radar 15 2.2.2 Chirp sequence modulation 17 2.2.3 Direction-of-arrival estimation 22 2.3 Signal processing 25 2.3.1 Target properties 26 2.3.2 Target extraction 28 Power detection 28 Clustering 30 2.3.3 Real radar data example 31 2.4 Conclusion 33 3 Micro-Doppler applications of a cyclist 35 3.1 Physical fundamentals 35 3.1.1 Micro-Doppler signatures of a cyclist 35 3.1.2 Orientation dependence 36 3.2 Cyclist feature extraction 38 3.2.1 Adaptive pedaling extraction 38 Ellipticity constraints 38 Ellipse fitting algorithm 39 3.2.2 Experimental results 42 3.3 Normalization of the orientation dependence 44 3.3.1 Geometric correction 44 3.3.2 Kinematic correction 45 3.3.3 Experimental results 45 3.4 Conclusion 47 3.5 Discussion and outlook 47 4 Micro-Doppler applications of a pedestrian 49 4.1 Pedestrian detection 49 4.1.1 Human kinematics 49 4.1.2 Micro-Doppler signatures of a pedestrian 51 4.1.3 Experimental results 52 Radially moving pedestrian 52 Crossing pedestrian 54 4.2 Pedestrian feature extraction 57 4.2.1 Frequency-based limb separation 58 4.2.2 Extraction of body parts 60 4.2.3 Experimental results 62 4.3 Pedestrian tracking 64 4.3.1 Probabilistic state estimation 65 4.3.2 Gaussian filters 67 4.3.3 The Kalman filter 67 4.3.4 The extended Kalman filter 69 4.3.5 Multiple-object tracking 71 4.3.6 Data association 74 4.3.7 Joint probabilistic data association 80 4.4 Kinematic-based pedestrian tracking 84 4.4.1 Kinematic modeling 84 4.4.2 Tracking motion model 87 4.4.3 4-D radar point cloud 91 4.4.4 Tracking implementation 92 4.4.5 Experimental results 96 Longitudinal trajectory 96 Crossing trajectory with sudden turn 98 4.5 Conclusion 102 4.6 Discussion and outlook 103 5 Summary and outlook 105 5.1 Developed algorithms 105 5.1.1 Adaptive pedaling extraction 105 5.1.2 Normalization of the orientation dependence 105 5.1.3 Model-based pedestrian tracking 106 5.2 Outlook 106 Bibliography 109 List of Acronyms 119 List of Figures 124 List of Tables 125 Appendix 127 A Derivation of the rotation matrix 2.26 127 B Derivation of the mixed radar signal 2.52 129 C Calculation of the marginal association probabilities 4.51 131 Curriculum Vitae 135 / Sensor-based detection of the near field in the context of highly automated driving is experiencing a noticeable trend in the integration of radar sensor technology. Advances in microelectronics allow the use of high-resolution radar sensors that continuously increase measurement accuracy through efficient processes in angle as well as distance and Doppler. This opens up novel possibilities in determining the geometric and kinematic nature of extended targets in the vehicle environment, which can be used for the specific development of automotive safety systems. In this work, vulnerable road users such as pedestrians and cyclists are analyzed using a high-resolution automotive radar. The focus is on the appearance of the micro-Doppler effect, caused by the objects’ high kinematic degree of freedom. The characteristic radar signatures produced by the micro-Doppler effect allow a clearer perception of the objects and can be directly related to their current state of motion. Novel methods are presented that consider the geometric and kinematic extents of the objects and realize real-time approaches to classification and behavioral indication. When a radar sensor detects an extended target (e.g., bicyclist), its motion state’s fundamental properties can be captured from its micro-Doppler signature within a measurement cycle. The spinning wheels’ velocity distributions allow an adaptive containment of the pedaling motion, whose behavior exhibits essential characteristics concerning predictive accident prediction. Furthermore, extended radar targets are subject to orientation dependence, directly affecting their geometric and kinematic profiles. This can negatively affect both the classification performance and the usability of parameters constituting the radar target’s intention statement. For this purpose, using the cyclist as an example, a method is presented that normalizes the orientation-dependent parameters in range and Doppler and compensates for the measured ambiguities. Furthermore, this paper presents a methodology that estimates a pedestrian’s leg motion over time (tracking) based on the pedestrian’s micro-Doppler profile and reveals valuable object information regarding his motion behavior. To this end, a motion model is developed that approximates the leg’s nonlinear locomotion and represents its high degree of biomechanical variability. By incorporating likelihood-based data association, radar detections are assigned to their respective evoking sources (left and right leg), and limb separation is realized. In contrast to previous tracking methods, the presented methodology shows an increase in the object information’s accuracy. It thus represents a decisive advantage for future driver assistance systems in order to be able to react significantly faster to critical traffic situations.:1 Introduction 1 1.1 Automotive environmental perception 2 1.2 Contributions of this work 4 1.3 Thesis overview 6 2 Automotive radar 9 2.1 Physical fundamentals 9 2.1.1 Radar cross section 9 2.1.2 Radar equation 10 2.1.3 Micro-Doppler effect 11 2.2 Radar measurement model 15 2.2.1 FMCW radar 15 2.2.2 Chirp sequence modulation 17 2.2.3 Direction-of-arrival estimation 22 2.3 Signal processing 25 2.3.1 Target properties 26 2.3.2 Target extraction 28 Power detection 28 Clustering 30 2.3.3 Real radar data example 31 2.4 Conclusion 33 3 Micro-Doppler applications of a cyclist 35 3.1 Physical fundamentals 35 3.1.1 Micro-Doppler signatures of a cyclist 35 3.1.2 Orientation dependence 36 3.2 Cyclist feature extraction 38 3.2.1 Adaptive pedaling extraction 38 Ellipticity constraints 38 Ellipse fitting algorithm 39 3.2.2 Experimental results 42 3.3 Normalization of the orientation dependence 44 3.3.1 Geometric correction 44 3.3.2 Kinematic correction 45 3.3.3 Experimental results 45 3.4 Conclusion 47 3.5 Discussion and outlook 47 4 Micro-Doppler applications of a pedestrian 49 4.1 Pedestrian detection 49 4.1.1 Human kinematics 49 4.1.2 Micro-Doppler signatures of a pedestrian 51 4.1.3 Experimental results 52 Radially moving pedestrian 52 Crossing pedestrian 54 4.2 Pedestrian feature extraction 57 4.2.1 Frequency-based limb separation 58 4.2.2 Extraction of body parts 60 4.2.3 Experimental results 62 4.3 Pedestrian tracking 64 4.3.1 Probabilistic state estimation 65 4.3.2 Gaussian filters 67 4.3.3 The Kalman filter 67 4.3.4 The extended Kalman filter 69 4.3.5 Multiple-object tracking 71 4.3.6 Data association 74 4.3.7 Joint probabilistic data association 80 4.4 Kinematic-based pedestrian tracking 84 4.4.1 Kinematic modeling 84 4.4.2 Tracking motion model 87 4.4.3 4-D radar point cloud 91 4.4.4 Tracking implementation 92 4.4.5 Experimental results 96 Longitudinal trajectory 96 Crossing trajectory with sudden turn 98 4.5 Conclusion 102 4.6 Discussion and outlook 103 5 Summary and outlook 105 5.1 Developed algorithms 105 5.1.1 Adaptive pedaling extraction 105 5.1.2 Normalization of the orientation dependence 105 5.1.3 Model-based pedestrian tracking 106 5.2 Outlook 106 Bibliography 109 List of Acronyms 119 List of Figures 124 List of Tables 125 Appendix 127 A Derivation of the rotation matrix 2.26 127 B Derivation of the mixed radar signal 2.52 129 C Calculation of the marginal association probabilities 4.51 131 Curriculum Vitae 135

Automotive radars have gained considerable interest in recent years for applications of road safety for vulnerable road users. The use of multipleinput and multiple-output (MIMO) technology in automotive radar has helped in realising a virtual aperture greater than the physical aperture of the antenna which has reduced the size of the overall radar module. But increasing the number of MIMO channels for greater angular resolution can introduce increased computational complexity, processing time and latency. A new type of radar using the multiple input multiple steered output (MIMSO) radar can alleviate these concerns by replacing the angle-FFT with beamforming by means of a lens. A double-layer lens with a beamforming layer and a radiating layer with a radiating aperture on the 2-D footprint of the lens is proposed as an antenna system for this new radar technique. This work focuses on the radiating aperture which has been realised as a travelling wave planar slotted array in gap waveguide technology due to its benefit of low losses and ease of manufacturing. A ridged gap waveguide is chosen for the reduction of the waveguide size and to avoid the appearance of grating lobes in the visible range for large scan angles. The planar slotted array is synthesised in the travelling wave configuration and reflection cancelling notches are used in the ridge to cancel the reflections from the slots. The aperture is chosen to be of a circular shape for a compact design and to maximise aperture efficiency. The planar array is verified with a full-wave simulation with a bandwidth of 76 to 81 GHz and a realised gain of 27.7 dBi at the centre frequency. The array can be scanned up to ±50◦ with a scan loss of 2.4 dBi. / Fordonsradarer har fått stort intresse under de senaste åren för tillämpningar av trafiksäkerhet för utsatta trafikanter. Användningen av MIMO-teknik (multipleinput och multiple-output) i bilradar har hjälpt till att realisera en virtuell bländaröppning som är större än antennens fysiska bländaröppning, vilket har minskat storleken på den totala radarmodulen. Men att öka antalet MIMOkanaler för större vinkelupplösning kan introducera ökad beräkningskomplexitet, bearbetningstid och latens. En ny typ av radar som använder MIMSO-radarn (multiple input multiple steered output) kan lindra dessa problem genom att ersätta vinkel-FFT med strålformning med hjälp av en lins. En dubbelskiktslins med ett strålformande skikt och ett strålande skikt med en strålande bländare på linsens 2D-fotavtryck föreslås som ett antennsystem för denna nya radarteknik. Detta arbete fokuserar på strålningsöppningen som har realiserats som en plan slitsad array i gap-vågledarteknologi på grund av dess fördel med låga förluster och enkel tillverkning. En vågledare med räfflade gap väljs för att minska vågledarstorleken och för att undvika uppkomsten av gitterlober i det synliga området för stora avsökningsvinklar. Den plana uppsättningen syntetiseras i den vandringsvågkonfigurationen och reflektionsupphävande skåror används i åsen för att eliminera reflektionerna från slitsarna. Bländaren är vald för att ha en cirkulär form för en kompakt design och för att maximera bländareffektiviteten. Planar arrayen verifieras med en helvågssimulering med en bandbredd på 76 till 81 GHz och en realiserad vinst på 27, 7 dBi vid mittfrekvensen. Arrayen kan skannas upp till ±50◦ med en skanningsförlust på 2, 4 dBi.

This thesis concerns the study, development and analysis of innovative artificial intelligence (AI)-driven optimization techniques within the System-by-Design (SbD) framework aimed at efficiently addressing the computational complexity inherent in advanced electromagnetic (EM) problems. By leveraging the available a-priori information as well as the proper integration of machine learning (ML) techniques with intelligent exploration strategies, the SbD paradigm enables the effective and reliable solution of the EM problem at hand, with user-defined performance and in a reasonable amount of time. The flexibility of the AI-driven SbD framework is demonstrated in practice with the implementation of two solution strategies to address the fully non-linear inverse scattering problem (ISP) for the detection and imaging of buried objects in ground penetrating radar (GPR)-based applications, and to address the design and optimization of mm-wave automotive radars that comply multiple challenging and contrasting requirements. A comprehensive set of numerical experiments is reported to demonstrate the efficacy and computational efficiency of the SbD-based optimization techniques in solving complex EM problems.

In this work, the interference sensitivity of an FMCW radar has been evaluated by studying the impact on a simulated detection chain. A commercially available FMCW radar was first characterized and its properties then laid the foundation for a simulation model implemented in Matlab. Different interference methods have been studied and a selection was made based on the results of previous research. One method aims to inject a sufficiently large amount of energy in the form of pulsed noise into the receiver. The second method aims to deceive the radar into seeing targets that do not actually exist by repeating the transmitted signal and thus giving the radar a false picture of its surroundings. The results show that if it is possible to synchronize with the transmitted signal then repeater jamming can be effective in misleading the radar. In one scenario the false target even succeeded in hiding the real target by exploiting the Cell-Averaging CFAR detection algorithm. The results suggests that without some smart countermeasures the radar has no way of distinguishing a coherent repeater signal, but just how successful the repeater is in creating a deceptive environment is highly dependent on the detection algorithm used. Pulsed noise also managed to disrupt the radar and with a sufficiently high pulse repetition frequency the detector could not find any targets despite a simulated object in front of the radar. On the other hand, a rather significant effective radiated power level was required for the pulse train to achieve any meaningful effect on the radar, which may be due to an undersampled signal in the simulation. It is therefore difficult based on this work to draw any conclusions about how suitable pulsed noise is in a non-simulated interference context and what parameter values to use.