Un nouvel axe de recherche sur les réseaux de capteurs a été initié au LAAS par la réalisation de nouveaux capteurs sans fil passifs utilisant une transduction électromagnétique dans la détection de pression et de gaz. Ces capteurs fortement intégrés ne nécessitent aucune alimentation embarquée et leur fréquence de fonctionnement se situe dans la bande de fréquence Ka (26 à 40 GHz). Cette thèse s'inscrit donc dans la conception et la réalisation d'un lecteur adapté à l'interrogation à distance de capteurs à transduction électromagnétique. Son principe de fonctionnement est basé sur une technologie radar de type FMCW. L'avantage principal de la lecture radar des données issues de ce type de capteurs passifs réside dans la possibilité d'avoir des portées de plusieurs dizaines de mètres, bien supérieures à celles classiquement obtenues dans les technologies SAW ou RFID. Dans une première étape est présenté le principe de fonctionnement du lecteur radar et la réalisation de deux prototypes centrés sur les fréquences de 3GHz et 30GHz. Une étude du spectre de la sortie radar, appelé signal de battement radar, est abordée afin de montrer comment les positions et les mesures des capteurs sont lues à distance par ce type de lecteur. Par la suite, un travail d'analyse de la communication sans fil permet de déterminer les paramètres de rétrodiffusion électromagnétique à prendre en compte, tels que les impédances et les fréquences de fonctionnement des capteurs. Ces paramètres sont la base d'une optimisation du système global en termes de sensibilité, de portée radar et des niveaux minimaux de Surface Equivalente Radar (SER) des cibles interrogées. La validation de cette analyse se borne à la mesure de la portée maximale associée à ce type de lecteur et aux différentes mesures de SER de plusieurs types de capteurs dans les bandes de fréquence de 3GHz et 30GHz. Deux principes d'identification de cellules passives sont ensuite présentés. Le premier est basé sur l'utilisation des deux modes de rétrodiffusion de la SER d'un capteur (mode de structure et mode d'antenne) favorisant dans le même temps l'identification sur un mode et la mesure de la grandeur physique sur l'autre, a distance du lecteur. Le deuxième principe utilise le spectre d'un diffuseur multi-bande dont sa SER reconfigurable permet d'associer l'identification de chaque capteur dans un réseau, à la manière d'un code barre. En conclusion, les résultats obtenus dans cette étude valident le principe d'interrogation à longue distance de réseau de capteurs passifs et ouvrent de nouvelles perspectives sur la conception de nouvelles cellules de mesures pour de nouvelles applications dans les secteurs de l'aéronautique, du nucléaire, et de l'environnement. / A new development on sensor networks has been started by LAAS to implement new wireless sensors using passive electromagnetic transduction in the detection of pressure and gas. These highly integrated sensors require no power and the embedded operating frequency is in the Ka band (26 to 40GHz). This thesis is on the design and the realization of a reader suitable for remote sensing of sensor electromagnetic transduction. Its working principle is based on an FMCW radar technology. The main advantage of this radar when reading passive sensors is the ability to have ranges of several tens of meters, much higher than those obtained with conventional SAW or RFID technology. In the first step, the principle of operation of the reader and also the realization of two prototypes focused on the frequencies of 3GHz and 30GHz are presented. A study of the output radar spectrum, called beat signal radar, is discussed to show how the positions and measurements from the sensors are read remotely by the reader. Afterwards, an analysis of the wireless communication is performed to take into account parameters of electromagnetic backscatter such as the impedance and operating frequency of these sensors. These parameters are the basis of an optimization of the global system in terms of sensitivity radar range and the minimal levels of Radar Cross Section (RCS) of the interrogated targets.The validation of this analysis is limited by the reader's maximum range and by various RCS measurements of several types of sensors in the frequency bands of 3GHz and 30GHz. Two principles of sensor passive identification are then presented. The first is based on the simultaneous use of both modes of the sensor's RCS (structural mode and antenna mode), facilitating the identification by one mode and measuring the physical quantity using the other mode. The second principle uses the spectrum of a multiband scatterer where its reconfigurable RCS can associate the identification of each sensor in a network, such as a barcode. In conclusion, the result obtained in this thesis validate the principle of an interrogating network of passive sensors over a long reading range and consequently open a new way of sensor design for future aerospace, nuclear and environment applications.

Sedan radar började användas under första hälften av 1900-talet har duellen mellan radar och signalspaning pågått. Genom att utnyttja radar har alltid en medveten risk tagits, risken att bli upptäckt av motståndarens signalspaning. Duellen gavs möjlighet att ta en paus då radarsystem med låg uteffekt introducerades på marknaden under slutet av 1980-talet, nu fanns plötsligt en möjlighet att använda radar samtidigt som de samtida signalspaningssystemen inte kunde upptäcka dessa radarsystem. I föreliggande magisteruppsats i krigsvetenskap med militärteknisk inriktning undersöks räckviddsförhållanden mellan dessa radarsystem och signalspaningssystem. Genom scenarier i den marina arenan försöker jag värdera de taktiska vinster en användare av radar med låg uteffekt kan göra. Analysen visar på att det fram till dess att signalspaningssystem med förmåga att upptäcka radar som utnyttjar låg uteffekt finns tillgängligt är det möjligt att nå taktiska fördelar med dessa system. / Since the advent of radar during the early 20th century the duel between radar and electronic support measurement systems has been practised. Using radar has always been associated with a risk of being detected by an opponent’s electronic support measurement systems. The duel came to a halt when radar systems using low output power were introduced on the market during the late 1980s, now it was possible to use radar without being detected by contemporary electronic support measurement systems. The present master of science (one year) thesis in war science with specialization in military technology looks into the range relationships between radar and electronic support measurement systems. Through scenarios in the naval domain, I seek to assess the tactical benefits a user of low probability of intercept radar may have. The analysis indicates that until electronic support measurement systems with the ability to detect radar systems using low output power are available it is still possible to gain tactical advantages with such systems.

Dans le cadre d'un suivi régulier de patients âgés pouvant souffrir de maladie d'Alzheimer, de nombreuses applications, dont leur localisation, s'avèrent utiles. Un système de localisation compact dédié à un environnement en intérieure est nécessaire. Cette thèse est dédiée à la réalisation d'un système de localisation pouvant répondre à cette attente. Le système développé (Indoor Localisation System, ILS) permet la localisation en trois dimensions d'un badge actif (Active Tag, AT) relativement à une ancre unique (Localisation Base Station, LBS). Le système utilise le principe de radar monopulse multistatique FMCW(Frequency Modulation Continuos Wave) et exploite la bande de fréquence Européenne ULB (6-8.5 GHz). La méthode employée pour l'ILS est une méthode goniométrique se basant sur la mesure conjointe de la différence de fréquence d'arrivée (FDoA) et la différence de phase d'arrivée (PDoA) pour l'estimation de la distance radiale et des angles de direction (azimut et élévation) de l'AT relativement au plan formé par l'ILS. Afin de valider ce système, un prototype d'ILS a été réalisé à Télécom ParisTech.L'objectif de cette thèse est d'obtenir un système de localisation compact permettant de localiser un badge actif avec une précision submétrique dédié pour les environnements en intérieurs exposés aux problèmes de multi-trajets. / Regular and accurate position monitoring of elderly suffering from dementia related problems (Alzheimer) may be required. To assist their monitoring a compact and a less complex indoor localization system is compulsary. This thesis is dedicated to design a Line-of-Sight (LoS) system to allow the indoor localization. The thesis aims to develop an Indoor Localization System (ILS) for three-dimension position estimates with respect to single Localization Base Station as an anchor. The designed ILS uses an Active-Tag (AT) as remote targel. The system uses the monopulse multistatic FMCW radar principle and covers the European UWB (6-8.5 GHz) frequency band. The designed ILS is based on the frequency-difference of arrival (FDoA) and the phase-difference-of-arrival (POoA) techniques for the radial-distance and the angles (azimuth and elevation) estimates. In order to validate this system, a prototype of the ILS is designed at Telecom ParisTech, France.The objective of the designed ILS is to have a localization system with an accuracy in few centimeters in Line-of-Sight condition. The system is designed to need a single anchor, and simultaneously addressing the indoor challenges such as multipaths, strong signal attenuations, reflections, etc.

Machine learning has been employed in the automotive industry together with cameras to detect objects in surround sensing technology. You Only Look Once is a state-of-the-art object detection algorithm especially suitable for real-time applications due to its speed and relatively high accuracy compared to competing methods. Recent studies have investigated whether radar data can be used as an alternative to camera data with You Only Look Once, seeing as radars are more robust to changing environments such as various weather and lighting conditions. These studies have used 3D data from radar consisting of range, angle, and velocity, transformed into a 2D image representation, either in the Range-Angle or Range-Doppler domain. Furthermore, the processed radar image can use either a Cartesian or a polar coordinate system for the rendering. This study will combine previous studies, using You Only Look Once with Range-Angle radar images and examine which coordinate system of Cartesian or polar is most optimal. Additionally, evaluating the localization and classification performance will be done using a combination of concepts and evaluation metrics. Ultimately, the conclusion is that the Cartesian coordinate system prevails with asignificant improvement compared to polar. / Maskininlärning har sedan länge använts inom fordinsindustrin tillsammans med kameror för att upptäcka föremål och få en ökad överblick över omgivningar. You Only Look Once är en toppmodern objektdetekteringsalgoritm särskilt lämplig för realtidsapplikationer tack vare dess hastighet och relativt höga noggrannhet jämfört med konkurrerande metoder. Nyligen genomförda studier har undersökt om radardata kan användas som ett alternativ till kameradata med You Only Look Once, eftersom radar är mer robusta för ändrade miljöer så som olika väder- och ljusförhållanden. Dessa studier har utnyttjat 3D data från radar bestående av avstånd, vinkel och hastighet, som transformerats till en 2D bildrepresentation, antingen i domänen Range-Angle eller Range-Doppler. Vidare kan den bearbetade radarbilden använda antingen ett kartesiskt eller ett polärt koordinatsystem för framställningen. Denna studie kommer att kombinera tidigare studier om You Only Look Once med Range-Angle radarbilder och undersöka vilket koordinatsystem, kartesiskt eller polärt, som är mest optimalt att använda för människodetektering med radar. Dessutom kommer en utvärdering av lokaliserings- och klassificeringsförmåga att göras med hjälp av en blandning av koncept och olika mått på prestanda. Slutsatsen gjordes att det kartesiska koordinatsystemet är det bättre alternativet med en betydligt högre prestanda jämfört med det polära koordinatsystemet.

Die Interaktion zwischen Mensch und Computer ist zu einem Teil unseres täglichen Lebens geworden. Radarsensoren sind aufgrund ihrer geringen Größe, ihres niedrigen Stromverbrauchs und ihrer Erschwinglichkeit sehr vielversprechend. Im Vergleich zu anderen Sensoren wie Kameras und LIDAR kann RADAR in einer Vielzahl von Umgebungen eingesetzt werden, und wird dabei nicht durch Licht beeinträchtigt. Vor allem aber besteht keine Gefahr, dass die Privatsphäre des Benutzers verletzt wird. Unter den vielen Radararten wird das FMCW-Radar für die Gestenerkennung genutzt, da es mehrere Ziele beobachten, Reichweite, Geschwindigkeit und Winkel messen kann und die Hardware und Signalverarbeitung relativ einfach sind. Die radargestützte Gestenerkennung kann in einer Vielzahl von Bereichen eingesetzt werden. So kann z. B. bei Gesundheits- und Sicherheitsaspekten durch den Einsatz radargestützter Gestenerkennungssysteme Körperkontakt vermieden und die Möglichkeit einer Kontamination verringert werden. Auch in der Automobilbranche kann die berührungslose Steuerung bestimmter Funktionen, wie z. B. das Einschalten der Klimaanlage, das Benutzererlebnis verbessern und zu einem sichereren Fahrverhalten beitragen. Bei der Implementierung eines auf künstlicher Intelligenz basierenden Gestenerkennungssystems unter Verwendung von RADAR gibt es noch viele Herausforderungen, wie z. B. die Interpretation von Daten, das Sammeln von Trainingsdaten, die Optimierung der Berechnungskomplexität und die Verbesserung der Systemrobustheit. Diese Arbeit konzentriert sich auf die Bewältigung dieser Herausforderungen. Diese Arbeit befasst sich mit wichtigen Aspekten von Gestenerkennungssystemen. Von der Radarsignalverarbeitung, über maschinelle Lernmodelle, Datenerweiterung bis hin zu Multisensorsystemen werden die Herausforderungen der realen Welt angegangen. Damit wird der Grundstein für den umfassenden Einsatz von Gestenerkennungssystemen in der Praxis gelegt. / Human-computer interaction has become part of our daily lives. RADAR stands out as a very promising sensor, with its small size, low power consumption, and affordability. Compared to other sensors, such as cameras and LIDAR, RADAR can work in a variety of environments, and it is not affected by light. Most importantly, there is no risk of infringing on user's privacy. Among the many types of RADAR, FMCW RADAR is utilised for gesture recognition due to its ability to observe multiple targets and to measure range, velocity and angle, as well as its relatively simple hardware and signal processing. RADAR-based gesture recognition can be applied in a variety of domains. For example, for health and safety considerations, the use of RADAR-based gesture recognition systems can avoid physical contact and reduce the possibility of contamination. Similarly, in automotive applications, contactless control of certain functions, such as turning on the air conditioning, can improve the user experience and contribute to safer driving. There are still many challenges in implementing an artificial intelligence-based gesture recognition system using RADAR, such as interpreting data, collecting training data, optimising computational complexity and improving system robustness. This work will focus on addressing these challenges. This thesis addresses key aspects of gesture recognition systems. From RADAR signal processing, machine learning models, data augmentation to multi-sensor systems, the challenges posed by real-world scenarios are tackled. This lays the foundation for a comprehensive deployment of gesture recognition systems for many practical applications.

This thesis presents work done to extend and improve the operation of homodyne dechirp-on-receive linearly frequency modulated radars. First, an investigation of the effect of common phase errors on the point response function of the radar is described. The dependence on the window function of the degradation due to phase errors is investigated, and a simple, precise, and general approach for calculating the degraded Point Spread Function (PSF) is described and demonstrated. This method is shown to be particularly useful when investigating the effect of chirp nonlinearity on the PSF. Next, a method for focussing range profiles that are degraded by chirp nonlinearity is described. This method is based on two established methods, the Phase Gradient Algorithm (PGA) and a time-domain re-sampling technique. The technique is entirely hardware independent, allowing any homodyne dechirp-on-receive linearly frequency modulated radar to be focussed. Where suitable archive signal data exists, focussed imagery can even be produced from radars that no longer exist. The complete algorithm and details of the implementation are described, and the technique is demonstrated on three representative radar cases: extreme chirp nonlinearity, typical chirp nonlinearity, and a retrospective case. In all of the cases, it was shown that the PSF was dramatically improved. A technique based on down conversion by aliasing for reducing the required sampling rate is described, and a simple technique for calculating suitable sampling rates is presented. This method is demonstrated for a typical application in which sampling rate reduction might be required, namely Moving Target Indication (MTI). The MTI application is described and quantified, including a simple technique for choosing suitable radar operation parameters. The MTI technique with subsampling was demonstrated in software simulations and in a simple radar experiment. A Synthetic Aperture Radar (SAR) test bench for researching component performance and scatterer properties in the context of SAR was developed. An appropriate image formation processing algorithm was found and modified to better suit the task of a short data collection baseline and drifting centre frequencies, both of which are present in the test bench situation. Software was written to collect data, to control the hardware, and to process the signals into SAR images. A data simulator was written to test the image formation algorithm implementation; it also served as a useful tool for investigating the effect of signal errors on the quality of the resultant SAR imagery. A suitable oscillator was chosen for the task, based on phase noise and centre frequency stability considerations, both of which are quantified and discussed. Preliminary SAR imagery was produced, indicating that the system operates correctly and in agreement with comparable systems.

As small unmanned aerial systems (UAS) are introduced into the national airspace, measures must be introduced to ensure that they do not interfere with manned aviation and other UAS. Radar provides an attractive solution because of its inherent range accuracy and because it works in diverse weather and lighting conditions. Traditional radar systems, however, are large and high power and do not meet the size, weight and power (SWaP) constraints imposed by UAS, and fully integrated automotive solution do not provide the necessary range. This thesis proposes a compact radar system that meets both the SWaP and range requirements for UAS and can act as a standalone sensor for a sense and avoid system (SAA). The system meets the field of view requirements motivated by the UAS sensing problem (120deg x 30deg) and tracks targets in range and azimuthal angle using a four element phased array receiver. The phased array receiver implements real time correlation and beamforming using a field programmable gate array (FPGA) and can track multiple targets simultaneously. Excluding antennas, the radar transceiver and signal processing platform weighs approximately 120g and is approximately the size of a whiteboard eraser (2.25in x 4in x 1in), which meets the payload requirements of many small (<25kg) UAS. To our knowledge, this is the first real time phased array radar that meets the sensing and SWaP requirements for small UAS.Our testing was done with the radar system on the ground, aimed at airborne UAS targets. Using antennas with a gain of 12 dB, and 800 milliwatts of transmitted power, the system detects UAS targets with a radar cross section of less than 0.1 square meters up to 150 meters away. The ground based system demonstrates radar detectability of extremely small UAS targets, and is scalable to further ranges by increasing antenna gain or adding additional elements. Based on our success in detecting airborne UAS, we conclude that radar remains a feasible option for a UAS collision avoidance sensor.