Location information is vital for any type of aircraft and even more crucial for Unmanned Aerial Systems (UAS). GPS is a readily available solution but signals can easily be jammed or lost. In this thesis, radar is explored as a backup system for self-localization when GPS signals are not available. The method proposed requires that an area be pre mapped by collecting radar data with known latitude and longitude coordinates. New radar data is then collected and compared to previously stored values. Channel matrices are stored at each point and are used as the basis for location comparisons. Various methods of matrix comparison are used and both simulation as well as experimental results are shown. The main results of this thesis show that position can be determined using channel matrices if the sensor is within a certain radius of previously stored locations. This radius is on the order of a wavelength or less. Using correlation matrix comparisons the radius of localization is broadened. A novel method using multiple channel and multiple frequency data proves to be successful and determines the position of an octorotor UAS with a mean position error of less than three meters. The design of a low-cost, compact, and light-weight FMCW radar for two applications is also presented. The first application is a novel radar based positioning system that utilizes multiple channel and multiple frequency information to determine position. The second application is a UAS sense and avoid system using a monopulse configuration. Without connectors or antennas, the radar weighs 45.7 grams, is 7.5 cm x 5 cm x 3 cm in size, and costs less than $100 when built in quantities of 100 or more (excludes antennas and connectors). It is tested using delay lines and corner reflectors and accurately determines the distance to close range targets.

With the expansion of unmanned aircraft system (UAS) technologies, there is a growing need for UAS Traffic Management (UTM) systems to promote safe operation and development. To be successful, these UTM systems must be able to detect and track multiple drones in the presence of clutter. This paper examines the implementation of different algorithms on a compact, X-band, frequency modulated continuous wave (FMCW) radar in an effort to enable more accurate detection and estimation of drones. Several algorithms were tested through post processing on actual radar data to determine their accuracy and usefulness for this system. A promising result was achieved through the application of pulse-Doppler processing. Post processing on recorded radar data showed that a moving target indicator successfully separated a target from clutter. An improvement was also noted for the implementation of phase comparison monopulse which accurately estimated angle of arrival (AOA) and required fewer computations than digital beamforming.The second part of this thesis explains the work done on an adaptive broadband, real time beamformer for RF interference (RFI) mitigation. An effective communication system is reliable and can counteract the effects of jamming. Beamforming is an appropriate solution to RFI. To assist in this process FPGA firmware was developed to prepare signals for frequency domain beamforming. This system allows beamforming to be applied to 150 MHz of bandwidth. Future implementation will allow for signal reconstruction after beamforming and demodulation of a communication signal.

No description available.

Highly dense Multiple-Input Multiple-Output (MIMO) radars provide robust detection at a high angular resolution in automotive applications. However, these systems require extensive parallel processing, higher off-chip communication data rates, and higher power consumption as a result of denser arrays to tackle. In this work, concepts, algorithms and circuits for the first-in-literature System-on-Chip (SoC) performing on-chip 5D localization of targets are researched and developed. The targeted system features a scalable homogeneous architecture for fully integrated signal processing of Frequency Modulated Continuous Wave (FMCW) signals and near-sensor smart capabilities for the identification of critical targets (e.g., pedestrians) in an automotive context. To achieve this functionality at a low-power budget, the interconnection of locally constrained processing nodes each with low-area and low-power accelerators operating at low frequencies is developed. The design of efficient algorithms, data flow, and cognitive concepts is also researched and presented to provide an unconventional holistic co-design approach. As a result of the research carried out in this thesis, a 12-ADC multi-core Digital Signal Processor (DSP) in 22FDX GLOBALFOUNDRIES (GF) using Adaptive Body Biasing (ABB) at 0.6V to enable smart on-chip classification with 25 processing elements (PEs) is proposed, providing a low power consumption of only 52.6mW that is at least 90x lower than the state-of-the-art commercial MIMO Radar DSPs.:Abstract Zusammenfassung List of Figures List of Tables Nomenclature 1. Introduction 1.1. Introduction 1.2. Motivation 1.3. Aims and Objectives 1.4. Contributions 1.5. Publications 1.6. Thesis Outline 2. Signal Processing for 5D Radars 2.1. Signal Processing Overview 2.2. Velocity Disambiguation Proposals for MIMO Radars 2.3. Cognitive Principles 2.4. Proposed Clustering for Constrained Processors 2.5. Target Classification 2.6. Summary of the Proposed Contributions 3. Hardware for 5D Radars: A Prototype Implementation 3.1. Multiprocessor Systems-on-Chip 3.2. FFT Acceleration 3.3. Silicon Implementation 3.4. Proposed Testchip 3.5. Proposed Implementation of the Processing Stages 3.6. Summary of Contributions 4. Conclusion and Outlook 4.1. Summary 4.2. Applications 4.3. Further Work 4.4. Conclusion A. Appendix A.1. FMCW Equations A.2. Dataset for Velocity Disambiguation A.3. Dataset for Machine Learning A.4. Dataset for Cognitive Radar Mode A.5. Reliability Proof for the Ambiguity Detector A.6. Measurement Setup A.7. EDA Tools Used in this Work Publications Bibliography / Hochdichte MIMO-Radar-Systeme bieten robuste Detektion mit hoher Winkelauflösung in Automobilanwendungen. Diese Systeme erfordern jedoch aufgrund dichterer Arrays umfangreiche parallele Verarbeitung, höhere Datenraten für die Off-Chip-Kommunikation und einen höheren Stromverbrauch. In dieser Arbeit werden Konzepte, Algorithmen und Schaltungen für den erstmaligen SoC-Ansatz zur On-Chip-Lokalisierung von Zielen in fünf Dimensionen untersucht und entwickelt. Das angestrebte System zeichnet sich durch eine skalierbare homogene Architektur für die vollständig integrierte Signalverarbeitung von FMCW-Signalen aus sowie durch intelligente Fähigkeiten in der Nähe des Sensors zur Identifizierung kritischer Ziele (z. B. Fußgänger) im automobilen Kontext. Um diese Funktionalität bei geringem Energieverbrauch zu erreichen, wird die Verbindung von lokal begrenzten Verarbeitungsknoten mit niedrigflächigen und energieeffizienten Beschleunigern entwickelt, die bei niedrigen Frequenzen arbeiten. Des Weiteren werden effiziente Algorithmen, Datenflüsse und kognitive Konzepte erforscht und präsentiert, um einen unkonventionellen ganzheitlichen Co-Design-Ansatz zu bieten. Als Ergebnis der in dieser Arbeit durchgeführten Forschung wird ein 12-ADC-Multi-Core-DSP in 22FDX GF mit ABB bei 0,6V vorgeschlagen, um eine intelligente On-Chip-Klassifizierung mit 25 Verarbeitungselementen (PEs) zu ermöglichen. Dieser Prozessor weist einen geringen Stromverbrauch von lediglich 52,6mW auf, der mindestens 90-mal niedriger ist als bei den modernsten kommerziellen MIMO-Radar-DSPs.:Abstract Zusammenfassung List of Figures List of Tables Nomenclature 1. Introduction 1.1. Introduction 1.2. Motivation 1.3. Aims and Objectives 1.4. Contributions 1.5. Publications 1.6. Thesis Outline 2. Signal Processing for 5D Radars 2.1. Signal Processing Overview 2.2. Velocity Disambiguation Proposals for MIMO Radars 2.3. Cognitive Principles 2.4. Proposed Clustering for Constrained Processors 2.5. Target Classification 2.6. Summary of the Proposed Contributions 3. Hardware for 5D Radars: A Prototype Implementation 3.1. Multiprocessor Systems-on-Chip 3.2. FFT Acceleration 3.3. Silicon Implementation 3.4. Proposed Testchip 3.5. Proposed Implementation of the Processing Stages 3.6. Summary of Contributions 4. Conclusion and Outlook 4.1. Summary 4.2. Applications 4.3. Further Work 4.4. Conclusion A. Appendix A.1. FMCW Equations A.2. Dataset for Velocity Disambiguation A.3. Dataset for Machine Learning A.4. Dataset for Cognitive Radar Mode A.5. Reliability Proof for the Ambiguity Detector A.6. Measurement Setup A.7. EDA Tools Used in this Work Publications Bibliography

A K-band integrated super-regenerative amplifier (SRA) in a 130nm SiGe BiCMOS technology is designed and characterized. The circuit is based on a novel stacked transistor differential cross-coupled oscillator topology, with a controllable tail current for quenching the oscillations. The fabricated integrated circuit (IC) occupies an area of 0.63mm2, and operates at the free-running center frequency of 25.3 GHz. Characterization results show circuit operation from a minimum input power level required for a phase coherent output as −110 dBm, and the input power level corresponding to the linear to logarithmic mode transition of −85 dBm, the lowest reported for K-band integrated logarithmic mode SRAs to date to the knowledge of the authors. The measured output power is 7.8dBm into a 100 differential load. The power consumption of the circuit is 110mW with no quench signal applied, and 38mW with 30 % duty cycle quenching. The quench waveform designed for the reported measurement result is also discussed.

Cette thèse, réalisée en partenariat avec Rockwell-Collins France, s'inscrit dans le cadre du développement d'un radar FMCW aéroporté de détection d'obstacles fonctionnant en bande X. Dans cette thèse, nous nous plaçons dans le contexte plus général de détection de cibles présentant un risque de collision avec le porteur radar dans du fouillis de sol. Les performances de détection des cibles d'intérêt diminuent grandement lorsqu'elles se retrouvent dans les zones de fouillis. Le principal objectif de cette thèse réside ainsi dans la conception de traitements en vue d'améliorer les capacités de détection et de reconnaissance de cibles présentant un risque de collision avec le porteur radar dans les zones de fouillis de sol. Dans un premier temps, nous effectuons une revue des traitements adaptés à la détection d'obstacles par un radar aéroporté FMCW: formation de faisceaux conventionnelle, compensation de migration distance, et création d'une cartographie distance-vitesse par double FFT. Dans un second temps, nous utilisons ensuite un traitement d'antennes adaptatif pour séparer en élévation le fouillis de sol et d'éventuels obstacles situés au-dessus du sol pouvant présenter un risque pour le porteur (câbles, pylônes, immeubles, ...). Dans la seconde partie de cette thèse, nous incluons une information supplémentaire sur le signal temporel d'une case distance avec un temps d'intégration plus long~: la variation de fréquence Doppler des cibles. Une cible de collision ou un câble ne changent pas de fréquence tandis qu'un élément au sol aura une variation connue dépendant de la vitesse du porteur et de son angle de vue. Cette information nous a tout d'abord permis de séparer le signal d'un pylône et d'un câble, pour ensuite séparer la cible de collision du fouillis de sol. Enfin, nous effectuons la détection adaptative d'une cible mobile de collision étendue en distance et noyée dans le fouillis de sol. Les algorithmes développés dans cette thèse ont été testés avec succès sur données expérimentales. / This thesis, in collaboration with Rockwell-Collins France, forms part of the development of an X-band FMCW airborne radar designed for obstacles detection and collision avoidance. More precisely, this thesis deals with the problem of detecting targets which exhibit a collision trajectory with the radar carrier, in presence of ground clutter. Target detection performances are highly degraded when the targets of interest fall into ground clutter. The main goal of this thesis is to develop signal processing methods to increase radar detection capacities and recognition for collision targets inside ground clutter. First, we give a brief review of signal processing methods for target detection using an airborne FMCW radar : conventional beamforming, range migration compensation, double-FFTs for Range-Doppler Map visualization. We then derive an adaptive antenna array processing to separate ground clutter and fixed hazardous obstacles above the ground (cables, pylons, buildings, ...) using their difference in elevation angle. In the second part of this thesis, we use a long integration time and include extra information on the time model of a range cell signal : Doppler frequency variation. A collision target does not exhibit Doppler frequency variation, whereas fixed obstacle or ground clutter exhibits a known variation depending on the carrier velocity and the aspect angle. We take advantage of this variation first to separate a cable from a pylon, and then separate collision target from ground clutter. We finally tackle the problem of adaptively detecting a collision mobile spread target in ground clutter region. The proposed algorithms in this thesis have been successively tested on experimental data.

Continuous Wave (CW) radars are preferred for their low probability of intercept by the other receivers. Frequency modulation techniques, the linear frequency modulation (LFM) technique in particular, are commonly used in CW radars to resolve the range and the radial velocity of the detected targets. The conventional method for target detection in a linear FMCW radar makes use of a mixer followed by a low-pass filter whose output is Fourier transformed to get the range and velocity information. In this thesis, an alternative target detection technique based on the use of the Ambiguity Function (AF) will be investigated in frequency modulated CW radars. Results of the AF-based technique and the conventional Fourier-based technique will be compared for different target detection scenarios.

京都大学 / 新制・課程博士 / 博士(工学) / 甲第25263号 / 工博第5222号 / 新制||工||1996(附属図書館) / 京都大学大学院工学研究科都市社会工学専攻 / (主査)教授 林 為人, 教授 小池 克明, 講師 石塚 師也, 教授 須崎 純一 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DFAM

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.

Radars have been under steady development to track, identify, image, and classify targets. Modern radar systems, with the help of embedded systems, have additional comprehensive signal processing capabilities. They can extract useful information from very noisy data, e.g. interference from the environment and unwanted echoes which is collectively known as clutter in radar terms. Concerning the healthcare industry, radar applications for detection of vital signs, i.e. breathing and heart rate, have been extensively developed during the last few decades. Modern radar systems are expected to be a large part of non-intrusive monitoring in the coming smart home industry, where vital signs need to be monitored in the currently aging population. The research presented here is to break new ground in the radar-based healthcare technology, enabling detection of cold-induced shivering to such level that the micro-shivering can be clearly identified. To simplify the radar software optimization, a commercially available radar kit with demo application and a muscle model system using a vibration generator is used. The model is quantified through precise measurements. A simulated human body vital sign plus shivering is applied. By optimizing the radar software, the shivering amplitude and frequency are measured.