The purpose of this thesis was to assess the plausibility of using two Ultra- Wideband radars for detecting and tracking human targets. The detection has been performed by two different types of methods, constant false-alarm rate methods and a type of CLEAN algorithm. For tracking the targets, multiple hypothesis tracking has been studied. Particle filtering has been used for the state prediction, considering a significant amount of uncertainty in a motion model used in this thesis project. The detection and tracking methods have been implemented in MATLAB. Tracking in the cases of a single target and multiple targets has been investigated in simulation and experiment. The simulation results in these cases were compared with accurate ground truth data obtained using a VICON optical tracking system. The detection methods showed poor performance when using data that had been collected by the two radars and post-processed to enhance target features. For single targets, the detections were accurate enough to continuously track a target moving randomly in a controlled area. In the multiple target cases the tracker was not able to distinguish the multiple moving subjects.

Recently, the advent of the integrated circuits (ICs), the monolithic microwave integrated circuits (MMICs) and the multiprocessing computer technology have provided numerous opportunities to make the radar technology compact and affordable. The ultra-wideband (UWB) technology gives many advantages over the traditional narrowband radar systems due to its high spatial resolution, low susceptibility to interference, superior penetration depths, and increased peak power. However, the ability to digitize and reconstruct the full UWB signal spectrum comes at a considerable cost and size. Ultimately, high-speed sampling rates above 10 giga-samples per second (GSPS) are beyond the abilities of conventional analog-to-digital converters (ADCs). The UWB technology is inaccessible to the end-user for various advanced applications in microwave imaging and detection. The purpose of this work is to provide a low-cost, dual-channel UWB pulsed-radar system that is readily available with a 1:10 system bandwidth. The advancements in low-cost alternatives for compact and portable designs empower many promising UWB applications. Here, the desired bandwidth is from 500 MHz to 5 GHz, which utilizes a fast pulse repetition frequency (PRF) in short-range applications. The preliminary results from the novel Equivalent-Time Sampling Receiver are promising with an equivalent-time sampling rate up to 20 GSPS. Nevertheless, the system design is versatile for bandwidth tuning in order to meet the needs of different applications. This versatility is enabled by: i) selection of the effective sampling rate through the field-programmable gate array (FPGA) programming environment, ii) choice of the receivers' front-end track and hold (T & H) amplifier bandwidth, iii) a collection of different PRFs from the low kilohertz up to 20 MHz, iv) tuning of the pulse generator bandwidth, and v) simultaneous multi-channel capabilities enabling antenna beam-forming, polarization diversity and spatial diversity. The result is a fully functional prototype that costs a fraction of traditional bench-top solutions. / Thesis / Master of Applied Science (MASc)

Heart dysfunction is a worldly widespread problem that currently is one of the leading causes of death. Studies indicate that many deaths related to cardiac dysfunction could have been prevented if discovered early. Contemporarily, ultrasound and electrocardiography are indispensable modalities for diagnostic purposes and analysis of cardiac function. The Ventricorder is an Ultra-Wideband radar sensor manufactured by the Norwegian company Novelda. Ventricorder has been shown to be able detect heart movements and breathing but its actual clinical value remains to be investigated. The Cardiac State Diagram (CSD) is a pre-clinical software tool for visualization of the heart's mechanical function. The CSD is confirmed by pilot studies to be able to constitute a basis for diagnosis and cardiac function assessment. Theoretically, the CSD is well suited to be used with the Ventricorder since the Ventricorder detects small changes over time and information about time events is all that is required for the creation of a CSD. Contemporarily, ultrasound tissue velocity imaging (TVI) is usually used for production of CSDs and in this master thesis we examined if the Ventricorder can be used to produce CSDs. This was done by mainly comparing velocity data from the Ventricorder with velocity data from temporally synchronized apical four-chamber images acquired with ultrasound TVI. The results indicate that there is an apparent correlation between these data sets and the Ventricorder should therefore be able to produce data that could constitute the basis for the production of a CSD. What remain now is to confirm these results statistically with a larger test group and to investigate whether all the time instants needed for the production of a CSD can be identified objectively. / Hjärtdysfunktion är ett värdsligt utbrett problem som ligger bakom många dödsfall varje år. Studier har visat att många dödsfall som är relaterade till hjärtdysfunktion hade kunnat förebyggas om de upptäckts i tid. För närvarande är bland annat ultraljud och EKG oumbärliga metoder för diagnostisering och analys av hjärtfunktion. Ventricorder är en typ av radarsensor som utnyttjar ett brett frekvensspektrum, så kallat Ultra Wideband, och är tillverkad av det norska företaget Novelda. Ventricorder har visat sig kunna detektera exempelvis hjärtrörelser och andning men dess kliniska värde har ännu inte undersökts. Cardiac State Diagram (CSD) är ett prekliniskt mjukvaruverktyg för att visualisera hjärtats mekaniska funktion och som har bekräftats genom pilotstudier att kunna användas som underlag för diagnostik och bedömning av hjärtats funktion. Teoretiskt sett är CSD väl lämpat för att användas med Ventricordern eftersom Ventricordern registrerar små rörelser över tid och just ändringar över tid är precis vad som behövs för att skapa ett CSD. I dagsläget används vanligen vävnadsdoppler (TVI) för produktion av CSD och i denna masteruppsats undersöktes huruvida Ventricorder kan användas för att producera CSD. Detta gjordes genom att jämföra mätdata från Ventricorder med temporalt synkroniserade apikala fyrkammar-bilder framställda med vävnadsdoppler. Resultaten indikerar att det finns en påtaglig korrelation mellan dessa data och att mätdatat från en Ventricorder således bör kunna användas för produktion av CSD. Det kvarstår att bekräfta dessa resultat statistiskt med en större testgrupp och att undersöka om samtliga tidsmarkörer som behövs för produktion av ett CSD kan identifieras objektivt.

Two new stepped-frequency continuous wave (SFCW) radar sensor prototypes, based on a coherent super-heterodyne scheme, have been developed using Microwave Integrated Circuits (MICs) and Monolithic Millimeter-Wave Integrated Circuits (MMICs) for various surface and subsurface applications, such as profiling the surface and subsurface of pavements, detecting and localizing small buried Anti-Personnel (AP) mines and measuring the liquid level in a tank. These sensors meet the critical requirements for subsurface and surface measurements including small size, light weight, good accuracy, fine resolution and deep penetration. In addition, two novel wideband microstrip quasi-TEM horn antennae that are capable of integration with a seamless connection have also been designed. Finally, a simple signal processing algorithm, aimed to acquire the in-phase (I) and quadrature (Q) components and to compensate for the I/Q errors, was developed using LabView. The first of the two prototype sensors, named as the microwave SFCW radar sensor operating from 0.6-5.6-GHz, is primarily utilized for assessing the subsurface of pavements. The measured thicknesses of the asphalt and base layers of a pavement sample were very much in agreement with the actual data with less than 0.1-inch error. The measured results on the actual roads showed that the sensor accurately detects the 5-inch asphalt layer of the pavement with a minimal error of 0.25 inches. This sensor represents the first SFCW radar sensor operating from 0.6-5.6-GHz. The other sensor, named as the millimeter-wave SFCW radar sensor, operates in the 29.72-35.7-GHz range. Measurements were performed to verify its feasibility as a surface and sub-surface sensor. The measurement results showed that the sensor has a lateral resolution of 1 inch and a good accuracy in the vertical direction with less than  0.04-inch error. The sensor successfully detected and located AP mines of small sizes buried under the surface of sand with less than 0.75 and 0.08 inches of error in the lateral and vertical directions, respectively. In addition, it also verified that the vertical resolution is not greater than 0.75 inches. This sensor is claimed as the first Ka-band millimeter-wave SFCW radar sensor ever developed for surface and subsurface sensing applications.

Two new stepped-frequency continuous wave (SFCW) radar sensor prototypes, based on a coherent super-heterodyne scheme, have been developed using Microwave Integrated Circuits (MICs) and Monolithic Millimeter-Wave Integrated Circuits (MMICs) for various surface and subsurface applications, such as profiling the surface and subsurface of pavements, detecting and localizing small buried Anti-Personnel (AP) mines and measuring the liquid level in a tank. These sensors meet the critical requirements for subsurface and surface measurements including small size, light weight, good accuracy, fine resolution and deep penetration. In addition, two novel wideband microstrip quasi-TEM horn antennae that are capable of integration with a seamless connection have also been designed. Finally, a simple signal processing algorithm, aimed to acquire the in-phase (I) and quadrature (Q) components and to compensate for the I/Q errors, was developed using LabView. The first of the two prototype sensors, named as the microwave SFCW radar sensor operating from 0.6-5.6-GHz, is primarily utilized for assessing the subsurface of pavements. The measured thicknesses of the asphalt and base layers of a pavement sample were very much in agreement with the actual data with less than 0.1-inch error. The measured results on the actual roads showed that the sensor accurately detects the 5-inch asphalt layer of the pavement with a minimal error of 0.25 inches. This sensor represents the first SFCW radar sensor operating from 0.6-5.6-GHz. The other sensor, named as the millimeter-wave SFCW radar sensor, operates in the 29.72-35.7-GHz range. Measurements were performed to verify its feasibility as a surface and sub-surface sensor. The measurement results showed that the sensor has a lateral resolution of 1 inch and a good accuracy in the vertical direction with less than  0.04-inch error. The sensor successfully detected and located AP mines of small sizes buried under the surface of sand with less than 0.75 and 0.08 inches of error in the lateral and vertical directions, respectively. In addition, it also verified that the vertical resolution is not greater than 0.75 inches. This sensor is claimed as the first Ka-band millimeter-wave SFCW radar sensor ever developed for surface and subsurface sensing applications.

No description available.

Les travaux menés lors de cette thèse s’inscrivent dans le cadre général de la détection de cibles en utilisant une forme d’onde non-conventionnelle large bande. L’utilisation d’une forme d’onde large bande à faible PRF a été proposée par le passé une alternative aux traitements multi-PRF qui limitent le temps d’illumination de la scène. En effet, l’augmentation de la bande instantanée permet d’obtenir une meilleure résolution distance ; les cibles rapides sont alors susceptibles de migrer lors du temps de traitement, mais ce phénomène de couplage distance-vitesse peut être mis à profit pour lever les ambiguïtés. L’objectif de la thèse est alors de développer, pour une forme d’onde large bande avec faible PRF, des traitements prenant en compte la migration des cibles et capables de lever les ambiguïtés vitesse dans des scénarios réalistes. Les travaux se basent sur un algorithme de représentation parcimonieuse non-ambigüe de cibles migrantes, dans un cadre algorithmique Bayésien. Cet algorithme est en revanche développé sous certaines hypothèses, et des travaux de robustification sont alors entrepris afin de l’utiliser sur des scénarios plus réalistes. Dans un premier temps, l’algorithme est robustifié au désalignement des cibles par rapport à la grille d’analyse, puis modifié pour prendre également en compte une possible composante diffuse de bruit. Il est également remanié pour estimer correctement une scène comportant une forte diversité de puissance, où des cibles fortes masquent potentiellement des cibles faibles. Les différents algorithmes sont validés à la fois sur des données synthétiques et expérimentales. / The work conducted during this PhD falls within the general context of radar target detection using a non-conventional wideband waveform. More precisely, the use of a low-PRF wideband waveform has been proposed in the past as an alternative to the classical staggered-PRF processing used to mitigate velocity ambiguities that limits dwell time. Increasing the instantaneous bandwidth improves range resolution; fast moving targets are then likely to migrate during the coherent processing interval. This range-velocity coupling can then be used to mitigate velocity ambiguities. This PhD thesis aims at developing an algorithm able to provide unambiguous estimation of migrating targets using a low-PRF wideband waveform. It is based on a sparse representation algorithm able to unambiguously estimate migrating targets, within a Bayesian framework. However, this algorithm is developed under some hypothesis, and then requires robustification to be used on more realistic scenarii. First, the algorithm is robustified to the case of off-grid targets, and then upgraded to take into account a possible diffuse clutter component. On the other hand, the reference algorithm is modified to accurately estimate high dynamic range scenes where weak targets compete with strong targets. All the developed algorithms have been validated on synthetic and experimental data recorded by the PARSAX radar from the Technical University of Delft, The Netherlands.

L’objectif de cette thèse est la classification automatique des cibles (ATC) en utilisant les signaux rétrodiffusés par un radar ultra large bande (UWB). La classification des cibles est réalisée en comparant les signatures des cibles et les signatures stockées dans une base de données. Premièrement, une étude sur la théorie de diffusion nous a permis de comprendre le sens physique des paramètres extraits et de les exprimer mathématiquement. Deuxièmement, des méthodes d’extraction de paramètres sont appliquées afin de déterminer les signatures des cibles. Un bon choix des paramètres est important afin de distinguer les différentes cibles. Différentes méthodes d’extraction de paramètres sont comparées notamment : méthode de Prony, Racine-classification des signaux multiples (Root-MUSIC), l’estimation des paramètres des signaux par des techniques d’invariances rotationnels (ESPRIT), et la méthode Matrix Pencil (MPM). Troisièmement, une méthode efficace de classification supervisée est nécessaire afin de classer les cibles inconnues par l’utilisation de leurs signatures extraites. Différentes méthodes de classification sont comparées notamment : Classification par la distance de Mahalanobis (MDC), Naïve Bayes (NB), k-plus proches voisins (k-NN), Machines à Vecteurs de Support (SVM). Une bonne technique de classification doit avoir une bonne précision en présence de signaux bruités et quelques soit l’angle d’émission. Les différents algorithmes ont été validés en utilisant les simulations des données rétrodiffusées par des objets canoniques et des cibles de géométries complexes modélisées par des fils minces et parfaitement conducteurs. Une méthode de classification automatique de cibles basée sur l’utilisation de la méthode Matrix Pencil dans le domaine fréquentiel (MPMFD) pour l’extraction des paramètres et la classification par la distance de Mahalanobis est proposée. Les résultats de simulation montrent que les paramètres extraits par MPMFD présentent une solution plausible pour la classification automatique des cibles. En outre, nous avons prouvé que la méthode proposée a une bonne tolérance aux bruits lors de la classification des cibles. Enfin, les différents algorithmes sont validés sur des données expérimentales et cibles réelles. / The objective of this thesis is the Automatic Target Classification (ATC) based on radar backscattered Ultra WideBand (UWB) signals. The classification of the targets is realized by making comparison between the deduced target properties and the different target features which are already recorded in a database. First, the study of scattering theory allows us to understand the physical meaning of the extracted features and describe them mathematically. Second, feature extraction methods are applied in order to extract signatures of the targets. A good choice of features is important to distinguish different targets. Different methods of feature extraction are compared including wavelet transform and high resolution techniques such as: Prony’s method, Root-Multiple SIgnal Classification (Root-MUSIC), Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT) and Matrix Pencil Method (MPM). Third, an efficient method of supervised classification is necessary to classify unknown targets by using the extracted features. Different methods of classification are compared: Mahalanobis Distance Classifier (MDC), Naïve Bayes (NB), k-Nearest Neighbors (k-NN) and Support Vector Machine (SVM). A useful classifier design technique should have a high rate of accuracy in the presence of noisy data coming from different aspect angles. The different algorithms are demonstrated using simulated backscattered data from canonical objects and complex target geometries modeled by perfectly conducting thin wires. A method of ATC based on the use of Matrix Pencil Method in Frequency Domain (MPMFD) for feature extraction and MDC for classification is proposed. Simulation results illustrate that features extracted with MPMFD present a plausible solution to automatic target classification. In addition, we prove that the proposed method has better ability to tolerate noise effects in radar target classification. Finally, the different algorithms are validated on experimental data and real targets.

Due to recent improvements, robots are more applicable in factories and various production lines where smoke, fog, dust, and steam are inevitable. Despite their advantages, robots introduce new safety requirements when combined with humans. Radars can play a crucial role in this context by providing safe zones where robots are operating in the absence of humans. The goal of this Master’s thesis is to investigate different clutter suppression methods for single radar sensor reflection data via digital signal processing. This was done in collaboration with ABB Jokab AB, Sweden. The calculations and implementation of the digital signal processing algorithms are made with Octave. A critical problem is false detection that could possibly cause irreparable damage. Therefore, a safety system with an extremely low false alarm rate is desired to reduce costs and damages. In this project, we have studied four different digital low pass filters: moving average, multiple-pass moving average, Butterworth, and window-based filters. The results are compared, and it is ascertained that all the results are logically compatible, broadly comparable, and usable in this context.

Millions worldwide cannot tell when their bladder is nearing total capacity. The catheter, a tube to empty the bladder, is a vital part of life for many people. A catheter is, however, not a comfortable option, and it is the most common cause of infection in people staying in hospitals. This thesis aims to make the process more comfortable and non-invasive. The proposed idea is to use a UWB radar system with Vivaldi antennas to monitor the bladder state. Research shows that UWB radars can see a difference between a full and an empty phantom bladder. However, current research that explores the usage of UWB radar systems to monitor the bladder state does not consider regulations other than the ones set by FCC. They also only perform experiments on a phantom bladder. This thesis investigates the practical viability of using a UWB radar system designed per the restricted regulations set by Post- och Telestyrelsen. The thesis includes the design, simulations,manufacturing, and testing of the antennas as well as the radar system. The goal was to test the system in both simulations, with a phantom model and with a human body as a target, to advance the current state of research and determine its practicality forreal-life applications. The simulations showed a significant difference in reflections between full and empty bladders. The measurements from the experiments showed a slight difference in amplitude as well, although not as great as predicted due to a longer pulse. The Vivaldi antennas performed as expected according to both theory and simulations and they should work as desired in further experiments that use a UWB radar to monitor the bladder state per the PTS regulations. This thesis is solely based on an original idea and has not been influenced or derived from any external company.