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isbn: 978-65-89159-04-9

En l'actualitat, el vehicle incorporà un gran nombre de dispositius electrònic per tal de millorar l'experiència de conducció i la seguretat dels passatgers. En aquest projecte, es desenvolupa el disseny mecànic d'un radar que té la funció de detectar persónes a l'interior del vehicle. Aquest radar és capaç de realitzar mitjançant algoritmes un "point cloud" de l'interior del vehicle. El procediment de desenvolupament mecànic del radar ha sigut en col·laboració a l'empresa IDNEO TECHNOLOGIES S.A.U, on s'ha adaptat un disseny inicial del radar als requisits establert per al client. L'adaptació del disseny ha comportat a diferents versions i simulacions per tal de validar. En cada component s'ha definit les característiques de disseny i material necessari per complir amb les necessitats del radar. En aquesta memòria podreu trobar un resum de tots els conceptes i eines necessàries per al disseny mecànic d'un component, el criteri per avaluar el disseny, algunes de les simulacions dutes a terme per tal de validar el disseny del radar i imatges reals del prototipatge del component. Tot i ser un treball enfocat al disseny mecànic, en tot el treball s'han tingut en compte les necessitats de radiofreqüència i electromagnetisme del radar., En la actualidad, el vehículo incorporó un gran número de dispositivos electrónico para mejorar la experiencia de conducción y la seguridad de los pasajeros. En este proyecto, se desarrolla el diseño mecánico de un radar que tiene la función de detectar personas en el interior del vehículo. Este radar es capaz de realizar mediante algoritmos un "point cloud" del interior del vehículo. El procedimiento de desarrollo mecánico del radar ha sido en colaboración a la empresa IDNEO TECHNOLOGIES S.A.U, donde se ha adaptado un diseño inicial del radar a los requisitos establecido para el cliente. La adaptación del diseño ha comportado a diferentes versiones y simulaciones para validar. En cada componente se ha definido las características de diseño y material necesario para cumplir con las necesidades del radar. En esta memoria podréis encontrar un resumen de todos los conceptos y herramientas necesarias para el diseño mecánico de un componente, el criterio para evaluar el diseño, algunas de las simulaciones llevadas a cabo para validar el diseño del radar e imágenes reales del prototipaje del componente. A pesar de ser un trabajo enfocado al diseño mecánico, en todo el trabajo se han tenido en cuenta las necesidades de radiofrecuencia y electromagnetismo del radar., The vehicle now incorporated a large number of electronic devices to improve driving experience and passenger safety. In this project, the mechanical design of a radar is developed to detect people inside the vehicle. This radar is capable of performing a "point cloud" of the interior of the vehicle using algorithms. The mechanical development procedure for the radar has been in collaboration with IDNEO TECHNOLOGIES S.A.U, where an initial radar design has been adapted to the requirements established for the client. The design adaptation has led to different versions and simulations in order to validate. In each component, the design and material characteristics necessary to meet radar needs have been defined. In this memory you can find a summary of all the concepts and tools necessary for the mechanical design of a component, the criterion for evaluating the design, some of the simulations carried out in order to validate the radar design and actual images of the component's prototyping. Despite being a work focusing on mechanical design, all work has taken into account radar radio frequency and electromagnetism needs.

In this work, different solutions for human presence detection in a door intercom device are examined. The study was conducted at a company in Lund, Sweden. The aspiration was to have a reliable presence detection to be able to put the device in sleep mode when not used, and the current solution is not optimal because of limiting design requirements and false triggers. In the project, several different sensor technologies and sensors were examined and evaluated. After an initial selection, four different sensor technologies were studied and six different sensors using these technologies were investigated and examined both theoretically and practically during tests. The sensor technologies explored were passive IR, active IR, ultrasonic and radar. With the knowledge gained during the investigation and experiments, the different sensors suitability for the project were discussed and evaluated. The technology most appropriate for this project was found to be radar, due to its ability to easily be installed and integrated inside the intercom since it can function through a lot of materials, including the hardened glass found on the device. While the first radar sensor that was tested demonstrated the potential of the technology, it was found to be a bit too simple. There are a lot of sophisticated radar sensors available but after much investigation the one ultimately chosen was the 60 GHz Acconeer A121 Pulsed Coherent Radar Sensor due to its compatibility with the specific use case. This sensor allows for a much smarter presence detection than the one currently used in the intercom. After testing and learning about the sensor it was concluded that it could be integrated into the intercom’s PCB and function through the hardened glass panel on the front. This makes it much easier to implement than the currently used solution by having less limiting requirements on the mechanical design of the intercom. The sensor enables more efficient presence detection because of the a, With global warming being an ever-looming threat, there is a need to decrease our carbon footprints. This can be done in several ways – from large changes like electrifying our current modes of transportation, to smaller things such as turning off devices when no one is using them. This project has examined different presence detection technologies to implement in a door station. In the same way that the lights in a public restroom only turn on for a limited time after someone enters, a door station can be built in a way that allows it to turn off when no one is close to it. This allows for lower energy consumption which not only saves on electricity but also increases the life span of the components. The product this was tested on was an intercom door station, but the findings from this project would be applicable to other devices that face similar environments. To place electric equipment outside there is a need for weatherproofing. This gives rise to limitations when designing the parts of the door station that interacts with the outside world. Currently, a PIR (passive infrared) sensor is used to detect if there is any movement in front of the sensor. This is done by measuring if there is any temperature change in front of the sensor. A problem with PIR sensors is that they work much better at spotting if someone walks past the sensor than if someone walks towards it, this makes them prone to false triggers. Another problem is that IR light can’t penetrate most materials, this puts some very limiting requirements on the mechanical design of the product as a special plastic cover needs to be placed in front of the sensor to weatherproof it. This plastic cover is both difficult to source and difficult to get certified as a sealing material. The goal of the project was to find a different technology that solved these problems. To accomplish this goal, several different technologies and sensors were researched, tested, and evaluated. A type of radar sensor called "P

Micro-Doppler effects are phenomena that occur because of micro-motion. A micro-motion is either a vibration, rotation, or acceleration which is small relative to the motion of the target. These effects can be used in order to characterize a target through their signature movement. These effects were captured using a Frequency Modulated Continous Wave (FMCW) radar on several targets with a distinct signature. The targets were a four-armed drone, a cyclist, and a pedestrian. Using conventional- and super-resolution algorithms allows the user to process the captured data. To best be able to determine these signatures, different algorithms were used, Short-Time Fourier Transform (STFT), Smoothed Pseudo-Wigner-Ville Distribution (SPWVD), Pade Fourier approximation (PFA), and MUltiple SIgnal Classification (MUSIC). The comparison of the algorithms on the measured data was done in MATLAB where the best possible scenario was taken. From the comparison, it was noticed that in order to capture the most details, the MUSIC, PFA, STFT, and SPWVD performed the best with a decreasing order., Examensarbetet är utfört vid Institutionen för teknik och naturvetenskap (ITN) vid Tekniska fakulteten, Linköpings universitet

Robust detection, localization, and tracking of objects are essential for autonomous driving. Computer vision has largely driven development based on camera sensors in recent years, but 3D localization from images is still challenging. Sensors such as LiDAR or RADAR are used to compute depth; each having its own advantages and drawbacks. The main idea of the project is to be able to mix images from the camera and RADAR detections in order to estimate depths for the objects appearing in the images. Fusion strategies can be considered the solution to give a more detailed description of the environment by utilizing both the 3D localization capabilities of range sensors and the higher spatial resolution of image data. The idea is to fuse 3D detections from the RADAR onto the image plane, this requires a high level of synchronization of the sensors and projections of the RADAR data on the required image., Robust detektering, lokalisering och spårning av objekt är avgörande för autonom körning. Datorseende har till stor del drivit utvecklingen baserad på kamerasensorer de senaste åren, men 3D-lokalisering från bilder är fortfarande utmanande. Sensorer som LiDAR eller RADAR används för att beräkna djup; var och en har sina egna fördelar och nackdelar. Huvudtanken med projektet är att kunna blanda bilder från kameran och RADAR-detektioner för att uppskatta djup för de objekt som förekommer i bilderna. Fusionsstrategier kan anses vara lösningen för att ge en mer detaljerad beskrivning av miljön med både 3D-lokaliseringsförmågan hos avståndssensorer och den högre rumsliga upplösningen av bilddata. Tanken är att smälta samman 3D-detektioner från RADAR till bildplanet, detta kräver en hög nivå av synkronisering av sensorerna och projektioner av RADAR-data på den önskade bilden.

Recent breakthroughs in the fields of antennas, electromagnetic sensors, propagation, and advanced materials have unveiled new opportunities for body area sensing, disease detection, and continuous monitoring. Traditional healthcare approaches not only incur substantial costs but also suffer from inherent drawbacks such as ionizing radiation risks. A range of medical devices, including pacemakers, implants, endoscopy equipment, microwave imaging, and thermal ablation clinical apparatus have greatly benefited from the incorporation of electromagnetic sensors and wireless body area networks. Electromagnetic sensors hold significant potential to transform not only the healthcare sector but also the sports and wearable electronics industries, offering myriad innovative applications. This comprehensive review paper provides an in-depth exploration of the challenges and prospects associated with electromagnetic sensors, including but not limited to microwave probes, resonators, and antennas. We aim to shed light on the potential of these emerging technologies and provide a roadmap for their future development in the context of healthcare and beyond.

Recent breakthroughs in the fields of antennas, electromagnetic sensors, propagation, and advanced materials have unveiled new opportunities for body area sensing, disease detection, and continuous monitoring. Traditional healthcare approaches not only incur substantial costs but also suffer from inherent drawbacks such as ionizing radiation risks. A range of medical devices, including pacemakers, implants, endoscopy equipment, microwave imaging, and thermal ablation clinical apparatus have greatly benefited from the incorporation of electromagnetic sensors and wireless body area networks. Electromagnetic sensors hold significant potential to transform not only the healthcare sector but also the sports and wearable electronics industries, offering myriad innovative applications. This comprehensive review paper provides an in-depth exploration of the challenges and prospects associated with electromagnetic sensors, including but not limited to microwave probes, resonators, and antennas. We aim to shed light on the potential of these emerging technologies and provide a roadmap for their future development in the context of healthcare and beyond.

The current synthetic-aperture-radar (SAR) image formation algorithms have been developed for the pulse radar systems, and they are desired to be used for frequency modulated continuous wave (FMCW) radar systems. Since there is a difference between the outputs of pulse radar and FMCW radar, it is necessary to adapt these algorithms to the output of the pulse radar. Beside this, the start-stop approximation, which can be used for signal processing of pulse radar systems, should be taken into account for FMCW radar systems due to the fact that the pulse duration of pulse radar is relatively small in comparison to the modulation time of FMCW radar. The study investigates the phase error caused by the start-stop approximation in processing the data measured by a FMCW radar system for synthetic aperture imaging. The important finding is that the start-stop approximation is valid for processing FMCW SAR data in many cases. If the following circumstances occur simultaneously, such as high radar signal frequency, long modulation time, high platform speed, and short propagation range, then the approximation may become invalid. The simulations and the experiments performed with a wideband 154 GHz FMCW radar support this statement. Author, Project Multistatic High-Resolution Sensing at THz

The current synthetic-aperture-radar (SAR) image formation algorithms have been developed for the pulse radar systems, and they are desired to be used for frequency modulated continuous wave (FMCW) radar systems. Since there is a difference between the outputs of pulse radar and FMCW radar, it is necessary to adapt these algorithms to the output of the pulse radar. Beside this, the start-stop approximation, which can be used for signal processing of pulse radar systems, should be taken into account for FMCW radar systems due to the fact that the pulse duration of pulse radar is relatively small in comparison to the modulation time of FMCW radar. The study investigates the phase error caused by the start-stop approximation in processing the data measured by a FMCW radar system for synthetic aperture imaging. The important finding is that the start-stop approximation is valid for processing FMCW SAR data in many cases. If the following circumstances occur simultaneously, such as high radar signal frequency, long modulation time, high platform speed, and short propagation range, then the approximation may become invalid. The simulations and the experiments performed with a wideband 154 GHz FMCW radar support this statement. Author, Project Multistatic High-Resolution Sensing at THz

The current synthetic-aperture-radar (SAR) image formation algorithms have been developed for the pulse radar systems, and they are desired to be used for frequency modulated continuous wave (FMCW) radar systems. Since there is a difference between the outputs of pulse radar and FMCW radar, it is necessary to adapt these algorithms to the output of the pulse radar. Beside this, the start-stop approximation, which can be used for signal processing of pulse radar systems, should be taken into account for FMCW radar systems due to the fact that the pulse duration of pulse radar is relatively small in comparison to the modulation time of FMCW radar. The study investigates the phase error caused by the start-stop approximation in processing the data measured by a FMCW radar system for synthetic aperture imaging. The important finding is that the start-stop approximation is valid for processing FMCW SAR data in many cases. If the following circumstances occur simultaneously, such as high radar signal frequency, long modulation time, high platform speed, and short propagation range, then the approximation may become invalid. The simulations and the experiments performed with a wideband 154 GHz FMCW radar support this statement. Author, Project Multistatic High-Resolution Sensing at THz

The current synthetic-aperture-radar (SAR) image formation algorithms have been developed for the pulse radar systems, and they are desired to be used for frequency modulated continuous wave (FMCW) radar systems. Since there is a difference between the outputs of pulse radar and FMCW radar, it is necessary to adapt these algorithms to the output of the pulse radar. Beside this, the start-stop approximation, which can be used for signal processing of pulse radar systems, should be taken into account for FMCW radar systems due to the fact that the pulse duration of pulse radar is relatively small in comparison to the modulation time of FMCW radar. The study investigates the phase error caused by the start-stop approximation in processing the data measured by a FMCW radar system for synthetic aperture imaging. The important finding is that the start-stop approximation is valid for processing FMCW SAR data in many cases. If the following circumstances occur simultaneously, such as high radar signal frequency, long modulation time, high platform speed, and short propagation range, then the approximation may become invalid. The simulations and the experiments performed with a wideband 154 GHz FMCW radar support this statement. Author, Project Multistatic High-Resolution Sensing at THz

Les avalanches sont des phénomènes naturels résultant de l’interaction entre la météorologie et le terrain, et leur gestion repose sur l’évaluation des risques. Cela inclut la protection des infrastructures, des routes, des stations de ski, des activités récréatives en montagne et de l’industrie forestière. Au Canada, la route transcanadienne à travers le col de Roger est particulièrement exposée à ces risques et fait l’objet d’une gestion intensive depuis des décennies. Cependant, les changements climatiques ont un impact significatif sur les conditions météorologiques et nivales, potentiellement modifiant les régimes d’avalanches. Afin de bien comprendre et d’évaluer ces changements, des données météorologiques fiables sont nécessaires ainsi qu’un site représentatif de l’endroit où ces changements peuvent survenir. Le site d’étude de Fidelity est idéal pour mettre en place et tester de nouveaux protocoles qui permettront une meilleure adaptation aux changements de régimes d’avalanches. Comprendre la dynamique de l’eau liquide dans la neige est crucial pour améliorer les modèles de stabilité du manteau neigeux. Dans ce contexte, le modèle SNOWPACK, développé par le WSL Institut pour l’étude de la neige et des avalanches (SLF), permet de simuler les propriétés de la neige sur un terrain, offrant un outil précieux pour évaluer l’instabilité du manteau neigeux dans des conditions de neige mouillée. Cette capacité d’évaluation est essentielle pour anticiper et adapter les stratégies de gestion des risques d’avalanches aux changements climatiques. Cette thèse examine l’importance de la percolation de l’eau dans la neige pour évaluer les risques d’avalanches. Les simulations de ce phénomène sont essentielles pour les prévisionnistes, car la mesure directe sur le terrain est difficile. L’étude se base sur des simulations réalisées avec le modèle SNOWPACK sur le mont Fidelity, au Canada. Les résultats indiquent que la configuration de la température de transition pluie/nei

Radar technologies reserve a large latent capacity in dealing with human motion recognition (HMR). For the problem that it is challenging to quickly and accurately classify various complex motions, an HMR algorithm combing the attention mechanism and convolution neural network (ECA-CNN) using vital signs is proposed. Firstly, the original radar signal is obtained from human chest wall displacement. Chirp-Z Transform (CZT) algorithm is adopted to refine and amplify the narrow band spectrum region of interest in the global spectrum of the signal, and accurate information on the specific band is extracted. Secondly, six time-domain features were extracted for the neural network. Finally, an ECA-CNN is designed to improve classification accuracy, with a small size, fast speed, and high accuracy of 98%. This method can improve the classification accuracy and efficiency of the network to a large extent. Besides, the size of this network is 100 kb, which is convenient to integrate into the embedded devices.

Radar technologies reserve a large latent capacity in dealing with human motion recognition (HMR). For the problem that it is challenging to quickly and accurately classify various complex motions, an HMR algorithm combing the attention mechanism and convolution neural network (ECA-CNN) using vital signs is proposed. Firstly, the original radar signal is obtained from human chest wall displacement. Chirp-Z Transform (CZT) algorithm is adopted to refine and amplify the narrow band spectrum region of interest in the global spectrum of the signal, and accurate information on the specific band is extracted. Secondly, six time-domain features were extracted for the neural network. Finally, an ECA-CNN is designed to improve classification accuracy, with a small size, fast speed, and high accuracy of 98%. This method can improve the classification accuracy and efficiency of the network to a large extent. Besides, the size of this network is 100 kb, which is convenient to integrate into the embedded devices.

© 2010 Elsevier Ltd. We acknowledge the partial support for the realization of this work to the Secretaría de Educación Pública of México through the project PIFI-2007, and the Ministerio de Ciencia y Tecnología of Spain trough the project DPI2005-03891., In our recently reported work [1] (Villa et al., 2009) we derived a regularized quadratic-cost function, which includes fringe orientation information, for denosing fringe pattern images. In this work we adopt such idea for denoising wrapped phase-maps. We use a regularized cost-function that uses complex-valued Markov random fields (CMRFs) with orientation information of the filtering direction along isophase lines. The advantage of using an anisotropic filter along isophase lines is that phase and noise can be properly separated while 2 pi phase jumps are preserved even in high frequency zones. Apart from its robustness, the outstanding advantage of our method is its minimal computational effort. We present some results processing simulated and real phase-maps., Secretaría de Educación Pública of México, Ministerio de Ciencia y Tecnología of Spain, Depto. de Óptica, Fac. de Ciencias Físicas, TRUE, pub

The Swedish Transport Administration Research and Innovation fund for Maritime research funded the project "Reference data and algorithms to support research and development of smart ships". The project goes by the working name, and is communicated as, Reeds. It responds to a synthesis of a number of different needs identified in previous projects and studies. The background to the project is that in recent years the focus has been on developing algorithms to interpret and act on the physical environment around different types of craft. In order to be able to develop and evaluate these algorithms, it has become clear that open datasets and a fair benchmarking platform are required that allow various developers in industries and researchers to evaluate algorithms. In the road vehicle sector, Kitti, as of 2013, is the largest dataset used as a reference dataset. The dataset in this project contains sensor data from several data collection occasions within a maritime context, from high-precision sensors such as cameras, radar, lidar, and IMU. For marine applications, there has been no similar dataset with anywhere near the same amount of data and time synchronisation between sensors. The reference data and reference algorithms were available periodically during the project through an online service where researchers and developers could upload their algorithms to use the dataset. In addition to the dataset itself, Reeds adds additional strengths compared to other reference datasets: - New approach to comparing algorithms fairly, where new algorithms are always compared on a centralised hardware in a cloud service and re-evaluated when new data is added, i.e. an unbiased algorithm evaluation service. - Method that combines NTP and PTP time protocols for synchronisation between the sensors with microsecond accuracy - More types and more modern sensors that can be used at a higher level of abstraction and can thus be applied in more areas. - Se, Projektet “Referensdata och algoritmer till stöd för forskning och utveckling av smarta fartyg” har finansierats av Trafikverkets Forsknings - och Innovationsportfölj för sjöfart. Projektet går under arbetsnamnet och kommuniceras som Reeds svarar mot en syntes av ett antal olika behov som identifierats i tidigare projekt och studier. Bakgrunden till projektet är att de senaste åren har fokus lagts på att ta fram algoritmer för att tolka och agera på den fysiska miljön kring olika typer av farkoster. För att kunna utveckla och utvärdera dessa algoritmer har det blivit tydligt att det krävs öppna dataset och en rättvis benchmarkingplattform som tillåter olika utvecklare inom industrier och forskare att utvärdera algoritmer. Inom vägfordonssektorn är Kitti , från 2013, det största datasetet som används som referensdata set. Datasetet i detta projekt innehåller sensordata från flertalet datainsamlingstillfällen i en maritim kontext, från högprecisionssensorer som kameror, radar, lidar, och IMU. För maritima applikationer har det inte funnits något liknande dataset med tillnärmelsevis lika stor datamängd och med tidssynkronisering mellan sensorer. Referensdata och referensalgoritmerna var tillgängliga periodvis under projektet genom en onlinetjänst där forskare och utvecklare kunde ladda upp sina algoritmer för att använda datasetet. Utöver själva datasetet tillför Reeds ytterligare styrkor jämfört andra referensdata set: - Nytt tillvägagångssätt för att jämföra algoritmer rättvist, där nya algoritmer alltid jämförs på en centraliserad hårdvara i en molntjänst och omvärderas när nya data läggs till, dvs en opartisk tjänst för utvärdering av algoritmer. - Metod som kombinerar NTP och PTP tidsprotokoll för synkronisering mellan sensorerna med mikrosekunds noggrannhet - Fler typer och modernare sensorer som kan användas på en högre abstraktionsnivå, och kan därmed tillämpas inom fler områden. - Sensorfusion av både ombord sensorer och av sen, Projektet har finansierats av Trafikverkets Forskning och Innovations sjöfartsportfölj (P105354). Trafikverket projektnummer: TRV2019/120103

The Bird Flu Radar (GUI) has been developed for EFSA as part of the project named 'Implementation of an Early Warning System for Highly Pathogenic Avian Influenza' (NP/EFSA/BIOHAW/2022/01). The purpose of this project was to develop a spatiotemporal risk assessment to estimate the probability of HPAI outbreaks in the wild bird population by spatiotemporal unit across Europe. The spatiotemporal risk assessment model is now updated in real time with new results being displayed every Monday morning based on the latest HPAI outbreaks (H5 and H7) reported in wild birds in Europe.

Recent breakthroughs in the fields of antennas, electromagnetic sensors, propagation, and advanced materials have unveiled new opportunities for body area sensing, disease detection, and continuous monitoring. Traditional healthcare approaches not only incur substantial costs but also suffer from inherent drawbacks such as ionizing radiation risks. A range of medical devices, including pacemakers, implants, endoscopy equipment, microwave imaging, and thermal ablation clinical apparatus have greatly benefited from the incorporation of electromagnetic sensors and wireless body area networks. Electromagnetic sensors hold significant potential to transform not only the healthcare sector but also the sports and wearable electronics industries, offering myriad innovative applications. This comprehensive review paper provides an in-depth exploration of the challenges and prospects associated with electromagnetic sensors, including but not limited to microwave probes, resonators, and antennas. We aim to shed light on the potential of these emerging technologies and provide a roadmap for their future development in the context of healthcare and beyond.

Este artículo presenta los resultados del análisis polarimétrico, a través de una imagen de radar de apertura sintética (SAR) con cuatro polarizaciones utilizando la herramienta SAR polarimetry target analysis, realizado a las coberturas de la tierra obtenidas con la metodología Corine Land Cover y verificándolas con imágenes de sensores pasivos en un área de la sabana de Bogotá, como resultado del quehacer investigativo del Núcleo de Investigaciones en Datos Espaciales (NIDE)[1] y su semillero, Grupo de Investigaciones en Percepción Remota y Sistemas de Información Geográfica GEIPER[2], de la Universidad Distrital Francisco José de Caldas. Debido a las condiciones climáticas colombianas, que no permiten obtener datos de manera frecuente a partir de sensores pasivos para la generación y actualización de cartografía básica y temática, este grupo de investigación se ha visto en la necesidad de analizar y evaluar la utilización de fuentes de datos de sensores activos, como los radares, para garantizar la consecución de información necesaria para el monitoreo territorial, como los mapas de uso y cobertura de la tierra. Dentro de este contexto, las imágenes de radar de apertura sintética han venido siendo utilizadas por muchas instituciones internacionales y, con mucha menos asiduidad, por las nacionales, aplicando habitualmente una sola polarización, lo que genera mayor dedicación en los trabajos de campo y pos edición. Es precisamente la posibilidad actual de poder trabajar con cuatro polarizaciones lo que direccionó al equipo de trabajo a realizar un análisis de este tipo de imágenes adoptando uno de los sistemas de clasificación más utilizado en el país, el Corine Land Cover. Para ello, se escogen referentes teóricos polarimétricos y módulos de software comercial, como SAR polarimetry target analysis (SPTA) de Catalyst, una marca de PCI Geomatics.

Recent launches of satellite constellations in the Low Earth Orbit (LEO) region have increased the collision probability of existing debris objects with active satellites. Monitoring the trajectories of these debris objects is crucial for Space Situational Awareness (SSA) to prevent the creation of more debris due to unwanted collisions. Much focus is on the LEO regime, with little awareness of the higher Geostationary orbit (GEO) debris population. To date, the explosion of the Russian Ekran 2 satellite in 1978 as well as the disintegration of the Titan IIIC Trans-stage in 1992, have been recorded. These incidents have increased the number of small-sized debris objects in GEO. More unnoticed fragmentation events have been speculated to have occurred, which pose a significant risk of collisions and damage to all weather and communication satellites in use today. The NASA Debris Office confirms that current ground-based radar or optical sensing methods can only be performed for objects of size 1 m and larger, leaving a gap in the precise orbit determination of sub-meter-sized objects in GEO. Moreover, limited observations and atmospheric losses hinder the quality of orbit determination, thus limiting present ground-based SSA techniques. Attempting to bridge this gap in current space surveillance and tracking methods is the objective of this thesis. It evaluates the feasibility of using space-based sensing methods to enhance SSA in the GEO regime. In this research, a satellite in a sub-GEO orbit is deployed to collect in situ radar measurements, which are processed to determine the orbit of a single object in GEO. Different satellite geometries (altitudes and inclinations) and measurement types such as range, range-rate, and direction (azimuth and elevation angles) and combinations thereof have been analysed. A simple grid search optimisation has been performed to assess the feasibility of such a technique and propose a possible favourable observation configuration, w, Aerospace Engineering | Space Exploration

In this paper, we investigate an intelligent reflecting surface (IRS)-assisted integrated sensing and communication (ISAC) system design in a clutter environment. Assisted by an IRS equipped with a uniform planar array (UPA), a multi-antenna base station (BS) is targeted for simultaneously sensing multiple targets in the non-light-of-sight (NLoS) region and communicating with multiple communication users (CUs). We consider the joint IRS-assisted ISAC design in the case with Type-I or Type-II CUs, where each Type-I CU and Type-II CU can and cannot cancel the interference from sensing signals, respectively. Under the perfect communication/sensing channel state information assumption, we aim to maximize the minimum sensing beampattern gain among multiple targets, where the sensing beampattern gain qualifies the achieved illumination signal power at the given location of the target of interest. We jointly optimize the BS’s communication-sensing beamformers and the IRS’s phase shifting matrix, subject to the signal-to-interference-plus-noise ratio (SINR) constraint for each Type-I/Type-II CU, the interference power constraint per clutter, the transmission power constraint at the BS, and the cross-correlation pattern constraint. Due to the design variable coupling, the joint IRS-assisted ISAC design problem is shown to be non-convex in the case with Type-I or Type-II CUs. To circumvent the non-convexity dilemma, we propose semidefinite relaxation (SDR) based alternating optimization algorithms in both cases, for which the computational complexity and convergency behavior are analyzed. In the case with Type-I CUs, we show that the dedicated sensing signal at the BS can help enhance the sensing performance gain. By contrast, the dedicated sensing signal at the BS is not required for the IRS-assisted ISAC designs in the case with Type-II CUs. Numerical results are provided to show that the proposed IRS-assisted ISAC design schemes achieve a significant gain over the existing

In this work, we develop and analyze a new software-defined pulsed ultra-wideband (UWB) transmitter for pulsed radar systems. As compared to conventional analog pulse generator-based transmitters, the implementation of a software-defined generator allows for flexibility in pulse shaping and bandwidth based on situation. The implementation of the software-defined transmitter is vital as it allows for (1) an advantage in imaging targets at different distances and (2) the potential to suppress ringing and clutter through implementation of digital pre-distortion (DPD). The system is tested in applications with ground penetrating radar (GPR). First, we discuss the architecture and design of the software-defined transmitter operating from DC-11.9 GHz that implements an arbitrary waveform generator (AWG), amplifier, and switching network. In addition to evaluating these components, we perform scans outside of Kemper Hall at UC Davis to show how flexibility from the software-defined radar allows for detection of different target types. Next, we describe the design and evaluation of a UWB 3:1 switching network on a 45 nm RFSOI process operating from DC-67 GHz potentially useful for radar. Aside from the hardware design, we also establish a DPD algorithm that uses Wiener filter compensation followed by an iterative feedback loop to decrease measured ringing and increase pulse fidelity. We show the effectiveness in applying this DPD algorithm for pulses with a 20-dB bandwidth up to 8.46 GHz. Additionally, we show an adjusted DPD algorithm useful for compensating pulses out of a non-linear transmission line using a look-up table-based approach. Lastly, we analyze the effect of realistic vibration on a UWB transmitter for B-scan image quality of GPR scans.

Accurate precipitation monitoring is crucial for understanding climate change and rainfall-driven hazards at a local scale. However, the current suite of monitoring approaches, including weather radar and rain gauges, have different insufficiencies such as low spatial and temporal resolution and difficulty in accurately detecting potentially destructive precipitation events such as hailstorms. In this study, we develop an array-based method to monitor rainfall with seismic nodal stations, offering both high spatial and temporal resolution. We analyze seismic records from 1825 densely spaced, high-frequency seismometers in Oklahoma, and identify signals from nine precipitation events that occurred during the one-month station deployment in 2016. After removing anthropogenic noise and Earth structure response, the obtained precipitation spatial pattern mimics the one from a nearby operational weather radar, while offering higher spatial (~ 300 m) and temporal (< 10 s) resolution. We further show the potential of this approach to monitor hail with joint analysis of seismic intensity and independent precipitation rate measurements, and advocate for coordinated seismological-meteorological field campaign design.

This thesis explores the option to apply Synthetic Aperture Radar (SAR) techniques to image near-field targets utilizing mmWave pulsed coherent radar (PCR). The recent development of mmWave radars has broadened the scope for SAR, but there are few concrete examples explaining and demonstrating the fundamental SAR algorithms from a PCR perspective. This thesis aims to address this gap by investigating the imaging capabilities of near-field SAR, where the curvature of the incoming waves has to be considered. The focus is on a comparative analysis of two distinct imaging approaches: frequency-based image formation and time-based image formation. The two approaches are compared using elementary algorithms in each category: Doppler Beam Sharpening and Global Backprojection. The comparison involves explaining the theory and approximations of each algorithm, discussing the shortcomings, and examining the expected effects when applying them in near-field applications. These effects are later exemplified through simulations. Finally, the algorithms are applied to measurements made using the Acconeer A121 PCR system, showcasing the remarkable potential of basic SAR techniques in rendering intricate images of near-field targets. By making these investigations, we endeavor to contribute to the academic understanding and practical utilization of near-field SAR with PCR systems.

The advancement of future generations of wireless communication and radar sensing warrants the need for mm-wave digitally controlled oscillators (DCOs) with high-frequency trade-offs in consideration. The purpose of this project is to investigate DCO topologies inspired from scientific literature. The DCO is an electronic component that takes a digital code as input to tune the output operation frequency. Acconeer's application, a pulsed coherent radar system, sets unconventional performance requirements on the DCO compared to continuous wave systems. A specific type of oscillator core, namely the cross-coupled differential-pair harmonic oscillator, has been investigated. The performance of this oscillator is subject to special trade-offs in the DCO implementation. A strategy of multiple stages was used to guide the work. First, possible solutions were crudely investigated, then promising solutions selected, and finally pre- and post-layout simulation results of said solutions were provided. Five solution alternatives were identified and benchmarked with respect to a digital equivalent of the cross-coupled differential-pair LC-VCO. These solutions present different opportunities to relax trade-offs in the design of the DCO. Benchmarking the post-layout results of the solutions with literature revealed competitive performance, considering requirements set by the radar application, which is the context of this work. The analysis of this investigation provides a foundation and suggestive guidelines of future action for Acconeer. This work also captures the state-of-the-art of DCOs for pulsed coherent radar, priming further research within the field., In the hunt for faster wireless communication and more advanced radar technology, the design of digital oscillators is of utmost importance. Consider a regular day in your life, such as today. It is likely that you made or will make a phone call. Even more likely is that you will use the mobile phone that is in your pocket right now to search the web or simply scroll through social media. Even though not every single person has these habits, a large portion of today's society relies on being connected wirelessly. Wireless communication can be defined as the act of transferring information seemingly instantly, at the speed of light, from one device to another. As the technological advancement of the human race progresses, the demand for faster data transfer rates increases, which is achieved by increasing the bandwidth and modulation complexity of the transmitted electromagnetic waves. Larger bandwidths are available at higher frequencies. The frequencies in use in today's technology are typically in the gigahertz (GHz, one billion oscillations per second) region. The wavelength of a wave with a frequency of a few tens of GHz is in the order of a few millimeters, hence the name millimeter wave (mm-wave) technology. Additionally, research is currently underway to support the sub-terahertz (THz, one trillion oscillations per second) region. The properties of electromagnetic waves can also be used for sensing applications, and the most relevant for this work, radar. Radar is a technique where electromagnetic waves are sent out, reflected on objects, and then received. The properties of the reflected light, as well as the time it took for the light to return, can be used to determine properties about the surroundings, such as position, shape, and speed of objects. The capabilities of radar increases as support for higher frequencies is developed. In the next generation of wireless communication, 6G, there's talk about integrating wireless communication with sensing to ac

Vital signs are a group of biological indicators that show the status of the body’s life-sustaining functions. They provide an objective measurement of the essential physiological functions of a living organism, and their assessment is the critical first step for any clinical evaluation. Monitoring vital sign information provides valuable insight into the patient's condition, including how they are responding to medical treatment and, more importantly, whether the patient is deteriorating. However, conventional contact-based devices are inappropriate for long-term continuous monitoring. Besides mobility restrictions and stress, they can cause discomfort, and epidermal damage, and even lead to pressure necrosis. On the other hand, the contactless monitoring of vital signs using radar devices has several advantages. Radar signals can penetrate through different materials and are not affected by skin pigmentation or external light conditions. Additionally, these devices preserve privacy, can be low-cost, and transmit no more power than a mobile phone. Despite recent advances, accurate contactless vital sign monitoring is still challenging in practical scenarios. The challenge stems from the fact that when we breathe, or when the heart beats, the tiny induced motion of the chest wall surface can be smaller than one millimeter. This means that the vital sign information can be easily lost in the background noise, or even masked by additional body movements from the monitored subject. This thesis aims to propose innovative signal processing solutions to enable the contactless monitoring of vital signs in practical scenarios. Its main contributions are threefold: a new algorithm for recovering the chest wall movements from radar signals; a novel random body movement and interference mitigation technique; and a simple, yet robust and accurate, adaptive estimation framework. These contributions were tested under different operational conditions and scenarios, spanning ideal

The vital sign measurement systems inside vehicles have taken great or impulse in recent years, and the technologies that have been most welcomed are based on wireless measurements that do not interrupt driving and are imperceptible to the driver. There are disorders in breathing patterns, which include the movement of different regions of the human thorax mainly. In this sense, the objective of this paper is to determine the dimensions of a lens-based antenna system and the pointing angles of the radiation main lobe of the six antenna-elements to measure the elongation of six regions of the human torso and determine breathing patterns. The pointing angle is controlled by the position of the antenna behind the lens, and the beamwidth of the lobe depends on the directivity achieved by the antenna. An electronic system to simulate torso elongation is also presented to calibrate and test the sensitivity of the system., This work was supported by the Spanish “Comisión Interministerial de Ciencia y Tecnologia” (CICYT) under projects PID2019-107885GB-C31 and MDM2016-O6OO; Catalan Research Group 2017 SGR 219; and ”Secretaría Nacional de Educación Superior, Ciencia, Tecnología e Innovación” (SENESCYT) from the Ecuadorian government., Peer Reviewed, Postprint (author's final draft)

This thesis will aim to design and implement an ADS-B integral and distributed system for detecting aircrafts broadcasts messages. Those messages will be processed and stored in a SQL database the project will rely on an MariaDB server installed on a home build server computer. After the data processing, clients through a web application developed with Python and Django framework will be able to consume on real time the information which will be displayed in an interactive map thanks to an API REST. Additionally, it will be also possible to access historic and real time data for researchers through downloadable files or through a direct SQL connection to the server with read-only privilege dedicated account. The system will be developed at a first stage with a raspberry pi 4B 8GB and then migrated to a dedicated server, the system is gives only support to GNU-LINUX Debian based distributions such as Ubuntu and Raspbian. The hardware for receiving messages will be an RTL-SDR receiver and will rely on the following open-source projects: dump1090 for Raspbian OS or dump1090-mutability for Ubuntu OS where data will be collected through an UDP socket. Scalability will be taken into account allowing to have multiple base stations feeding to the server at the same time. It will involve from the radio frequency system conditioning to the front-end development. The applications for such system will be the promotion of the EETAC, a tool for researchers in ATM, for performing some basic statistics with the data harvested and for estimating the radio propagation in the 1090 MHz band

This thesis combines radar signal processing, with data driven artificial neuralnetwork (ANN) methods. Signal processing algorithms are often based on modelingassumptions of how the data was formed. In some cases, such models are sufficientfor designing good, or even optimal, solutions.In many cases however, these models may be too complicated to form analyticalsolutions; be too simplified, such that practical results may differ significantly fromwhat was theoretically indicated; be unknown in the sense that one of several knownmodels or parameter values may fit the data, but we do not know which; or be toocomplex such that the solution will be too heavy to compute.Data driven ANN methods provide a simple way of bridging these gaps. Wedemonstrate this in four different studies, where we make use of radar data modelsto formulate data driven solutions that are both accurate and computationallyefficient.We compare ANN based results to computationally demanding least squares,and exhaustive matched filtering approaches. We show that the performance of theANNs are comparable to these, but come at a fraction of the computational load.We train ANNs on data sampled from models using a wide range of parametervalues. This naturally handles drifts and unknown parameter values, which maychange the data, but not the desired prediction. We show that an ANN classifiertrained on data from simple models may in practice perform significantly worsethan what was expected from theory. We improve this by combining a limitedamount of real data with synthetic model data. In all cases, we make use of modelsthat are simple to evaluate. They are however not simple to analyze for the purposeof creating analytical solutions.In particular we present a method for achieving non-coherent pulse compressionthat resolves targets within a single pulse width. We present a method fordetecting weak target trajectories that does not require prior assumptions ontarget acceleration, the signal-to-noise ratio, Denna avhandling kombinerar radarsignalbehandling med datadrivna artificiellaneuronnät (ANN) metoder. Signalbehandlings algoritmer är ofta baserade påmodellantaganden om hur data kommit till. I vissa fall är sådana modeller tillräckligaför att designa bra, eller till och med optimala, lösningar.I många fall kan dock dessa modeller vara alltför komplicerade för att ta framanalytiska lösningar; vara alltför förenklade, så att resultat från praktik skiljer sigmarkant från vad som var teoretiskt väntat; vara okända i den bemärkelsen att enav många kända modeller eller parameter värden kan passa data, men vi vet intevilket; eller vara alltför komplexa så att lösningen blir för tung att beräkna.Datadrivna ANN metoder kan användas för att brygga dessa gap. Vi demonstrerar detta i fyra olika studier, där vi använder oss av modeller för radardata föratt formulera datadrivna lösningar som är både noggranna och beräkningsmässigteffektiva.Vi jämför resultat från ANN lösningar med resultat från beräkningsmässigt merkrävande minsta kvadrat och matchade filter lösningar. Vi visar att prestandan avANN är jämförbar med dessa, men kräver endast en bråkdel av beräkningarna. Vitränar ANN på data från modeller med ett brett span av parameter värden. Dettaför att hantera okända parameter värden och förändringar i dessa, som kan ändradata men inte den önskade prediktionen. Vi visar att en ANN klassificerare som ärtränad på data från enkla modeller kan prestera anmärkningsvärt sämre i praktikenfrån vad som vad var teoretiskt väntat. Vi förbättrar detta genom att kombinera enbegränsad mängd riktigt data med syntetiskt modelldata. I samtliga fall användervi oss av modeller som är enkla att exekvera. Dom är dock inte enkla att analyserai avsikt att skapa analytiska lösningar.Mer konkret presenterar vi en metod för icke-koherent pulskompression somlöser upp mål inom en pulsvidd. Vi presenterar en metod för att detektera svagamålspår som inte kräver antaganden om målets acceleration, signal-til, Reserach funder: SAABQC 20230914

This paper presents a silicon micromachined reconfigurable beam-steering frontend chip in which multiple components are integrated within a single silicon chip. The size o the whole frontend chip is 14.3×20×1.2 mm3. The signal path includes a novel switching circuit, a beam-steering network, two power-dividing networks, and a 2×8 array antenna. The presented frontend chip is able to create two frequency steerable beam-shapes. The switching circuit determines which beam shape to be radiated. The first beam-shape is a steerable broad fan-beam with reduced sidelobe level (SLL) in the H-plane, and the second is a steerable notched fan-beam. The measured SLL of the broad beam is better than 18.5 dB in the H-plane, and the measured notch depth is better than 24 dB in the E-plane pattern. Both radiation patterns can be steered by frequency and move from -20 degrees at 238 GHz to +20 degrees at 248 GHz.The measured return loss of the fabricated device is better than 15 dB at 220-265 GHz, which is equal to almost 18.6 % fractional bandwidth., QC 20230630

This paper presents a silicon micromachined reconfigurable beam-steering frontend chip in which multiple components are integrated within a single silicon chip. The size o the whole frontend chip is 14.3×20×1.2 mm3. The signal path includes a novel switching circuit, a beam-steering network, two power-dividing networks, and a 2×8 array antenna. The presented frontend chip is able to create two frequency steerable beam-shapes. The switching circuit determines which beam shape to be radiated. The first beam-shape is a steerable broad fan-beam with reduced sidelobe level (SLL) in the H-plane, and the second is a steerable notched fan-beam. The measured SLL of the broad beam is better than 18.5 dB in the H-plane, and the measured notch depth is better than 24 dB in the E-plane pattern. Both radiation patterns can be steered by frequency and move from -20 degrees at 238 GHz to +20 degrees at 248 GHz.The measured return loss of the fabricated device is better than 15 dB at 220-265 GHz, which is equal to almost 18.6 % fractional bandwidth., QC 20230630

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.

During the last century, various countries' armed forces have used unmanned aerial vehicles, commonly known as drones. In recent years, strives have been made to develop small commercial drones that have allowed the general public to afford and use them for recreational purposes. The availability of drones has led to immoral applications of the technology. Such applications need to be faced with anti-measures and effective detection methods. Therefore, this thesis aims to develop a mobile reconnaissance robot that can detect commercial drones with radar. It describes integrating radar sensors with single-board computers to detect and localise air-bound objects. The finished product aims to be used for educational and exhibition purposes at the Swedish Armed Forces technical school to increase awareness of the technology., Försvarsmaktens tekniska skola i Halmstad var intressenter för uppsatsen.

Accurate and efficient localization is a fundamental requirement for autonomous operation of robots, especially in areas that deny global navigation services. Localization is even more challenging in environments that present visual and geographic difficulties. This not only includes environmental aspects like darkness, fog and dust but also geometrically monotone areas. The solution that the Center for Applied Autonomous Sensor Systems at the Örebro university decided to develop is therefore a prototype of radar-only localization and mapping (SLAM) system. The radar modality is less susceptible to the environmental factors when compared to, for example, a lidar. Our goal is to support this effort by creating an odometry module that uses radar and inertial data to provide the localization for this SLAM prototype. This radar-inertial-odometry (RIO) takes radar point clouds and inertial gyroscopic data to output an odometry message usable by other components in the robot operating system (ROS). The module has been tested on two datasets representing areas typical for deployment, one consisting of underground tunnels and the other one being an outside forest environment. The dataset has been processed by two different mappers where the lidar has been used as the basic modality. This choice allows us to evaluate the odometry module in a more practical way. The final results are promising, the underground localization closely adheres to reality. The forest dataset is more challenging although it still resembles the ground-truth position in the horizontal dimension. The module's biggest shortcoming is a noticeable drift problem in the vertical z-dimension , for which we propose a constraint that limits this drift.

Radar is a tool that has had a tremendous impact since its discovery. This thesis evaluates an algorithm called ESPRIT. ESPRIT is used in radar to estimate the angles to detected objects. The angle of an object is referred to as its DOA (Direction of arrival). ESPRIT separates from similar algorithms by having lower computational complexity, storage needs, and robustness. The thesis compares ESPRIT with another DOA-estimation algorithm used by a company called Raytelligence. The other algorithm can not be named due to confidentiality. The comparison is based on gathered data from an FMCW (Frequency Modulated Continuous Wave) radar. The comparison aims to validate ESPRIT functionality and its competitiveness versus the other algorithm. The comparison is based on two criteria: Accuracy and complexity. The thesis also presents potential optimizations which can improve ESPRIT’s ability to estimate DOA. These are an increase in the number of antennas used in the DOA estimation, and using the preprocessing scheme Spatial smoothing. The result for DOA estimation shows that ESPRITs' strength lies in detecting several objects at the same distance. The difference between ESPRIT and the other DOA estimation algorithm was insignificant when estimating one object. No conclusion could be drawn about the estimation accuracy for one object detection. The result also showed that ESPRIT's performance increases with the number of antennas and which preprocessing scheme is used. The result for complexity showed that ESPRIT has higher complexity than the other DOA estimation algorithm. For ESPRIT to use its strength, which is to detect several objects at the same distance, the implementation of complex pre-processing schemes is required. This will further increase the difference in complexity between the two compared algorithms., Radar är ett verktyg som har haft en enorm påverkan sen dess upptäckt. Denna avhandling utvärderar en algoritm som heter ESPRIT. ESPRIT används i radar för att estimera vinklarna till detekterade objekt. Vinkeln för ett objekt benämns som dess DOA (Direction of arrival). ESPRIT skiljer sig från liknande algoritmer genom dess lägre beräkningskomplexitet, lagringsbehov samt robusthet. Avhandlingen jämför ESPRIT med en annan DOA estimerings algoritm som används av företaget Raytelligence idag. På grund av sekretess kan denna algoritm inte namnges. Jämförelsen bygger på praktiskt insamlad data från en FMCW (Frequency Modulated Continious Wave) radar. Jämförelsen siktar på att validera att ESPRIT fungerar, samt dess konkurrersförmåga mot den andra algoritmen. Jämförelsen utgick från två kriterier: Noggranhet och komplexitet. Avhandlingen presenterar även möjliga optimiseringar som kan förbättra ESPRITs förmåga att estimera DOA. Dessa är ökning av antalet antenner som används i DOA estimeringen, samt att använda förbehandlingsschemat Spatial smoothing. Resultatet för DOA estimering visar att ESPRITs' styrka ligger i att kunna detektera flera objekt på samma avstånd. Skillnaden mellan ESPRIT och den andra DOA estimerings algoritmen, vid estimering av ett objekt var inte tillräckligt signifikant för att dra några slutsatser. Resultatet visade också att ESPRITs' prestationsförmåga ökar med antalet antenner, samt vilket förbehandlingsschema som används. Resultatet för komplexitet visade att ESPRIT har högre komplexitet än den andra DOA estimerings algoritmen. För att ESPRIT ska kunna nyttja sin styrka, att kunna detektera flera objekt på samma distans, krävs implementation av komplexa förbehandlingsscheman. Detta ökar skillnaden på komplexitet mellan de två jämförda algoritmerna ytterliggare.

Försvarsmakten är under en återuppbyggnad och står inför en stor nyanskaffning av materiel till samtliga delar av organisationen. 161. Stridsledning- och luftbevakningsbataljonen skall utöka och ersätta delar av den befintliga sensorkedjan med nya system där det finns utrymme för anskaffning av rörliga markbaserade radarsystem. Tidigare forskning och rapporter från bland annat FOI och Försvarsmakten kopplat mot framtidens radarsensorer tyder på att AESA-radarer är väl lämpliga vid en framtida anskaffning. Arbetet är av tekniskt beskrivande karaktär och använder teorin om militär nytta samt analysverktyget multimålmetoden. Arbetets syfte är att undersöka om de framtagna värderingskriterierna kostnad, rörlighet, masthöjd och målupptäckt skulle kunna användas vid en svensk anskaffning av ett rörligt markbaserat radarsystem. Slutsatsen är att värderingskriterierna som tagits fram i arbetet kan och bör användas vid en anskaffning av ett rörligt markbaserat radarsystem. Dock behöver värderingskriterierna fördjupas ytterligare för att i framtida användning få fram ett mer precist resultat., The Swedish Armed Forces are undergoing a re-establishment and are facing a major new acquisition of equipment for all parts of the organization. 161. Combat Control and Air Surveillance Battalion will increase and replace parts of the existing sensor chain with new systems where there is room for the acquisition of mobile ground-based radar systems. Previous research and reports from, among others, FOI and the Swedish Armed Forces related to future radar sensors indicate that AESA radars are well suited for in a future acquisition. This report is of a technical descriptive type and uses the theory of military utility and the analysis tool multi-criteria decision. The purpose of the report is to investigate whether the valuation criteria’s cost, mobility, mast height and target detection should be used as criteria in a Swedish acquisition of a mobile ground-based radar system. The conclusion is that the evaluation criteria concluded in the report can and should be used in the acquisition of a mobile ground-based radar system. However, the evaluation criteria need to be further deepened to obtain a more precise result in future use.

A transformative revolution in transportation is coming with the advent of Au-tonomous Vehicles (AVs), which are expected to increase mobility, reduce trafficcongestion, and save fuel. Although AVs present significant advantages, they alsopose substantial challenges, particularly when it comes to security and safety. Theaim of this study is to map out the existing knowledge in order to facilitate furtherresearch and development, which will hasten the rollout of secure and reliable au-tonomous vehicles. This, in turn, will enable a sustainable and efficient future fortransportation. Research on AV safety and security is reviewed in this thesis in acomprehensive systematic literature review. The search process identified a total of283 studies published between 2019 and 2022, out of which 24 studies were selectedthrough a multi-stage process according to our predefined protocol. Based on re-search topics in selected studies, our findings have a significant impact on the fieldof Artificial Intelligence and automated vehicles. Based on our findings, we canprovide a summary of current knowledge regarding the safety, security, and stabilityimplications of autonomous vehicles. Simulations, real-life experiments, and physi-cal tests were all used in the selected articles for evaluation. Aside from the excellentresults, we identified many limitations of the articles, including the limitations of thedata sets, the analysis of unusual events, and the verification practices.

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.

This paper presents a silicon micromachined reconfigurable beam-steering frontend chip in which multiple components are integrated within a single silicon chip. The size o the whole frontend chip is 14.3×20×1.2 mm3. The signal path includes a novel switching circuit, a beam-steering network, two power-dividing networks, and a 2×8 array antenna. The presented frontend chip is able to create two frequency steerable beam-shapes. The switching circuit determines which beam shape to be radiated. The first beam-shape is a steerable broad fan-beam with reduced sidelobe level (SLL) in the H-plane, and the second is a steerable notched fan-beam. The measured SLL of the broad beam is better than 18.5 dB in the H-plane, and the measured notch depth is better than 24 dB in the E-plane pattern. Both radiation patterns can be steered by frequency and move from -20 degrees at 238 GHz to +20 degrees at 248 GHz.The measured return loss of the fabricated device is better than 15 dB at 220-265 GHz, which is equal to almost 18.6 % fractional bandwidth., QC 20230630

This thesis combines radar signal processing, with data driven artificial neuralnetwork (ANN) methods. Signal processing algorithms are often based on modelingassumptions of how the data was formed. In some cases, such models are sufficientfor designing good, or even optimal, solutions.In many cases however, these models may be too complicated to form analyticalsolutions; be too simplified, such that practical results may differ significantly fromwhat was theoretically indicated; be unknown in the sense that one of several knownmodels or parameter values may fit the data, but we do not know which; or be toocomplex such that the solution will be too heavy to compute.Data driven ANN methods provide a simple way of bridging these gaps. Wedemonstrate this in four different studies, where we make use of radar data modelsto formulate data driven solutions that are both accurate and computationallyefficient.We compare ANN based results to computationally demanding least squares,and exhaustive matched filtering approaches. We show that the performance of theANNs are comparable to these, but come at a fraction of the computational load.We train ANNs on data sampled from models using a wide range of parametervalues. This naturally handles drifts and unknown parameter values, which maychange the data, but not the desired prediction. We show that an ANN classifiertrained on data from simple models may in practice perform significantly worsethan what was expected from theory. We improve this by combining a limitedamount of real data with synthetic model data. In all cases, we make use of modelsthat are simple to evaluate. They are however not simple to analyze for the purposeof creating analytical solutions.In particular we present a method for achieving non-coherent pulse compressionthat resolves targets within a single pulse width. We present a method fordetecting weak target trajectories that does not require prior assumptions ontarget acceleration, the signal-to-noise ratio, Denna avhandling kombinerar radarsignalbehandling med datadrivna artificiellaneuronnät (ANN) metoder. Signalbehandlings algoritmer är ofta baserade påmodellantaganden om hur data kommit till. I vissa fall är sådana modeller tillräckligaför att designa bra, eller till och med optimala, lösningar.I många fall kan dock dessa modeller vara alltför komplicerade för att ta framanalytiska lösningar; vara alltför förenklade, så att resultat från praktik skiljer sigmarkant från vad som var teoretiskt väntat; vara okända i den bemärkelsen att enav många kända modeller eller parameter värden kan passa data, men vi vet intevilket; eller vara alltför komplexa så att lösningen blir för tung att beräkna.Datadrivna ANN metoder kan användas för att brygga dessa gap. Vi demonstrerar detta i fyra olika studier, där vi använder oss av modeller för radardata föratt formulera datadrivna lösningar som är både noggranna och beräkningsmässigteffektiva.Vi jämför resultat från ANN lösningar med resultat från beräkningsmässigt merkrävande minsta kvadrat och matchade filter lösningar. Vi visar att prestandan avANN är jämförbar med dessa, men kräver endast en bråkdel av beräkningarna. Vitränar ANN på data från modeller med ett brett span av parameter värden. Dettaför att hantera okända parameter värden och förändringar i dessa, som kan ändradata men inte den önskade prediktionen. Vi visar att en ANN klassificerare som ärtränad på data från enkla modeller kan prestera anmärkningsvärt sämre i praktikenfrån vad som vad var teoretiskt väntat. Vi förbättrar detta genom att kombinera enbegränsad mängd riktigt data med syntetiskt modelldata. I samtliga fall användervi oss av modeller som är enkla att exekvera. Dom är dock inte enkla att analyserai avsikt att skapa analytiska lösningar.Mer konkret presenterar vi en metod för icke-koherent pulskompression somlöser upp mål inom en pulsvidd. Vi presenterar en metod för att detektera svagamålspår som inte kräver antaganden om målets acceleration, signal-til, Reserach funder: SAABQC 20230914

This paper presents a silicon micromachined reconfigurable beam-steering frontend chip in which multiple components are integrated within a single silicon chip. The size o the whole frontend chip is 14.3×20×1.2 mm3. The signal path includes a novel switching circuit, a beam-steering network, two power-dividing networks, and a 2×8 array antenna. The presented frontend chip is able to create two frequency steerable beam-shapes. The switching circuit determines which beam shape to be radiated. The first beam-shape is a steerable broad fan-beam with reduced sidelobe level (SLL) in the H-plane, and the second is a steerable notched fan-beam. The measured SLL of the broad beam is better than 18.5 dB in the H-plane, and the measured notch depth is better than 24 dB in the E-plane pattern. Both radiation patterns can be steered by frequency and move from -20 degrees at 238 GHz to +20 degrees at 248 GHz.The measured return loss of the fabricated device is better than 15 dB at 220-265 GHz, which is equal to almost 18.6 % fractional bandwidth., QC 20230630

Accurate and efficient localization is a fundamental requirement for autonomous operation of robots, especially in areas that deny global navigation services. Localization is even more challenging in environments that present visual and geographic difficulties. This not only includes environmental aspects like darkness, fog and dust but also geometrically monotone areas. The solution that the Center for Applied Autonomous Sensor Systems at the Örebro university decided to develop is therefore a prototype of radar-only localization and mapping (SLAM) system. The radar modality is less susceptible to the environmental factors when compared to, for example, a lidar. Our goal is to support this effort by creating an odometry module that uses radar and inertial data to provide the localization for this SLAM prototype. This radar-inertial-odometry (RIO) takes radar point clouds and inertial gyroscopic data to output an odometry message usable by other components in the robot operating system (ROS). The module has been tested on two datasets representing areas typical for deployment, one consisting of underground tunnels and the other one being an outside forest environment. The dataset has been processed by two different mappers where the lidar has been used as the basic modality. This choice allows us to evaluate the odometry module in a more practical way. The final results are promising, the underground localization closely adheres to reality. The forest dataset is more challenging although it still resembles the ground-truth position in the horizontal dimension. The module's biggest shortcoming is a noticeable drift problem in the vertical z-dimension , for which we propose a constraint that limits this drift.

This thesis combines radar signal processing, with data driven artificial neuralnetwork (ANN) methods. Signal processing algorithms are often based on modelingassumptions of how the data was formed. In some cases, such models are sufficientfor designing good, or even optimal, solutions.In many cases however, these models may be too complicated to form analyticalsolutions; be too simplified, such that practical results may differ significantly fromwhat was theoretically indicated; be unknown in the sense that one of several knownmodels or parameter values may fit the data, but we do not know which; or be toocomplex such that the solution will be too heavy to compute.Data driven ANN methods provide a simple way of bridging these gaps. Wedemonstrate this in four different studies, where we make use of radar data modelsto formulate data driven solutions that are both accurate and computationallyefficient.We compare ANN based results to computationally demanding least squares,and exhaustive matched filtering approaches. We show that the performance of theANNs are comparable to these, but come at a fraction of the computational load.We train ANNs on data sampled from models using a wide range of parametervalues. This naturally handles drifts and unknown parameter values, which maychange the data, but not the desired prediction. We show that an ANN classifiertrained on data from simple models may in practice perform significantly worsethan what was expected from theory. We improve this by combining a limitedamount of real data with synthetic model data. In all cases, we make use of modelsthat are simple to evaluate. They are however not simple to analyze for the purposeof creating analytical solutions.In particular we present a method for achieving non-coherent pulse compressionthat resolves targets within a single pulse width. We present a method fordetecting weak target trajectories that does not require prior assumptions ontarget acceleration, the signal-to-noise ratio, Denna avhandling kombinerar radarsignalbehandling med datadrivna artificiellaneuronnät (ANN) metoder. Signalbehandlings algoritmer är ofta baserade påmodellantaganden om hur data kommit till. I vissa fall är sådana modeller tillräckligaför att designa bra, eller till och med optimala, lösningar.I många fall kan dock dessa modeller vara alltför komplicerade för att ta framanalytiska lösningar; vara alltför förenklade, så att resultat från praktik skiljer sigmarkant från vad som var teoretiskt väntat; vara okända i den bemärkelsen att enav många kända modeller eller parameter värden kan passa data, men vi vet intevilket; eller vara alltför komplexa så att lösningen blir för tung att beräkna.Datadrivna ANN metoder kan användas för att brygga dessa gap. Vi demonstrerar detta i fyra olika studier, där vi använder oss av modeller för radardata föratt formulera datadrivna lösningar som är både noggranna och beräkningsmässigteffektiva.Vi jämför resultat från ANN lösningar med resultat från beräkningsmässigt merkrävande minsta kvadrat och matchade filter lösningar. Vi visar att prestandan avANN är jämförbar med dessa, men kräver endast en bråkdel av beräkningarna. Vitränar ANN på data från modeller med ett brett span av parameter värden. Dettaför att hantera okända parameter värden och förändringar i dessa, som kan ändradata men inte den önskade prediktionen. Vi visar att en ANN klassificerare som ärtränad på data från enkla modeller kan prestera anmärkningsvärt sämre i praktikenfrån vad som vad var teoretiskt väntat. Vi förbättrar detta genom att kombinera enbegränsad mängd riktigt data med syntetiskt modelldata. I samtliga fall användervi oss av modeller som är enkla att exekvera. Dom är dock inte enkla att analyserai avsikt att skapa analytiska lösningar.Mer konkret presenterar vi en metod för icke-koherent pulskompression somlöser upp mål inom en pulsvidd. Vi presenterar en metod för att detektera svagamålspår som inte kräver antaganden om målets acceleration, signal-til, Reserach funder: SAABQC 20230914

The sub-THz and THz frequency ranges, that have been designated for astronomy and military, are now considered for the next generation of cellular networks. Radar systems operating in these frequency ranges are popular. Sharing the same radio frequency (RF) resources of cellular networks and radar systems opens the great potential to integrate radar system on mobile equipment. With this integration, the radar applications based on detection and ranging are available for mobile equipment. Realizing synthetic aperture radar (SAR) is also possible due to the movement of the mobile equipment that helps to synthesize an aperture larger than the physical aperture of the mobile equipment. Precise active localization in indoor environment is therefore feasible. The paper presents a discussion about active localization by realizing monostatic, bistatic, multistatic and passive SAR on mobile equipment with an integrated radar system. The simulation and experiment results shows the feasibility of the proposal. © 2023 IEEE.

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Microwave Sensing, Signals & Systems

Radar-based solutions have attracted great attention in human activity recognition (HAR) for their advantages in accuracy, robustness, and privacy protection. The conventional approaches transform radar signals into feature maps and then directly process them as visual images. While effective, these image-based methods may not be the best solutions in terms of representation efficiency to encode the relevant information for classification. This article proposes a novel HAR method combining sparse theory and PointNet network, with both operations in the time-Doppler (TD) and range-Doppler (RD) domains. First, sparsity-based feature extraction is introduced to use a limited number of sparse solutions to characterize human activities in the form of TD sparse point clouds (TDSP) or dynamic RD sparse point clouds (DRDSP). This new representation is validated by comparing the reconstructed and original signals. Then, PointNet networks are adopted to summarize multidomain features and predict human activity labels by a sparse set of input point clouds. Comprehensive experiments were conducted to demonstrate that the proposed method can yield a higher representation efficiency, classification accuracy, and better generalization capability than existing ones., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Microwave Sensing, Signals & Systems

Two designs of lagrangian low-cost drifting buoys have been developed in order to monitor the ocean surface dynamics in the North-west Iberian Peninsula and provide ground-truth observations that can be used to assess the performance of High Frequency (HF) Radars of RAIA observatory from 2020 to 2022. Since regression model type I, which is typically used in buoy-HF radar antennas validations, does not consider the presence of errors in the observations from both instruments, regression model type II was proposed to instrument intercomparison. Furthermore, a new metric was developed to better assess both model types regressions in lagrangian validations., Peer Reviewed

The difficulties in the communication between the deaf and normal people through sign language can be overcome by implementing deep learning in the gestures signal recognition. The use of the Convolution Neural Network (CNN) in distinguishing radar-based gesture signals of deaf sign language has not been investigated. This paper describes the recognition of gestures of deaf sign language using radar and CNN. Six gestures of deaf sign language were acquired from normal subjects using a radar system and processed. Short-time Fourier Transform was performed to extract the gestures features and the classification was performed using CNN. The performance of CNN was examined using two types of inputs; segmented and non-segmented spectrograms. The accuracy of recognising the gestures is higher (92.31%) using the non-segmented spectrograms compared to the segmented spectrogram. The radar-based deaf sign language could be recognised accurately using CNN without segmentation.

Volcanic processes play a key role in the formation and evolution of terrestrial planets in the Solar System. On Earth, volcanism drives the recycling and growth of crustal material and is a major resurfacing mechanism. On other planets like Mars, volcanism reshaped almost 60 percent of its surface. This activity later waned, leaving behind a record of these changes in the subsurface stratigraphy. Orbital and in-situ radar remote sensing techniques can penetrate into these units and unpack the stratigraphy and geologic history of volcanic regions on Mars and Earth. The work contained in this dissertation utilizes orbital and ground-penetrating radar remote sensing techniques to map and interpret stratigraphy in what are primarily volcanic settings on Mars and Earth. An introduction to volcanism on Mars and Earth are included in Chapter 1, including an overview of radar remote sensing in planetary science. The discussion of Earth volcanism will specifically discuss Icelandic styles as Chapter 4 focuses solely on deposits associated with the Icelandic highlands volcano, Askja. Chapters 2 and 3 are investigations utilizing orbital and ground-penetrating radar, respectively, to map and characterize emplaced materials in two primarily volcanic environments on Mars. In Chapter 2, we map lava flows and other deposits near the volcano Ascraeus Mons in the Tharsis Volcanic Province. We also examine the radar characteristics of these deposits to determine the primary drivers of successful subsurface sounding are in these terrains. In Chapter 3, we utilize similar analysis techniques characterize and map the subsurface stratigraphy the floor of Jezero crater using the ground-penetrating radar payload on the Perseverance rover. We infer a volcanic origin for the crater floor units we examined and discuss the stratigraphy there as revealed from the radar data. Chapter 4 focuses on how radar can be used to satisfy in-situ resource utilization objectives and strategies for interpr

This paper presents a silicon micromachined reconfigurable beam-steering frontend chip in which multiple components are integrated within a single silicon chip. The size o the whole frontend chip is 14.3×20×1.2 mm3. The signal path includes a novel switching circuit, a beam-steering network, two power-dividing networks, and a 2×8 array antenna. The presented frontend chip is able to create two frequency steerable beam-shapes. The switching circuit determines which beam shape to be radiated. The first beam-shape is a steerable broad fan-beam with reduced sidelobe level (SLL) in the H-plane, and the second is a steerable notched fan-beam. The measured SLL of the broad beam is better than 18.5 dB in the H-plane, and the measured notch depth is better than 24 dB in the E-plane pattern. Both radiation patterns can be steered by frequency and move from -20 degrees at 238 GHz to +20 degrees at 248 GHz.The measured return loss of the fabricated device is better than 15 dB at 220-265 GHz, which is equal to almost 18.6 % fractional bandwidth., QC 20230630