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For optical propagation through the turbulent atmosphere, the angle of arrival (AOA) cross-correlation function obtained from two spatially separated light sources carries information regarding the transverse wind velocity averaged along the propagation path. Two methods for the retrieval of the beam transverse horizontal wind velocity, v_t, based on the estimation of the time delay to the peak and the slope at zero lag of the AOA cross-correlation function, are presented. Data collected over a two week long experimental campaign conducted at the Boulder Atmospheric Observatory (BAO) site near Erie, CO was analyzed. The RMS difference between 10 s estimates of v_t retrieved optically, and 10 s averages of the transverse horizontal wind velocity measured by an ultrasonic anemometer, was found to be 14 cm/s for the time-delay-to- peak method and 20 cm/s for the slope-at-zero-lag method, for a 2 h period beginning 0345 MDT on 16 June, 2010, during which the transverse horizontal wind velocity varied between -1 m/s and 2 m/s.

Direction of Arrival estimation using unsteered antenna arrays, unlike mechanically scanned or phased arrays, requires complex algorithms which perform poorly with small aperture arrays or without a large number of observations, or snapshots. In general, these algorithms compute a sample covriance matrix to obtain the direction of arrival and some require a prior estimate of the number of signal sources. Herein, artificial neural network architectures are proposed which demonstrate improved estimation of the number of signal sources, the true signal covariance matrix, and the direction of arrival. The proposed number of source estimation network demonstrates robust performance in the case of coherent signals where conventional methods fail. For covariance matrix estimation, four different network architectures are assessed and the best performing architecture achieves a 20 times improvement in performance over the sample covariance matrix. Additionally, this network can achieve comparable performance to the sample covariance matrix with 1/8-th the amount of snapshots. For direction of arrival estimation, preliminary results are provided comparing six architectures which all demonstrate high levels of accuracy and demonstrate the benefits of progressively training artificial neural networks by training on a sequence of sub- problems and extending to the network to encapsulate the entire process.

Poaching is a persistent issue that threatens many of earth’s species including therhino. The methods used by poachers are varied, but many use guns to carry outtheir illegal activities. Gunfire is extremely loud and can be heard for kilometres.This thesis investigates whether it is possible to aid anti-poaching efforts in Kenyawith a gunshot detection and estimation device using an array of microphones. Ifsuccessful, the device could be placed around the savannah or any exposed areaand warn if poaching is taking place in the nearby. If a shot is fired within theaudible range of the device’s microphones, a trained machine learning algorithmdetects the shot on the edge using a microprocessor. The detection runs in realtime and achieved an accuracy of 93% on an unbalanced data set, where themajority class was the one without gunshots. Once a detection has been made, thereceived signal power to each microphone is used to produce a direction of arrivalestimate. The estimate can produce an angle estimate with a standard deviationof 66.78° for a gunshot, and with a standard deviation of 7.65° when testing themodel with white noise. Future implementations could use several devices thatdetected the same event, and fuse their estimates to locate the shooter’s position.All of this information, as well as the sound file, can be used to alert and assistlocal wildlife services. The challenges of this project have been centred aroundmaking a system run in real time with only a microprocessor on the edge, whilealso prioritizing low cost components for future deployment. / Project Ngulia

Le Timepix3, successeur du Timepix, est un détecteur au silicium composé de deux couches sensibles installées en parallèle. Chaque couche est munie d’une matrice de 65 536 pixels (256x256) et d’une épaisseur de 500 μm. Une des améliorations du Timepix3 par rapport aux générations précédentes est qu’il est possible de récolter simultanément la quantité de charge déposée ainsi que le temps d’arrivée de cette charge. Pour la prise de données Run 3 du LHC qui a débuté en 2022, 16 détecteurs Timepix3 ont été installés dans la caverne du détecteur ATLAS. Les Timepix3 seront utilisés pour mesurer la luminosité du faisceau du LHC ainsi que pour caractériser et mesurer la radiation dans la caverne ATLAS, où beaucoup de composantes électroniques sont installés. L’objet de cette maitrise est de développer un algorithme d’identification des particules qui frappe le détecteur Timepix3. Dans un premier temps, l’information de la quantité d’énergie déposée et du temps d’arrivée sera utilisée pour caractériser un champ de particules incidentes au détecteur Timepix3 (électrons, photons, particules lourdes chargées). La nouvelle méthode consiste à utiliser les paramètres physiques des particules lors de leurs interactions avec le milieu, tels que la trajectoire, l’angle d’incidence, le dépôt d’énergie, la densité spatiale de l’amas, densité énergétique le long de la trajectoire de la particule incidente. Dans un second temps, comme les rayons delta sont des effets récurrents et indésirables qui perturbent l’analyse des données en physique des particules, ce mémoire traitera de la façon de les supprimer pour ne récolter que l’énergie déposée directement par la particule incidente. Il sera aussi question d’utiliser la statistique liée à la production des rayons delta lors du passage d’un flux de particules dans le détecteur pour en déterminer l’énergie cinétique. L’algorithme développé pour caractériser un champ de particules avec le Timepix3 a été confronté aux données obtenues avec un cyclotron de protons à Aahrus au Danemark. Nous avons obtenu des résultats satisfaisants, étant donné que la majorité des particules sont identifiées comme des protons et que nous avons réussi à déterminer l’énergie cinétique de ces protons qui se rapproche de l’énergie cinétique du faisceau de protons utilisé. / The Timepix3, successor to the Timepix, is a silicon detector composed of two sensitive layers mounted in parallel. Each layer has a matrix of 65 536 pixels (256x256) and a thickness of 500 μm. One of the improvements of the Timepix3 compared to previous generations is that it is possible to simultaneously collect the quantity of charge deposited as well as the time of arrival of this charge. For the LHC Run 3 data taking which started in 2022, 16 Timepix3 detectors were installed in the ATLAS detector cavern. The Timepix3 will be used to measure the luminosity of the LHC beam as well as to characterize and measure the radiation in the ATLAS cavern, where many electronic components are installed. The purpose of this master thesis is to develop an algorithm for identifying particles that strike the Timepix3 detector. Initially, information on the amount of energy deposited and the time of arrival will be used to characterize a field of particles incident at the Timepix3 detector (electrons, photons, heavy charged particles). The new method consists in using the physical parameters of the particles during their interactions with the medium, such as the trajectory, the angle of incidence, the energy deposition, the spatial density of the cluster, energy density along the trajectory of the incident particle. Secondly, as delta rays are recurring and undesirable effects which disturb the analysis of data in particle physics, this thesis will deal with how to suppress them in order to harvest only the energy deposited directly by the incident particle. It will also be a question of using the statistics linked to the production of delta rays when a flow of particles passes through the detector to determine their kinetic energy. The algorithm developed to characterize a particle field with the Timepix3 was confronted with data obtained with a proton cyclotron at Aahrus in Denmark. We have obtained satisfactory results, given that the majority of the particles are identified as protons and that we have succeeded in determining the kinetic energy of these protons which is close to the kinetic energy of the proton beam used.

In recent years, unmanned aerial vehicles (UAV), also called drones, have experienced a rapid increase, which leads to the concern of illegal use of them. Passive RF is one of the effective ways to detect drones by receiving drones’ communication signals. After receiving the signal from drones, one can utilize the prior knowledge of signal characteristics for identifying and locating the drones. The angle of arrival (AoA) measured by multiple passive RF sensors can be used for localization by triangulation. However, the accuracy of the AoA measured by the passive RF sensors is strongly affected by the environment. In particular in urban areas, the multipath effect is prominent due to the building blockage and complicated terrestrial conditions that introduce certain errors to the result. So the service provider of the sensors needs a tool to perform the environment analysis to understand the quality of the service. A fast tool that can simulate the sensor network and surrounding environment can offer a flexible solution to optimize the sensor coverage and indicate the blind zone of detection. Especially when the sensors are deployed on the mobile platform, such tool can significantly improve the defensive quality of the drone detection system by optimizing real-time deployment and indicating low observable areas. In order to plan the sensor locations and assess the performance after the deployment of the sensor at a fast speed, We propose a multipath-based model to calculate the AoA error. The model is able to utilize the input of geometrical information for simulating the AoA error within a region. In this thesis, we investigate the outdoor channel at 2.4GHz using the ray-tracing method as it is the most used channel for UAVs. Massive simulations have been carried out and real test flights have been conducted to evaluate the accuracy of the modeling. Both simulations and test flights are carried out in Kista center where buildings are from high-rises to one-floor houses with various heights. In the simulation, the AoA is obtained by MUltiple SIgnal Classification (MUSIC) algorithm. Test flights are conducted using an existing Software-defined radio (SDR) based RF sensor. We tried our best to carry out the same trajectories in both simulations and test flights to provide fair comparisons. The simulation results show that the multipath model can predict the trend of AoA error when the height changes, while not sufficient to predict the error when the 2D position changes. Thus, to more accurately characterize the signal transmission, it is essential to extend this thesis to include more detailed environmental information and adaption based on measurement. / Under de senaste åren har obemannade flygfarkoster (UAV), även kallade drönare, ökat snabbt, vilket leder till oro för olaglig användning av dem. Passiv RF är ett av de effektiva sätten att upptäcka drönare genom att ta emot drönarnas kommunikationssignaler. Efter att ha tagit emot signalen från drönare kan man använda den tidigare kunskapen om signalegenskaperna för att identifiera och lokalisera drönarna. AoA som mäts av flera passiva RF-sensorer kan användas för lokalisering genom triangulering. Noggrannheten hos AoA som mäts av de passiva RF-sensorerna påverkas dock starkt av miljön. Särskilt i stadsområden är multipath-effekten framträdande på grund av byggnadsblockering och komplicerade markförhållanden som medför vissa fel i resultatet. Därför behöver leverantören av sensorer ett verktyg för att utföra miljöanalysen för att förstå tjänstens kvalitet. Ett snabbt verktyg som kan simulera sensornätverket och den omgivande miljön kan erbjuda en flexibel lösning för att optimera sensortäckningen och ange den blinda zonen för upptäckt. Särskilt när sensorerna placeras på en mobil plattformkan ett sådant verktyg avsevärt förbättra drönardetektionssystemets försvarskvalitet genom att optimera utplaceringen i realtid och ange områden med låg observationsgrad. För att planera sensorernas placering och bedöma prestandan efter att sensorn har placerats ut i snabb takt föreslår vi en multipath-baserad modell för att beräkna AoAfelet. Modellen kan utnyttja inmatningen av geometrisk information för att simulera AoA-felet inom ett område. I denna avhandling undersöker vi utomhuskanalen vid 2:4 GHz med hjälp av raytracing- metoden eftersom det är den mest använda kanalen för UAV:er. Massiva simuleringar har utförts och verkliga testflygningar har genomförts för att utvärdera modelleringens noggrannhet. Både simuleringar och testflygningar har utförts i Kista centrum där byggnaderna är allt från höghus till envåningshus med olika höjd. I simuleringen erhålls AoA med hjälp av MUSIC-algoritmen. Testflygningar genomförs med hjälp av en befintlig SDR-baserad RF-sensor. Vi gjorde vårt bästa för att utföra samma banor i både simuleringar och testflygningar för att ge rättvisa jämförelser. Simuleringsresultaten visar att multipathmodellen kan förutsäga trenden för AoA-felet när höjden ändras, medan den inte är tillräcklig för att förutsäga felet när 2D-positionen ändras. För att mer exakt karakterisera signalöverföringen är det därför viktigt att utöka denna avhandling till att omfatta mer detaljerad miljöinformation och anpassning baserad på mätning.

Due to the massive increase of active transmitters broadcasting over wideband frequencies, such as 5G wireless systems, LEO/MEO satellites, satellite constellations, and the increase of IoT devices in the average home, the radio frequency spectrum is becoming more and more congested by interference. Passive receivers face additional challenges due to the growing use of wideband frequency transmissions aimed at boosting communication system throughput. As a result, passive receivers must adopt more robust and intricate techniques to mitigate radio frequency interference. A proposed RFI removal system, known as the true time delay Hadamard projection algorithm, has been introduced in previous work to eliminate a single RFI source while preserving a narrowband signal of interest. An RF frontend is developed to assess the effectiveness of the Hadamard projection algorithm implemented on an RFSoC ZCU216. Additionally, the TTD Hadamard projection algorithm is expanded to enable the cancellation of multiple RFI sources rather than just a single source for a uniform linear array and a uniform rectangular array. Over-the-air tests are conducted to verify the performance of the interference cancellation algorithms and demonstrate the algorithms' ability to preserve the signals of interest while removing the wideband interference. Multiple algorithms are proposed to estimate the time delays used by the interference cancellation algorithm to effectively eliminate wideband interference. These algorithms address diverse scenarios encompassing interference sources ranging from strong to weak SNR. Detailed reports of algorithm performance provide insights into their effectiveness and suitability across specific interference conditions.

Introduktion: Antalet prehospitala förlossningar är få och därför kan det vara svårt för ambulanspersonal att upprätthålla tillräcklig kompetens inom området. Eftersom det händer sällan kan det väcka oro hos sjuksköterskor. Syfte: Syftet med studien var att beskriva sjuksköterskors erfarenheter av att vårda vid prehospital förlossning. Metod: En kvalitativ metod användes med semistrukturerade intervjuer som analyserades med hjälp av kvalitativ innehållsanalys med induktiv manifest ansats. Nio sjuksköterskor verksamma i norra Sverige inkluderades. Resultat: Resultatet presenteras i fem kategorier; Vikten av information och förberedelse, Stress och oro för komplikationer, En känsla av skräckblandad förtjusning, Stöd och samarbete minskar oron och Kunskap och erfarenhet ökar upplevelsen av trygghet. Resultatet visade att sjuksköterskor inom ambulanssjukvården känner en skräckblandad förtjusning när det kommer till att ta sig an uppgiften att bistå vid en förlossning prehospitalt. Det är en arbetsuppgift som skänker glädje i slutändan men vägen dit kan vara fylld av stress, oro och en upplevelse av brist på kunskap inom området. Slutsats: Förlossningar är ett uppdrag som sjuksköterskor inom ambulansen känner sig mindre förberedda på, det är en sällanhändelse och det gör att de inte kan tillägna sig den erfarenheten de önskar. Det finns ett behov av ökad kunskap och övning inom området.

Sensor network performance is governed by the physical placement of sensors and their geometric relationship to the events they measure. To illustrate this, the entirety of this thesis covers the following interconnected subjects: 1) graphical analysis of the variance of the estimation error caused by physical characteristics of an acoustic target source and its geometric location relative to sensor arrays, 2) event/anomaly detection method for time aggregated point sensor data using a parametric Poisson distribution data model, 3) a sensor reduction or placement technique using Bellman optimal estimates of target agent dynamics and probabilistic training data (Goode, Chin, & Roan, 2011), and 4) transforming event monitoring point sensor data into event detection and classification of the direction of travel using a contextual, joint probability, causal relationship, sliding window, and geospatial intelligence (GEOINT) method. / Master of Science

In the sixth generation of wireless communication systems (6G), there exist multiple candidate enabling technologies that help the wireless network satisfy the ever-increasing demand for speed, coverage, reliability, and mobility. Among these technologies, reconfigurable intelligent surfaces (RISs) extend the coverage of a wireless network into dead zones, increase capacity, and facilitate integrated sensing and communications tasks by consuming very low power, thus contributing to energy efficiency as well. RISs are meta-material-based devices whose electromagnetic reflection characteristics can be controlled externally to cater to the needs of the communication links. Most ubiquitously, this comes in the form of adding a desired phase shift to an incident wave before reflecting it, which can be used to phase-align multiple incident waves to increase the strength of the signal at the receiver and provide coverage to an area that otherwise would be a dead zone. While this portrays an image of a dream technology that would boost the existing wireless networks significantly, RISs do not come without engineering problems. First of all, the individual elements do not exhibit ideal reflection characteristics, that is, they attenuate the incident signal in a fashion depending on the configured phase shift. This creates the phenomenon called "phase-dependent amplitude". Another problem caused by RISs is the channel estimation overhead. In a multiple-antenna communication system, the channel between two terminals is as complex as the product of the number of antennas at each end. However, when an RIS comes into the equation, the cascade of the transmitter-RIS and RIS-receiver channels has a complexity further multiplied by the number of RIS elements. Consequently, the channel estimation process to utilize the RIS effectively becomes more demanding, that is, more pilot signals are required to estimate the channel for coherent reception. This adversely affects the effective data rate within a communication system since more resources need to be spent for pilot transmission and fewer resources can be allocated for data transmission. While there exists some work on reducing the channel dimensions by exploiting the channel structure, this problem persists for unstructured channels. In addition, for the wireless networks using multiple RISs, a new kind of pilot contamination arises, which is the main topic of this thesis. In the first part of this thesis, we study this new kind of pilot contamination in a multi-operator context, where two operators provide services to their respective served users and share a single site. Each operator has a single dedicated RIS and they use disjoint frequency bands, but each RIS inadvertently reflects the transmitted uplink signals of the user equipment devices in multiple bands. Consequently, the concurrent reflection of pilot signals during the channel estimation phase introduces a new inter-operator pilot contamination effect. We investigate the implications of this effect in systems with either deterministic or correlated Rayleigh fading channels, specifically focusing on its impact on channel estimation quality, signal equalization, and channel capacity. The numerical results demonstrate the substantial degradation in system performance caused by this phenomenon and highlight the pressing need to address inter-operator pilot contamination in multi-operator RIS deployments. To combat the negative effect of this new type of pilot contamination, we propose to use orthogonal RIS configurations during uplink pilot transmission, which can mitigate or eliminate the negative effect of inter-operator pilot contamination at the expense of some inter-operator information exchange and orchestration. In the second part of this thesis, we consider a single-operator-two-RIS integrated sensing and communication (ISAC) system where the single user is both a communication terminal and a positioning target. Based on the uplink positioning pilots, the base station aims to estimate both the communication channel and the user's position within the indoor environment by estimating the angle of arrival (AoA) of the impinging signals on both RISs and then exploiting the system and array geometries to estimate the user position and user channels respectively. Although there is a single operator, due to the presence of multiple RISs, pilot contamination occurs through the same physical means as multi-operator pilot contamination unless the channel estimation process is parameterized. Since the communication links are considered to be pure line-of-sight (LOS), their structure allows the reduction of the number of unknown parameters. Consequently, the reduction of information caused by pilot contamination does not affect the channel estimation procedure, hence the pilot contamination is overcome. On the other hand, the position of the user is determined by intersecting the lines drawn along the AoA estimates. We adopt the Cramér-Rao Lower Bound (CRLB), the lower bound on the mean squared error (MSE) of any unbiased estimator, for both channel estimation and positioning. Our numerical results show that it is possible to utilize positioning pilots for parametric channel estimation when the wireless links are LOS. / <p>QC 20240416</p>