Um modelo espaço-temporal aplicado à agricultura de precisão

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Diagnose de trincas em sistemas rotativos, utilizando modelos de falhas através da metodologia dos observadores de estados

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Diagnóstico de falhas via observadores de estado com excitações desconhecidas, identificadas via funções ortogonais

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Agricultural commodities pricing model applied to the Brazilian sugar market

This article suggests a pricing model for commodities used to produce biofuel. The model is based on the concept that the deterministic component of the Wiener process is not constant and depends on time and exogenous variables. The model, which incorporates theory of storage, the convenience yield and the seasonality of harvests, was applied in the Brazilian sugar market. After predictions were made with the Kalman filter, the model produced results that were statistically more accurate than those returned by the two-factor model available in the literature.

A dynamical system approach to data assimilation in chaotic models

The Assimilation in the Unstable Subspace (AUS) was introduced by Trevisan and Uboldi in 2004, and developed by Trevisan, Uboldi and Carrassi, to minimize the analysis and forecast errors by exploiting the flow-dependent instabilities of the forecast-analysis cycle system, which may be thought of as a system forced by observations. In the AUS scheme the assimilation is obtained by confining the analysis increment in the unstable subspace of the forecast-analysis cycle system so that it will have the same structure of the dominant instabilities of the system. The unstable subspace is estimated by Breeding on the Data Assimilation System (BDAS). AUS- BDAS has already been tested in realistic models and observational configurations, including a Quasi-Geostrophicmodel and a high dimensional, primitive equation ocean model; the experiments include both fixed and“adaptive”observations. In these contexts, the AUS-BDAS approach greatly reduces the analysis error, with reasonable computational costs for data assimilation with respect, for example, to a prohibitive full Extended Kalman Filter. This is a follow-up study in which we revisit the AUS-BDAS approach in the more basic, highly nonlinear Lorenz 1963 convective model. We run observation system simulation experiments in a perfect model setting, and with two types of model error as well: random and systematic. In the different configurations examined, and in a perfect model setting, AUS once again shows better efficiency than other advanced data assimilation schemes. In the present study, we develop an iterative scheme that leads to a significant improvement of the overall assimilation performance with respect also to standard AUS. In particular, it boosts the efficiency of regime’s changes tracking, with a low computational cost. Other data assimilation schemes need estimates of ad hoc parameters, which have to be tuned for the specific model at hand. In Numerical Weather Prediction models, tuning of parameters — and in particular an estimate of the model error covariance matrix — may turn out to be quite difficult. Our proposed approach, instead, may be easier to implement in operational models.

Design and implementation of a novel multi-constellation FPGA-based dual frequency GNSS receiver for space applications

The PhD activity described in the document is part of the Microsatellite and Microsystem Laboratory of the II Faculty of Engineering, University of Bologna. The main objective is the design and development of a GNSS receiver for the orbit determination of microsatellites in low earth orbit. The development starts from the electronic design and goes up to the implementation of the navigation algorithms, covering all the aspects that are involved in this type of applications. The use of GPS receivers for orbit determination is a consolidated application used in many space missions, but the development of the new GNSS system within few years, such as the European Galileo, the Chinese COMPASS and the Russian modernized GLONASS, proposes new challenges and offers new opportunities to increase the orbit determination performances. The evaluation of improvements coming from the new systems together with the implementation of a receiver that is compatible with at least one of the new systems, are the main activities of the PhD. The activities can be divided in three section: receiver requirements definition and prototype implementation, design and analysis of the GNSS signal tracking algorithms, and design and analysis of the navigation algorithms. The receiver prototype is based on a Virtex FPGA by Xilinx, and includes a PowerPC processor. The architecture follows the software defined radio paradigm, so most of signal processing is performed in software while only what is strictly necessary is done in hardware. The tracking algorithms are implemented as a combination of Phase Locked Loop and Frequency Locked Loop for the carrier, and Delay Locked Loop with variable bandwidth for the code. The navigation algorithm is based on the extended Kalman filter and includes an accurate LEO orbit model.

Assessment of Daily Life Mobility Levels using Wearable Inertial Sensors and Minimun Measured Input Models

Tracking activities during daily life and assessing movement parameters is essential for complementing the information gathered in confined environments such as clinical and physical activity laboratories for the assessment of mobility. Inertial measurement units (IMUs) are used as to monitor the motion of human movement for prolonged periods of time and without space limitations. The focus in this study was to provide a robust, low-cost and an unobtrusive solution for evaluating human motion using a single IMU. First part of the study focused on monitoring and classification of the daily life activities. A simple method that analyses the variations in signal was developed to distinguish two types of activity intervals: active and inactive. Neural classifier was used to classify active intervals; the angle with respect to gravity was used to classify inactive intervals. Second part of the study focused on extraction of gait parameters using a single inertial measurement unit (IMU) attached to the pelvis. Two complementary methods were proposed for gait parameters estimation. First method was a wavelet based method developed for the estimation of gait events. Second method was developed for estimating step and stride length during level walking using the estimations of the previous method. A special integration algorithm was extended to operate on each gait cycle using a specially designed Kalman filter. The developed methods were also applied on various scenarios. Activity monitoring method was used in a PRIN’07 project to assess the mobility levels of individuals living in a urban area. The same method was applied on volleyball players to analyze the fitness levels of them by monitoring their daily life activities. The methods proposed in these studies provided a simple, unobtrusive and low-cost solution for monitoring and assessing activities outside of controlled environments.

Gait analysis using a single wearable inertial measurement unit

Procedures for quantitative walking analysis include the assessment of body segment movements within defined gait cycles. Recently, methods to track human body motion using inertial measurement units have been suggested. It is not known if these techniques can be readily transferred to clinical measurement situations. This work investigates the aspects necessary for one inertial measurement unit mounted on the lower back to track orientation, and determine spatio-temporal features of gait outside the confines of a conventional gait laboratory. Apparent limitations of different inertial sensors can be overcome by fusing data using methods such as a Kalman filter. The benefits of optimizing such a filter for the type of motion are unknown. 3D accelerations and 3D angular velocities were collected for 18 healthy subjects while treadmill walking. Optimization of Kalman filter parameters improved pitch and roll angle estimates when compared to angles derived using stereophotogrammetry. A Weighted Fourier Linear Combiner method for estimating 3D orientation angles by constructing an analytical representation of angular velocities and allowing drift free integration is also presented. When tested this method provided accurate estimates of 3D orientation when compared to stereophotogrammetry. Methods to determine spatio-temporal features from lower trunk accelerations generally require knowledge of sensor alignment. A method was developed to estimate the instants of initial and final ground contact from accelerations measured by a waist mounted inertial device without rigorous alignment. A continuous wavelet transform method was used to filter and differentiate the signal and derive estimates of initial and final contact times. The technique was tested with data recorded for both healthy and pathologic (hemiplegia and Parkinson’s disease) subjects and validated using an instrumented mat. The results show that a single inertial measurement unit can assist whole body gait assessment however further investigation is required to understand altered gait timing in some pathological subjects.

Target Tracking in UWB Multistatic Radars

Detection, localization and tracking of non-collaborative objects moving inside an area is of great interest to many surveillance applications. An ultra- wideband (UWB) multistatic radar is considered as a good infrastructure for such anti-intruder systems, due to the high range resolution provided by the UWB impulse-radio and the spatial diversity achieved with a multistatic configuration. Detection of targets, which are typically human beings, is a challenging task due to reflections from unwanted objects in the area, shadowing, antenna cross-talks, low transmit power, and the blind zones arised from intrinsic peculiarities of UWB multistatic radars. Hence, we propose more effective detection, localization, as well as clutter removal techniques for these systems. However, the majority of the thesis effort is devoted to the tracking phase, which is an essential part for improving the localization accuracy, predicting the target position and filling out the missed detections. Since UWB radars are not linear Gaussian systems, the widely used tracking filters, such as the Kalman filter, are not expected to provide a satisfactory performance. Thus, we propose the Bayesian filter as an appropriate candidate for UWB radars. In particular, we develop tracking algorithms based on particle filtering, which is the most common approximation of Bayesian filtering, for both single and multiple target scenarios. Also, we propose some effective detection and tracking algorithms based on image processing tools. We evaluate the performance of our proposed approaches by numerical simulations. Moreover, we provide experimental results by channel measurements for tracking a person walking in an indoor area, with the presence of a significant clutter. We discuss the existing practical issues and address them by proposing more robust algorithms.

Study of 3 Lambda H and 4 Lambda H in the reaction of 6 Li + 12 C at 2 A GeV

Die Produktion von Hyperkernen wurde in peripheren Schwerionenreaktionen untersucht, bei denen eine Kohlenstofffolie mit $^6$Li Projektilen mit einer Strahlenergie von $2 A$~GeV bestrahlt wurde. Es konnten klare Signale f{"{u}}r $Lambda$, $^3_{Lambda}$H, $^4_{Lambda}$H in deren jeweiligen invarianten Massenverteilungen aus Mesonenzerfall beobachtet werden.rnrnIn dieser Arbeit wird eine unabh{"{a}}ngige Datenauswertung vorgelegt, die eine Verifizierung fr"{u}herer Ergebnisse der HypHI Kollaboration zum Ziel hatte. Zu diesem Zweck wurde eine neue Track-Rekonstruktion, basierend auf einem Kalman-Filter-Ansatz, und zwei unterschiedliche Algorithmen zur Rekonstruktion sekund"{a}rer Vertices entwickelt.rn%-Rekonstruktionsalgorithmen .rnrnDie invarianten Massen des $Lambda$-Hyperon und der $^3_{Lambda}$H- und $^4_{Lambda}$H-Hyperkerne wurden mit $1109.6 pm 0.4$, $2981.0 pm 0.3$ und $3898.1 pm 0.7$~MeV$/c^2$ und statistischen Signifikanzen von $9.8sigma$, $12.8sigma$ beziehungsweise $7.3sigma$ bestimmt. Die in dieser Arbeit erhaltenen Ergebnisse stimmen mit der fr{"{u}}heren Auswertung {"{u}}berein.rnrnDas Ausbeutenverh{"{a}}ltnis der beiden Hyperkerne wurde als $N(^3_{Lambda}$H)/$N(^4_{Lambda}$H)$ sim 3$ bestimmt. Das deutet darauf hin, dass der Produktionsmechanismus f{"{u}}r Hyperkerne in Schwerionen-induzierten Reaktionen im Projektil-Rapidit{"{a}}tsbereich nicht allein durch einen Koaleszenzmechanismus beschrieben werden kann, sondern dass auch sekund{"{a}}re Pion-/Kaon-induzierte Reaktionen und Fermi-Aufbruch involviert sind.rn

Studio ed implementazione di algoritmi per la navigazione inerziale di velivoli autonomi ad ala rotante

I sistemi di navigazione inerziale, denominati INS, e quelli di navigazione inerziale assistita, ovvero che sfruttano anche sensori di tipo non inerziale come ad esempio il GPS, denominati in questo caso INS/GPS, hanno visto un forte incremento del loro utilizzo soprattutto negli ultimi anni. I filtri complementari sfruttano segnali in ingresso che presentano caratteristiche complementari in termine di banda. Con questo lavoro di tesi mi sono inserito nel contesto del progetto SHERPA (Smart collaboration between Humans and ground-aErial Robots for imProving rescuing activities in Alpine environments), un progetto europeo, coordinato dall'Università di Bologna, che prevede di mettere a punto una piattaforma robotica in grado di aiutare i soccorritori che operano in ambienti ostili, come quelli del soccorso alpino, le guardie forestali, la protezione civile. In particolare è prevista la possibilità di lanciare i droni direttamente da un elicottero di supporto, per cui potrebbe essere necessario effettuare l'avvio del sistema in volo. Ciò comporta che il sistema di navigazione dovrà essere in grado di convergere allo stato reale del sistema partendo da un grande errore iniziale, dal momento che la fase di inizializzazione funziona bene solo in condizioni di velivolo fermo. Si sono quindi ricercati, in special modo, schemi che garantissero la convergenza globale. Gli algoritmi implementati sono alla base della navigazione inerziale, assistita da GPS ed Optical Flow, della prima piattaforma aerea sviluppata per il progetto SHERPA, soprannominata DreamDroneOne, che include una grande varietà di hardware appositamente studiati per il progetto, come il laser scanner, la camera termica, ecc. Dopo una panoramica dell'architettura del sistema di Guida, Navigazione e Controllo (GNC) in cui mi sono inserito, si danno alcuni cenni sulle diverse terne di riferimento e trasformazioni, si descrivono i diversi sensori utilizzati per la navigazione, si introducono gli AHRS (Attitude Heading Rference System), per la determinazione del solo assetto sfruttando la IMU ed i magnetometri, si analizza l'AHRS basato su Extended Kalman Filter. Si analizzano, di seguito, un algoritmo non lineare per la stima dell'assetto molto recente, e il sistema INS/GPS basato su EKF, si presenta un filtro complementare molto recente per la stima di posizione ed assetto, si presenta un filtro complementare per la stima di posizione e velocità, si analizza inoltre l'uso di un predittore GPS. Infine viene presentata la piattaforma hardware utilizzata per l'implementazione e la validazione, si descrive il processo di prototipazione software nelle sue fasi e si mostrano i risultati sperimentali.

Statistical mapping of real environments with uwb radars

In this master thesis I evaluated the performance of a Ultra-Wide Bandwidth (UWB) radar system for indoor environments mapping. In particular, I used a statistical Bayesian approach which is able to combine all the measurements collected by the radar, including system non-idealities such as the error on the estimated antenna pointing direction or on the estimated radar position. First I verified through simulations that the system was able to provide a sufficiently accurate reconstruction of the surrounding environment despite the limitations imposed by the UWB technology. In fact, the emission of UWB pulses is limited in terms of transmitted power by international regulations. Motivated by the promising results obtained through simulations, I successively carried out a measurement campaign in a real indoor environment using a UWB commercial device. The obtained results showed that the UWB radar system is capable of providing an accurate reconstruction of indoor environments also adopting not directional antennas.

Localizzazione e tracking tramite filtri statistici in sistemi multi antenna

Uno dei temi più recenti nel campo delle telecomunicazioni è l'IoT. Tale termine viene utilizzato per rappresentare uno scenario nel quale non solo le persone, con i propri dispositivi personali, ma anche gli oggetti che le circondano saranno connessi alla rete con lo scopo di scambiarsi informazioni di diversa natura. Il numero sempre più crescente di dispositivi connessi in rete, porterà ad una richiesta maggiore in termini di capacità di canale e velocità di trasmissione. La risposta tecnologica a tali esigenze sarà data dall’avvento del 5G, le cui tecnologie chiave saranno: massive MIMO, small cells e l'utilizzo di onde millimetriche. Nel corso del tempo la crescita delle vendite di smartphone e di dispositivi mobili in grado di sfruttare la localizzazione per ottenere servizi, ha fatto sì che la ricerca in questo campo aumentasse esponenzialmente. L'informazione sulla posizione viene utilizzata infatti in differenti ambiti, si passa dalla tradizionale navigazione verso la meta desiderata al geomarketing, dai servizi legati alle chiamate di emergenza a quelli di logistica indoor per industrie. Data quindi l'importanza del processo di positioning, l'obiettivo di questa tesi è quello di ottenere la stima sulla posizione e sulla traiettoria percorsa da un utente che si muove in un ambiente indoor, sfruttando l'infrastruttura dedicata alla comunicazione che verrà a crearsi con l'avvento del 5G, permettendo quindi un abbattimento dei costi. Per fare ciò è stato implementato un algoritmo basato sui filtri EKF, nel quale il sistema analizzato presenta in ricezione un array di antenne, mentre in trasmissione è stato effettuato un confronto tra due casi: singola antenna ed array. Lo studio di entrambe le situazioni permette di evidenziare, quindi, i vantaggi ottenuti dall’utilizzo di sistemi multi antenna. Inoltre sono stati analizzati altri elementi chiave che determinano la precisione, quali geometria del sistema, posizionamento del ricevitore e frequenza operativa.

Dynamic registration using ultrasound for anatomical referencing

This paper proposes methods to circumvent the need to attach physical markers to bones for anatomical referencing in computer-assisted orthopedic surgery. Using ultrasound, a bone could be non-invasively referenced, and so the problem is formulated as the need for dynamic registration. A method for correspondence establishment is presented, and the matching step is based on three least-squares algorithms: two that are typically used in registration methods such as ICP, and the third is a form of the Unscented Kalman filter that was adapted to work in this context. A simulation was developed in order to reliably evaluate and compare the dynamic registration methods

Control algorithms for large scale adaptive optics

In this dissertation, the problem of creating effective large scale Adaptive Optics (AO) systems control algorithms for the new generation of giant optical telescopes is addressed. The effectiveness of AO control algorithms is evaluated in several respects, such as computational complexity, compensation error rejection and robustness, i.e. reasonable insensitivity to the system imperfections. The results of this research are summarized as follows: 1. Robustness study of Sparse Minimum Variance Pseudo Open Loop Controller (POLC) for multi-conjugate adaptive optics (MCAO). The AO system model that accounts for various system errors has been developed and applied to check the stability and performance of the POLC algorithm, which is one of the most promising approaches for the future AO systems control. It has been shown through numerous simulations that, despite the initial assumption that the exact system knowledge is necessary for the POLC algorithm to work, it is highly robust against various system errors. 2. Predictive Kalman Filter (KF) and Minimum Variance (MV) control algorithms for MCAO. The limiting performance of the non-dynamic Minimum Variance and dynamic KF-based phase estimation algorithms for MCAO has been evaluated by doing Monte-Carlo simulations. The validity of simple near-Markov autoregressive phase dynamics model has been tested and its adequate ability to predict the turbulence phase has been demonstrated both for single- and multiconjugate AO. It has also been shown that there is no performance improvement gained from the use of the more complicated KF approach in comparison to the much simpler MV algorithm in the case of MCAO. 3. Sparse predictive Minimum Variance control algorithm for MCAO. The temporal prediction stage has been added to the non-dynamic MV control algorithm in such a way that no additional computational burden is introduced. It has been confirmed through simulations that the use of phase prediction makes it possible to significantly reduce the system sampling rate and thus overall computational complexity while both maintaining the system stable and effectively compensating for the measurement and control latencies.