Eine Voraussetzung um einen Flugregler für Flugroboter zu realisieren, ist die Wahrnehmung der Bewegungen dieses Roboters. Diese Arbeit beschreibt einen Ansatz zur Schätzung der Bewegung eines autonomen Flugroboters unter Verwendung relativ einfacher, leichter und kostengünstiger Sensoren. Mittels eines Erweiterten Kalman Filters werden Beschleunigungssensoren, Gyroskope, ein Ultraschallsensor, sowie ein Sensor zu Messung des optischen Flusses zu einer robusten Bewegungsschätzung kombiniert. Dabei wurden die einzelnen Sensoren hinsichtlich der Eigenschaften experimentell untersucht, welche für die anschließende Erstellung des Filters relevant sind. Am Ende werden die Resultate des Filters mit den Ergebnissen einer Simulation und eines externen Tracking-Systems verglichen.

Die Sensordatenfusion ist eine allgegenwärtige Aufgabe im Bereich der mobilen Robotik und darüber hinaus. In der vorliegenden Arbeit wird das typischerweise verwendete Verfahren zur Sensordatenfusion in der Robotik in Frage gestellt und anhand von neuartigen Algorithmen, basierend auf einem Faktorgraphen, gelöst sowie mit einer korrespondierenden Extended-Kalman-Filter-Implementierung verglichen. Im Mittelpunkt steht dabei das technische sowie algorithmische Sensorkonzept für die Navigation eines Flugroboters im Innenbereich. Ausführliche Experimente zeigen die Qualitätssteigerung unter Verwendung der neuen Variante der Sensordatenfusion, aber auch Einschränkungen und Beispiele mit nahezu identischen Ergebnissen beider Varianten der Sensordatenfusion. Neben Experimenten anhand einer hardwarenahen Simulation wird die Funktionsweise auch anhand von realen Hardwaredaten evaluiert.

Eine Voraussetzung um einen Flugregler für Flugroboter zu realisieren, ist die Wahrnehmung der Bewegungen dieses Roboters. Diese Arbeit beschreibt einen Ansatz zur Schätzung der Bewegung eines autonomen Flugroboters unter Verwendung relativ einfacher, leichter und kostengünstiger Sensoren. Mittels eines Erweiterten Kalman Filters werden Beschleunigungssensoren, Gyroskope, ein Ultraschallsensor, sowie ein Sensor zu Messung des optischen Flusses zu einer robusten Bewegungsschätzung kombiniert. Dabei wurden die einzelnen Sensoren hinsichtlich der Eigenschaften experimentell untersucht, welche für die anschließende Erstellung des Filters relevant sind. Am Ende werden die Resultate des Filters mit den Ergebnissen einer Simulation und eines externen Tracking-Systems verglichen.

In this dissertation a novel alternative system concept for monocular-inertial egomotion and landmark position determination is introduced. It is mainly motivated by an in-depth analysis of the observability and consistency of the classic simultaneous localization and mapping (SLAM) approach, which is based on a world-centric model of an agent and its environment. Within the novel system concept - a body-centric agent and environment model, - a pseudo-world centric motion propagation, - and closed-form initialization procedures are introduced. This approach allows for combining the advantageous observability properties of body-centric modeling and the advantageous motion propagation properties of world-centric modeling. A consistency focused and simulation based evaluation demonstrates the capabilities as well as the limitations of the proposed concept. / In dieser Dissertation wird ein neuartiges, alternatives Systemkonzept für die monokular-inertiale Eigenbewegungs- und Landmarkenpositionserfassung vorgestellt. Dieses Systemkonzept ist maßgeblich motiviert durch eine detaillierte Analyse der Beobachtbarkeits- und Konsistenzeigenschaften des klassischen Simultaneous Localization and Mapping (SLAM), welches auf einer weltzentrischen Modellierung eines Agenten und seiner Umgebung basiert. Innerhalb des neuen Systemkonzeptes werden - eine körperzentrische Modellierung des Agenten und seiner Umgebung, - eine pseudo-weltzentrische Bewegungspropagation, - und geschlossene Initialisierungsprozeduren eingeführt. Dieser Ansatz erlaubt es, die günstigen Beobachtbarkeitseigenschaften körperzentrischer Modellierung und die günstigen Propagationseigenschaften weltzentrischer Modellierung zu kombinieren. Sowohl die Fähigkeiten als auch die Limitierungen dieses Ansatzes werden abschließend mit Hilfe von Simulationen und einem starken Fokus auf Schätzkonsistenz demonstriert.

Die Sensordatenfusion ist eine allgegenwärtige Aufgabe im Bereich der mobilen Robotik und darüber hinaus. In der vorliegenden Arbeit wird das typischerweise verwendete Verfahren zur Sensordatenfusion in der Robotik in Frage gestellt und anhand von neuartigen Algorithmen, basierend auf einem Faktorgraphen, gelöst sowie mit einer korrespondierenden Extended-Kalman-Filter-Implementierung verglichen. Im Mittelpunkt steht dabei das technische sowie algorithmische Sensorkonzept für die Navigation eines Flugroboters im Innenbereich. Ausführliche Experimente zeigen die Qualitätssteigerung unter Verwendung der neuen Variante der Sensordatenfusion, aber auch Einschränkungen und Beispiele mit nahezu identischen Ergebnissen beider Varianten der Sensordatenfusion. Neben Experimenten anhand einer hardwarenahen Simulation wird die Funktionsweise auch anhand von realen Hardwaredaten evaluiert.

Cada vez mais robôs móveis autônomos estão sendo utilizados em diversas tarefas e em ambientes com elevado risco para atividades humanas que a paralisação de suas atividades podem gerar outros riscos, perdas e elevados custos. Assim, o estado de carga (SOC) de sistemas de baterias em robôs móveis autônomos é um parâmetro importante na prevenção de uma falha primária nessa aplicação, a ausência de energia. Este trabalho apresenta os métodos existentes na literatura para a determinação do estado de carga de baterias e as tecnologias de baterias disponíveis utilizadas em robôs móveis autônomos ou veículos autônomos guiados. A partir desses estudos foi desenvolvido um modelo de medida, baseado no modelo combinado e foram realizados testes de bancadas para levantamento dos parâmetros e características de três modelos de células de baterias: Lítio Polímero (Li-PO), Níquel-Cádmio (NiCd) e Lítio-Ferro-Polímero (LiFePO4). Com esses parâmetros, aplicou-se o método de estimativa de carga baseado na técnica do Filtro de Kalman Estendido (EKF). Através dos testes, analisou-se comparativamente a resposta do método proposto e a resposta do método OCV e a capacidade de carga real. / Autonomous mobile robots have being increasingly used in various tasks, environments and activities of high risk to human that the stoppage of its activities may generate other risks, losses and high costs. Thus the state of charge (SOC) of battery systems in autonomous mobile robots, is an important parameter to prevent a primary failure in this application, the lack of energy. The paper presents the existing methods in the literature to determine the battery state of charge and battery commercial technologies available used in an autonomous mobile robot or autonomous guided vehicle, from these studies a measurement model based on combined model was developed and testing benches for three cells models on Lithium Polymer Battery (Li-PO), Nickel Cadmium (NiCd) and lithium-iron-Polymer (LiFePO4) batteries were performed for lifting the parameters and apply the battery state of charge method based on the Extended Kalman Filter (EKF) technique. The tests were analyzed in order to observe the comparatively response of the proposed method, the OCV method and Real charge capacity.

La mise en place d’un nouveau canal d’alimentation électrique incorporant un générateur à aimants permanents PMG (Permanent Magnet Generator) en remplacement de l’actuel canal de génération hydraulique est l’un des sujets de recherche en cours dans le secteur aéronautique. Le choix de cette solution est motivé par de nombreux avantages : réduction de masse, meilleure disponibilité du réseau hydraulique et maintenance plus aisée. Cependant, l’utilisation d’un PMG en tant que générateur électrique au sein d’un avion implique de nouvelles problématiques, notamment en ce qui concerne la sûreté de fonctionnement lors de défaillances internes au PMG. En effet, tant que le rotor est en rotation, la présence d’une excitation permanente due aux aimants entretient la présence du défaut même si le stator n’est plus alimenté, ce qui complexifie la mise en sécurité du PMG. Il est ainsi nécessaire de connaître précisément l’état de santé du PMG afin d’assurer une bonne continuité de service en évitant d’ordonner la mise en sécurité du PMG sur des défaillances externes au générateur. C’est pourquoi les travaux de cette thèse portent sur la détection des courts-circuits inter-spires dans les PMG, ces défauts ayant été identifiés comme les plus critiques pour ce type de machine. Compte tenu du contexte aéronautique, il a été choisi de travailler sur les méthodes de détection basées sur l’estimation de paramètres via un modèle mathématique de la machine en utilisant le Filtre de Kalman Etendu (FKE). En effet, s’il est correctement paramétré, le FKE permet d’obtenir une bonne dynamique de détection et s’avère être très robuste aux variations du réseau électrique (vitesse, déséquilibre, …), critère important pour garantir un canal de génération fiable. Deux types de modèle mathématique sont présentés pour la construction d’un indicateur de défaut utilisant les estimations fournies par le FKE. Le premier est basé sur une représentation saine du PMG où l’indicateur de défaut est construit à partir de l’estimation de certains paramètres de la machine (résistance, inductance, constante de fem ou pulsation électrique). Le second modèle utilise une formulation d’un PMG défaillant qui permet d’estimer le pourcentage de spires en court-circuit. Après avoir comparé et validé expérimentalement le comportement des différents indicateurs sur un banc de test à puissance réduite, la mise en place d’un indicateur de court-circuit inter-spires au sein d’un réseau électrique aéronautique et son interaction avec les protections existantes sur avion sont étudiées dans la dernière partie de ce mémoire. / The establishment of an electrical power supply channel including a Permanent Magnet Generator (PMG) to replace an hydraulic power channel is one of the current topics of research in the aeronautic field. This choice is motivated by several benefits : weight reduction, improvement of the hydraulic network avaibility and easier maintenance. However, the use of PMG as an electrical generator in an aircraft implies new issues, particularly as regards safety considerations when an internal fault occurs in the PMG. Indeed, as long as the rotor in rotating, the presence of the persistent excitation due to the magnets maintains the internal fault even if the stator is de-energized. This makes the safety procedure of PMG more complex. Therefore, it is necessary to precisely know the behavior of the PMG (healthy or faulty) to ensure the avaibility of this power supply channel in order to avoid triggering PMG safety procedure when an external fault occurs. Thus, this work deals with the on-line detection of inter-turn short-circuits in PMG, these faults have been identified as the most critical for this kind of machine Given the aeronautic context, it has been decided to work on detection methods based on parameter estimation via a mathematical model of the machine using the Extended Kalman Filter (EKF). Indeed, with an appropriate setting, the EKF provides a fast dynamic detection and can be very robust to variations in the electrical network (speed, unbalanced, ...) which is an important characteristic to ensure a reliable generation channel. Two types of mathematical model are presented for fault indicator construction using the estimations provided by the EKF. The first one is based on an healthy representation of the PMG where the fault indicator is built from the estimation of PMG electrical parameters (resistance, inductance, electromotive force constant or electrical rotational velocity). The second model uses a faulty PMG formulation to estimate the ratio of short-circuited turns. After the comparison and the experimental validation of the fault indicators behavior on a test bench at reduced power, the establishment of a inter-turn short-circuit indicator within an aircraft electrical system and its interaction with existing protections are studied in the last part of this thesis.

Advanced computational tools are applied to simulate a nuclear power plant (NPP) control rod assembly ejection (CRE) accident. The impact of these reactivity-initiated accidents (RIAs) on core reactivity behavior, 3D power distribution and stochastic reactivity estimation are evaluated. The three tools used are: the thermal-hydraulic (TH) RELAP5 (R5) code, the neutronic (NK) PARCS (P3D) code, and the coupled version P3D/R5, with specially developed linkage using the environment code MATLAB. This study considers three different-size cores: NPP1 (2772 MWt); NPP2 (530 MWt); and NPP3 (1061 MWt). The three cores have the same general design and control rod assembly (CRA) positions, and the ejected CRA has similar worth and at the same rod ejection pace. The CRE is assessed under both hot zero power (HZP) and hot full power (HFP) conditions. The analyses indicate that RIA modeling and simulation should be carried out through a systematic coding and configuration approaches, otherwise the results will not capture the true transient behavior of the core under analysis. The simulation of one code depends on the appropriate configuration of parameters generated by the other code and on the correct determination of the TH/NK mapping weight factors for the various mesh regions in each of the models. From the design point of view, the standalone codes predict milder magnitude of power and reactivity increase compared to the coupled P3D/R5 simulation. The magnitudes of reduced peak power and reactivity become larger as the core size shrinks. The HFP simulation shows that the three NPPs have the same transient peak value, but the post-transient steady power is lower for a smaller core. The HZP analysis indicates that the transient peak is lower for the smaller core, but the post-transient power occurs at the same level. The three-dimensional (3D) power distributions are different among the HFP and HZP cases, but do not depend on the size of the core. The results indicate: i) HFP: core power increases in the area surrounding the ejected rod/bank assembly, and this increase becomes lower as the NPPs shrinks however, the power is well-distributed after the transient; and ii) HZP: the area surrounding the CRA stays hotter, but the 3D peak assembly factor becomes lower, during and after the transients, as the NPPs shrinks. These features confirm that the smaller cores yield a safer response to a given inserted reactivity compared to larger cores. A stochastic extended Kalman filter (EKF) algorithm is implemented to estimate the reactivity based on the reactor power profile, after the addition of random noise. The inverse point kinetics (IPK) deterministic method is also implemented and the results of the application of EKF and IPK are compared to the P3D/R5 simulation. The following sophisticated strategies made the EKF algorithm robust and accurate: the system is modeled by a set of continuous time nonlinear stochastic differential equations; the code uses a time step directly based on the power measured and applies that to the model for online discretization and linearization; filter tuning goes automatically up from the first time step; and the state noise covariance matrix is updated online at each time step. It was found that the IPK reactivity has higher noise content compared to the EKF reactivity for all cases. Thus, the EKF presents superior and more accurate results. Furthermore, under a small reactivity insertion, the IPK reactivity varies widely from positive to negative values: this variation is not observed within the EKF. A sensitivity analysis for three distinct standard deviation (SD) noise measurements suggests that EKF is superior to IPK method, independent of the noise load magnitude. As the noise content increases, the error between the IPK and P3D/R5 reactivity also increases. A sensitivity analysis for five distinct carry-over effects of different random noise loads indicates that the random addition of different noise loads to the reactor power does not change the overall performance of both algorithms. / Este trabalho aplica métodos computacionais avançados para simular a ejeção de barras de controle (CRE) em uma planta térmica nuclear (NPP). São avaliados o impacto da ocorrência de acidentes iniciados por reatividade (RIAs) na reatividade total, na distribuição da potência em três dimensões (3D) e na determinação da reatividade. As ferramentas utilizadas são: o código termo-hidráulico (TH) RELAP5 (R5), o código neutrônico (NK) PARCS (P3D), a versão acoplada P3D/R5, e o ambiente computacional MATLAB. Este estudo considera três reatores nucleares de diferentes tamanhos: NPP1 (2772 MWT); NPP2 (530 MWt); e NPP3 (1061 MWt). Os três núcleos possuem projeto similar e idêntica posição dos grupos das barras de controle (CRA), além do mesmo valor de reatividade diferencial das CRA ejetadas e idêntica velocidade de ejeção. A ocorrência da CRE é avaliada sob condições de hot zero power (HZP) e de hot full power (HFP). As análises indicam que a modelagem e a simulação de RIAs devem ser realizadas sistematicamente, caso contrário os resultados não irão refletir o comportamento em regime transitório do núcleo. A simulação de um modelo em um código depende da apropriada configuração de parâmetros gerados pelo outro código e da determinação adequada do mapeamento TH/NK para as várias malhas dos modelos. Do ponto de vista de projeto, a utilização de códigos independentes resulta em cálculos de potência e reatividade conservadores em comparação com os resultados utilizando-se P3D/R5. Os picos de potência e de reatividade são menores à medida que o núcleo encolhe. A simulação em condições de HFP resulta em valores de pico de potência similares durante transitório para as três NPPs, mas a potência de pós-transitórios é menor para o menor núcleo. A análise em condições de HZP também indica que o valor máximo durante o transitório é menor para o menor núcleo, mas o pós-transitórios ocorre aos mesmos níveis de potência das demais NPPS. A distribuição de potência em 3D também apresenta resultados distintos para condições de HFP e HZP, mas tais resultados são independentes do tamanho do núcleo: i) HFP: há um aumento da potência do núcleo em torno da CRE, mas tal comportamento diminui para núcleos menores - no entanto, a potência é bem distribuída após o transitório; e ii) HZP: há aumento de potência na área do CRE, mas o pico de potência em 3D é menor durante e depois dos transitórios para núcleos menores. Tais características indicam que os núcleos menores respondem de forma mais segura quando da inserção de reatividade em comparação a reatores de maiores dimensões. O método estocástico de filtragem de Kalman estendido (EKF) foi codificado para estimar a reatividade com base no perfil de potência da NPP, após a adição de ruído aleatório. O método determinístico da cinética pontual inversa (IPK) também foi implementado e os resultados da aplicação dos algoritmos do EKF e IPK foram comparados com os resultados da simulação do P3D/R5. As seguintes estratégias, implementadas neste trabalho, possibilitaram a aplicação robusta e precisa do EKF: o sistema foi modelado por um conjunto de equações diferenciais não-lineares estocásticas de tempo contínuo; o algoritmo obtém o passo de tempo diretamente da potência medida e aplica-o ao modelo para a discretização e linearização online; o ajuste do filtro ocorre automaticamente a partir do primeiro passo de tempo; e a matriz de covariância do ruído no estado é atualizada online. Verificou-se que a reatividade calculada pelo método IPK possui maior nível de ruído quando comparada ao EKF para todos os casos estudados. Portanto, o EKF apresenta resultados superiores e mais precisos. Além disso, sob uma pequena inserção de reatividade, a reatividade calculada pelo método IPK varia consideravelmente de valores positivos para negativos: esta variação não é observada com o EKF. Uma análise de sensibilidade para três desvios padrão (SD) sugere que o algoritmo EKF é superior ao método IPK, independente da magnitude do ruído. Com o aumento da magnitude do ruído, o erro entre as reatividades calculadas pelo IPK e pelo P3D/R5 aumenta. A análise de sensibilidade para cinco ruídos aleatórios indica que a adição de ruído na potência do reator não altera o desempenho global de ambos os algoritmos.

Autonomous navigation is the determination of satellites position and velocity vectors onboard the satellite, using the measurements available onboard. The orbital information of a satellite needs to be obtained to support different house keeping operations such as routine tracking for health monitoring, payload data processing and annotation, orbit manoeuver planning, and prediction of intrusion in various sensors' field of view by celestial bodies like Sun, Moon etc. Determination of the satellites orbital parameters is done in a number of ways using a variety of measurements. These measurements may originate from ground based systems as range and range rate measurements, or from another satellite as in the case of GPS (Global Positioning System) and TDUSS (Tracking Data Relay Satellite Systems), or from the same satellite by using sensors like horizon sensor^ sun sensor, star tracker, landmark tracker etc. Depending upon the measurement errors, sampling rates, and adequacy of the estimation scheme, the navigation accuracy can be anywhere in the range of 10m - 10 kms in absolute location. A wide variety of tracking sensors have been proposed in the literature for autonomous navigation. They are broadly classified as (1) Satellite-satellite tracking, (2) Ground- satellite tracking, (3) fully autonomous tracking. Of the various navigation sensors, it may be cost effective to use existing onboard sensors which are well proven in space. Hence, in the current thesis, the Horizon scanner is employed as the primary navigation sensor-. It has been shown in the literature that by using horizon sensors and gyros, a high accuracy pointing of the order of .01 - .03 deg can be achieved in the case of low earth orbits. Motivated by such a fact, the current thesis deals with autonomous orbit determination using measurements from the horizon sensors with the assumption that the attitude is known to the above quoted accuracies. The horizon scanners are mounted on either side of the yaw axis in the pitch yaw plane at an angle of 70 deg with respect to the yaw axis. The Field Of View (FOV) moves about the scanner axis on a cone of 45 deg half cone angle. During each scan, the FOV generates two horizon points, one at the space-Earth entry and the other at the Earth-space exit. The horizon points, therefore, lie• on the edge of the Earth disc seen by the satellite. For a spherical earth, a minimum of three such horizon points are needed to estimate the angular radius and the center of the circular horizon disc. Since a total of four horizon points are available from a pair of scanners, they can be used to extract the satellite-earth distance and direction.These horizon points are corrupted by noise due to uncertainties in the Earth's radiation pattern, detector mechanism, the truncation and roundoff errors due to digitisation of the measurements. Owing to the finite spin rate of the scanning mechanism, the measurements are available at discrete time intervals. Thus a filtering algorithm with appropriate state dynamics becomes essential to handle the •noise in the measurements, to obtain the best estimate and to propagate the state between the measurements. The orbit of a low earth satellite can be represented by either a state vector (position and velocity vectors in inertial frame) or Keplerian elements. The choice depends upon the available processors, functions and the end use of the estimated orbit information. It is shown in the thesis that position and velocity vectors in inertial frame or the position vector in local reference frame, do result in a simplified, state representation. By using the f and g series method for inertial position and velocity, the state propagation is achieved in linear form. i.e. Xk+1 = AXK where X is the state (position, velocity) and A the state transition matrix derived from 'f' and 'g' series. The configuration of a 3 axis stabilised spacecraft with two horizon scanners is used to simulate the measurements. As a step towards establishing the feasibility of extracting the orbital parameters, the governing equations are formulated to compute the satellite-earth vector from the four horizon points generated by a pair of Horizon Scanners in the presence of measurement noise. Using these derived satellite-earth vectors as measurements, Kalman filter equations are developed, where both the state and measurements equations are linear. Based on simulations, it is shown that a position accuracy of about 2 kms can be achieved. Additionally, the effect of sudden disturbances like substantial slewing of the solar panels prior and after the payload operations are also analysed. It is shown that a relatively simple Low Pass Filter (LPF) in the measurements loop with a cut-off frequency of 10 Wo (Wo = orbital frequency) effectively suppresses the high frequency effects from sudden disturbances which otherwise camouflage the navigational information content of the signal. Then Kalman filter can continue to estimate the orbit with the same kind of accuracy as before without recourse to re-tuning of covariance matrices. Having established the feasibility of extracting the orbit information, the next step is to treat the measurements in its original form, namely, the non-linear form. The entry or exit timing pulses generated by the scanner when multiplied by the scan rate yield entry or exit azimuth angles in the scanner frame of reference, which in turn represents an effective measurement variable. These azimuth angles are obtained as inverse trigonometric functions of the satellite-earth vector. Thus the horizon scanner measurements are non-linear functions of the orbital state. The analytical equations for the horizon points as seen in the body frame are derived, first for a spherical earth case. To account for the oblate shape of the earth, a simple one step correction algorithm is developed to calculate the horizon points. The horizon points calculated from this simple algorithm matches well with the ones from accurate model within a bound of 5%. Since the horizon points (measurements) are non-linear functions of the state, an Extended Kalman Filter (EKF) is employed for state estimation. Through various simulation runs, it is observed that the along track state has got poor observability when the four horizon points are treated as measurements in their original form, as against the derived satellite-earth vector in the earlier strategy. This is also substantiated by means of condition number of the observability matrix. In order to examine this problem in detail, the observability of the three modes such as along-track, radial, and cross-track components (i.e. the local orbit frame of reference) are analysed. This difficulty in observability is obviated when an additional sensor is used in the roll-yaw plane. Subsequently the simulation studies are carried out with two scanners in pitch-yaw plane and one scanner in the roll-yaw plane (ie. a total of 6 horizon points at each time). Based on the simulations, it is shown that the achievable accuracy in absolute position is about 2 kms.- Since the scanner in the roll-yaw plane is susceptible to dazzling by Sun, the effect of data breaks due to sensor inhibition is also analysed. It is further established that such data breaks do not improve the accuracy of the estimates of the along-track component during the transient phase. However, filter does not diverge during this period. Following the analysis of the' filter performance, influence of Earth's oblateness on the measurement model studied. It is observed that the error in horizon points, due to spherical Earth approximation behave like a sinusoid of twice the orbital frequency alongwith a bias of about 0.21° in the case of a 900 kms sun synchronous orbit. The error in the 6 horizon points is shown to give rise to 6 sinusoids. Since the measurement model for a spherical earth is the simplest one, the feasibility of estimating these sinusoids along with the orbital state forms the next part of the thesis. Each sinusoid along with the bias is represented as a 3 state recursive equation in the following form where i refers to the ith sinusoid and T the sampling interval. The augmented or composite state variable X consists of bias, Sine and Cosine components of the sinusoids. The 6 sinusoids together with the three dimensional orbital position vector in local coordinate frame then lead to a 21 state augmented Kalman Filter. With the 21 state filter, observability problems are experienced. Hence the magnetic field strength, which is a function of radial distance as measured by an onboard magnetometer is proposed as additional measurement. Subsequently, on using 6 horizon point measurements and the radial distance measurements obtained from a magnetometer and taking advantage of relationships between sinusoids, it is shown that a ten state filter (ie. 3 local orbital states, one bias and 3 zero mean sinusoids) can effectively function as an onboard orbit filter. The filter performance is investigated for circular as well as low eccentricity orbits. The 10-state filter is shown to exhibit a lag while following the radial component in case of low eccentricity orbits. This deficiency is overcome by introducing two more states, namely the radial velocity and acceleration thus resulting in a 12-state filter. Simulation studies reveal that the 12-state filter performance is very good for low eccentricity orbits. The lag observed in 10-state filter is totally removed. Besides, the 12-state filter is able to follow the changes in orbit due to orbital manoeuvers which are part of orbit acquisition plans for any mission.

Die Fahrzeuglokalisierung ist im Bereich der Fahrerassistenzsysteme von entscheidender Bedeutung und Voraussetzung fur verschiedene Anwendungen der Robotik, wie z.B. Navigation oder Kollisionsvermeidung fur fahrerlose Transportsysteme (FTS). In dieser Arbeit wird ein Verfahren zur Lokalisierung mittels Landmarken vorgestellt, die eine Orientierung bezuglich einer Karte ermoglichen. Dabei werden der Erweiterte- Kalman-Filter und der Partikel-Filter fur diese Aufgabe untersucht und verglichen. Ein Schwerpunkt dieser Betrachtungen stellt dabei der Partikel-Filter dar. Die besondere Problematik der Initialisierung wird ausfuhrlich fur beide Filter dargestellt. Simulationen und Versuche zeigen, dass sich der Partikel-Filter fur eine robuste Lokalisierung der Fahrzeugposition verwenden lasst. Im Vergleich dazu kann der Erweiterte-Kalman-Filter nur im begrenzten Maße eingesetzt werden. / The localization of vehicles is of vital importance in the field of driver assistance systems and a requirement of different applications for robotics, i.e. navigation or collision avoidance for automatic guided vehicle systems. In this thesis an approach for localization by means of landmarks is introduced, which enables an orientation regarding a map. The extended Kalman filter and the particle filter are analyzed and compared. The main focus for this consideration is on the particle filter. The problematic for initialization is discussed in detail for both filters. Simulations and tests prove that the particle filter is suitable for robust localization of the vehicle position. Compared to this, the extended Kalman filter can only be used to a certain extend.