685 research outputs found
Digital demodulation with data subcarrier tracking
Digital demodulation with data subcarrier trackin
Inertial navigation aided by simultaneous loacalization and mapping
Unmanned aerial vehicles technologies are getting smaller and cheaper
to use and the challenges of payload limitation in unmanned aerial
vehicles are being overcome. Integrated navigation system design requires
selection of set of sensors and computation power that provides
reliable and accurate navigation parameters (position, velocity
and attitude) with high update rates and bandwidth in small and
cost effective manner. Many of today’s operational unmanned aerial
vehicles navigation systems rely on inertial sensors as a primary measurement
source. Inertial Navigation alone however suffers from slow
divergence with time. This divergence is often compensated for by
employing some additional source of navigation information external
to Inertial Navigation. From the 1990’s to the present day Global
Positioning System has been the dominant navigation aid for Inertial
Navigation. In a number of scenarios, Global Positioning System measurements
may be completely unavailable or they simply may not be
precise (or reliable) enough to be used to adequately update the Inertial
Navigation hence alternative methods have seen great attention.
Aiding Inertial Navigation with vision sensors has been the favoured
solution over the past several years. Inertial and vision sensors with
their complementary characteristics have the potential to answer the
requirements for reliable and accurate navigation parameters.
In this thesis we address Inertial Navigation position divergence. The
information for updating the position comes from combination of vision
and motion. When using such a combination many of the difficulties
of the vision sensors (relative depth, geometry and size of objects,
image blur and etc.) can be circumvented. Motion grants the vision
sensors with many cues that can help better to acquire information
about the environment, for instance creating a precise map of the environment
and localize within the environment.
We propose changes to the Simultaneous Localization and Mapping
augmented state vector in order to take repeated measurements of
the map point. We show that these repeated measurements with certain
manoeuvres (motion) around or by the map point are crucial for
constraining the Inertial Navigation position divergence (bounded estimation
error) while manoeuvring in vicinity of the map point. This
eliminates some of the uncertainty of the map point estimates i.e.
it reduces the covariance of the map points estimates. This concept
brings different parameterization (feature initialisation) of the map
points in Simultaneous Localization and Mapping and we refer to it
as concept of aiding Inertial Navigation by Simultaneous Localization
and Mapping.
We show that making such an integrated navigation system requires
coordination with the guidance and control measurements and the vehicle
task itself for performing the required vehicle manoeuvres (motion)
and achieving better navigation accuracy. This fact brings new
challenges to the practical design of these modern jam proof Global
Positioning System free autonomous navigation systems.
Further to the concept of aiding Inertial Navigation by Simultaneous
Localization and Mapping we have investigated how a bearing only
sensor such as single camera can be used for aiding Inertial Navigation.
The results of the concept of Inertial Navigation aided by
Simultaneous Localization and Mapping were used. New parameterization
of the map point in Bearing Only Simultaneous Localization
and Mapping is proposed. Because of the number of significant problems
that appear when implementing the Extended Kalman Filter in
Inertial Navigation aided by Bearing Only Simultaneous Localization
and Mapping other algorithms such as Iterated Extended Kalman Filter,
Unscented Kalman Filter and Particle Filters were implemented.
From the results obtained, the conclusion can be drawn that the nonlinear
filters should be the choice of estimators for this application
Applications of real number theorem proving in PVS
This work is supported by funding from the EPSRC under grants EP/H500162, EP/F02309X and GR/S31242Real number theorem proving has many uses, particularly for verification of safety critical systems and systems for which design errors may be costly. We discuss a chain of developments building on real number theorem proving in PVS. This leads from the verification of aspects of an air traffic control system, through work on the integration of computer algebra and automated theorem proving to a new tool, NRV, first presented here that builds on the capabilities of Maple and PVS to provide a verified and automatic analysis of Nichols plots. This automates a standard technique used by control engineers and greatly improves assurance compared with the traditional method of visual inspection of the Nichols plots.Publisher PDFPeer reviewe
YF-12 cooperative airframe/propulsion control system program, volume 1
Several YF-12C airplane analog control systems were converted to a digital system. Included were the air data computer, autopilot, inlet control system, and autothrottle systems. This conversion was performed to allow assessment of digital technology applications to supersonic cruise aircraft. The digital system was composed of a digital computer and specialized interface unit. A large scale mathematical simulation of the airplane was used for integration testing and software checkout
Investigation of application of two-degree-of-freedom dry tuned-gimbal gyroscopes to strapdown navigation systems
The work is described which was accomplished during the investigation of the application of dry-tuned gimbal gyroscopes to strapdown navigation systems. A conventional strapdown configuration, employing analog electronics in conjunction with digital attitude and navigation computation, was examined using various levels of redundancy and both orthogonal and nonorthogonal sensor orientations. It is concluded that the cost and reliability performance constraints which had been established could not be met simultaneously with such a system. This conclusion led to the examination of an alternative system configuration which utilizes an essentially new strapdown system concept. This system employs all-digital signal processing in conjunction with the newly-developed large scale integration (LSI) electronic packaging techniques and a new two-degree-of-freedom dry tuned-gimbal instrument which is capable of providing both angular rate and acceleration information. Such a system is capable of exceeding the established performance goals
Preliminary Candidate Advanced Avionics System (PCAAS)
Specifications which define the system functional requirements, the subsystem and interface needs, and other requirements such as maintainability, modularity, and reliability are summarized. A design definition of all required avionics functions and a system risk analysis are presented
Shuttle Ku-band signal design study
Carrier synchronization and data demodulation of Unbalanced Quadriphase Shift Keyed (UQPSK) Shuttle communications' signals by optimum and suboptimum methods are discussed. The problem of analyzing carrier reconstruction techniques for unbalanced QPSK signal formats is addressed. An evaluation of the demodulation approach of the Ku-Band Shuttle return link for UQPSK when the I-Q channel power ratio is large is carried out. The effects that Shuttle rocket motor plumes have on the RF communications are determined also. The effect of data asymmetry on bit error probability is discussed
Low-cost MEMS-INS/GPS integration using nonlinear filtering approaches
Some important key issues in GNSS/INS integration mainly arise in the field of creating and developing low-cost, robust and at the same time highly accurate navigation systems, putting a focus of interest onto powerful sensor fusion algorithms. The so-called tightly-coupled integration is one of the most promising approaches to fuse the GNSS (global navigation satellite systems) data with INS (inertial navigation system) measurements. However, when modeling the underlying problem, the system process and observation models turn out to be nonlinear, and the GNSS stochastic measurement errors are often non-Gaussian distributed (e.g., due to multipath effects). Among other estimation approaches, the so-called particle filter (PF) as a nonlinear/non-Gaussian estimation method is especially theoretically attractive to be used in this field. However, its large computational burden usually limits its practical usage. In order to reduce the computational burden without degrading the system estimation accuracy, recently, an unscented particle filter (UPF) has been proposed, which combines the PF with the unscented Kalman filter (UKF). In this thesis, only one UKF is used in the algorithm, and the re-sampling step is not required anymore. Thus, the number of particles can be largely reduced, and the implementation of the PF on a hardware platform turns out to be feasible.Aktuelle Entwicklungen auf dem Gebiet der Fusion von inertialer Navigation und satellitengestützten Positionierungsverfahren zielen klar auf kosteneffiziente, robuste und gleichzeitig hochpräzise Lösungen ab. Leistungsfähige Sensordatenfusionsansätze spielen hier eine Schlüsselrolle, wobei die sogenannte "Tightly Coupled Integration" zur Fusion der satellitengestützten Navigationsdaten mit den Messdaten eines inertialen Systems besonders vielversprechend erscheint. Als erschwerender Umstand ergeben sich hier allerdings nichtlineare Prozess- und Beobachtungsmodelle, die in Verbindung mit nicht länger gaußverteilten Beobachtungsfehlern, beispielsweise aufgrund von Mehrwegeausbreitung, nichtlineare, möglichst optimale Datenfusionsverfahren, wie beispielsweise Partikelfilter-Ansätze erfordern. Theoretisch elegant und leistungsfähig auf der einen Seite, benötigen diese Ansätze in der praktischen Realisierung vielfach eine ungemein hohe Anzahl von einzelnen "Partikeln", so dass der hierdurch verursachte Berechnungsaufwand die praktische Einsatzfähigkeit unter Echtzeitbedingungen vielfach entweder im Hinblick auf die Filterperformance oder auf die Taktzeit limitiert. Ein Ansatz zur Lösung dieser Problematik besteht in der Kombination eines Partikelfilters mit einem Unscented Kalman Filter. Hierbei wird der sonst bei Partikelfiltern übliche, aber zeitaufwändige, Resampling Schritt nicht mehr benötigt. Auch die Anzahl der benötigten Partikel kann stark reduziert werden, so dass eine Realisierung auf einer Signalprozessorplattform möglich wird
Solutions and algorithms for inertial navigation of railroad vehicles
Obiettivo di questa tesi è lo studio e lo sviluppo di soluzioni innovative di navigazione inerziale per applicazioni ferroviarie, strumento utile per il tracciamento del moto durante l'assenza prolungata di sistemi di localizzazione esterni, tipo GPS, come può avvenire in galleria. Definiti gli strumenti di lavoro, è stata poi eseguita un'analisi dello stato dell'arte al fine di mettere in evidenza le metodologie teoriche utilizzate, nonchè le prestazioni dei sistemi già esistenti. Sono poi caratterizzati i sensori e le misure disponibili.
Sono proposte varie soluzioni al problema della navigazione inerziale, con l'obiettivo di valutarne le prestazioni durante periodi prolungati assenza del GPS e con varie condizioni al contorno. Dopo una prima versione basata su un singolo EKF, si è scelto di svilupparne una seconda classe in cui il problema di stimadi assetto (AHRS) e diposizione/velocità sono separati e risolti mediante due algoritmi distinti. È stato implementato un AHRS basato su EKF e uno mediante un osservatore non lineare; inoltre, sono stati sviluppati un EKF di ordine completo e uno ridotto per le dinamiche di traslazione. È stata poi sviluppata una soluzione per l'integrazione dei dati delle mappe, in modo da fornire correzioni più frequenti all'INS, mantenendo inoltre un ridotto carico computazionale e facilità di integrazione.
Si è infine proceduto implementando e simulando la soluzione a singolo stadio e le varie combinazioni di INS a due stadi in ambiente Matlab-Simulink. Gli algoritmi a due stadi hanno mostrato in simulazione prestazioni migliori rispetto alla struttura a EKF singolo la quale presenta un dominio di convergenza troppo limitato per fini pratici.
A conclusione del lavoro, svolto avvalendosi della collaborazione di Sadel, sono state gettate le basi per una successiva analisi atta a verificare se la struttura a due stadi consente la convergenza anche dei bias di accelerometr
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