Browsing by Author "Allerton, David J."

Now showing 1 - 6 of 6
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    The application of relative navigation to civil air traffic management
    (2000-08) Sangpetchsong, K; Allerton, David J.
    This thesis addresses navigation and guidance which will be required for air traffic management in Future Air Navigation Systems (FANS) and Free Flight. In particular, the thesis covers the issues of data fusion and integrity monitoring, to provide an adequate level of aircraft separation assurance, based on relative navigation (RELNAV). The evolution of air navigation systems is described. The principles of Kalman filtering and Joint Tactical Information Distribution System (JTIDS) RELNAV are covered. Sensor models of strapdown Inertial Navigation System (INS), Global Positioning System (GPS), and Automatic Dependent Surveillance-Broadcast (ADS-B) are developed in Matlab and integrated to form a hybrid navigation system. RELNAV algorithms for centralised and decentralised Kalman filtering are formulated, and their respective performances are analysed using Monte Carlo simulations for an airspace containing several aircraft. It is shown that RELNAV, based on the integration of INS and ADS-B, can enable aircraft to maintain safe separation independent of GPS, where it is assumed that an ADS-B datalink provides accurate time synchronisation. An alternative approach that integrates INS, GPS, and ADS-B is developed and analysed. It is shown that this approach is more applicable to civil aviation because it eliminates the needs to establish and manage several navigation communities simultaneously, in effect, exploiting GPS as the navigation controller. The source selection functions used for RELNAV are also developed, and the stability and performance of this technique is evaluated from simulation studies. A failure detection algorithm that monitors the residuals of a Kalman filter is derived and evaluated using Monte Carlo simulations of GPS failures. It is shown that this algorithm combines the use of likelihood functions and chi-squared tests, allowing both a false alarm rate to be selected and a failed sensor to be identified. Finally, an algorithm is developed for separation assurance to determine the probability that aircraft are closer than a pre-determined distance, taking into account flight path prediction errors. It is shown that this algorithm simplifies aircraft conflict detection in three dimensions and allows the conflict probability at a particular time to be determined. This approach is validated using Monte Carlo simulations of aircraft trajectories which include near-misses.
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    Assessment of the autonomous air traffic control resolution tool for free flight
    (Cranfield University, 2004-07) Juman, M. A.; Allerton, David J.
    In order to improve air traffic coordination and planning, future ATMs need to allow various users of a particular airspace, timely access to the same data. Already, advances in technology, in the form of enhanced tools assisting airspace controllers and users, have enabled the sharing of high fidelity data across systems and improving standards in air traffic safety and throughput. To-date most of these tools are human- centered. The thesis presents a set of human-centered tools which use a common data structure for: detecting and resolving air traffic congestion, conflict detection and resolution and limiting the search space, in a ‘free-flight environment’. The chosen data-structure represents sets of discretized and indexed volumes of airspace, called ‘bins’, which store all the information necessary for operation in different airspace sectors. An algorithm using these bins has been proposed in the thesis. A large number of experiments carried out on a single purpose simulator, developed as a part of the thesis, have resulted in a set of optimized conflict free routes, which amply illustrate both medium and short-term detection of congestion and conflicts and provide solutions for their avoidance, across a large airspace volume that contains several airspace sectors, efficiently. In addition, a limited set of experiments, carried out with qualified ATCs in the loop, highlights the fact that the proposed ATM tool does assist them in better visualizing traffic flow and encounter geometry(ies).
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    Data fusion methodologies for multisensor aircraft navigation systems
    (Cranfield University, 2004-04) Jia, Huamin; Allerton, David J.
    The thesis covers data fusion for aircraft navigation systems in distributed sensor systems. Data fusion methodologies are developed for the design, development, analysis and simulation of multisensor aircraft navigation systems. The problems of sensor failure detection and isolation (FDI), distributed data fusion algorithms and inertial state integrity monitoring in inertial network systems are studied. Various existing integrated navigation systems and Kalman filter architectures are reviewed and a new generalised multisensor data fusion model is presented for the design and development of multisensor navigation systems. Normalised navigation algorithms are described for data fusion filter design of inertial network systems. A normalised measurement model of skewed redundant inertial measurement units (SRIMU) is presented and performance criteria are developed to evaluate optimal configurations of SRIMUs in terms of the measurement accuracy and FDI capability. Novel sensor error compensation filters are designed for the correction of SRIMU measurement errors. Generalised likelihood ratio test (GLRT) methods are improved to detect various failure modes, including short time and sequential moving-window GLRT algorithms. State-identical and state-associated fusion algorithms are developed for two forms of distributed sensor network systems. In particular, innovative inertial network sensing models and inertial network fusion algorithms are developed to provide estimates of inertial vector states and similar node states. Fusion filter-based integrity monitoring algorithms are also presented to detect network sensor failures and to examine the consistency of node state estimates in the inertial network system. The FDI and data fusion algorithms developed in this thesis are tested and their performance is evaluated using a multisensor software simulation system developed during this study programme. The moving-window GLRT algorithms for optimal SRIMU configurations are shown to perform well and are also able to detect jump and drift failures in an inertial network system. It is concluded that the inertial network fusion algorithms could be used in a low-cost inertial network system and are capable of correctly estimating the inertial vector states and the node states.
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    Design of data structures for terrain reference navigation
    (Cranfield University, 1994-05) Gia, M. C.; Allerton, David J.
    This thesis describes the design of a data structure for use with Digitised Terrain Elevation Data (DTED) in Terrain Reference Navigation (TRN) systems. The data structure is based on a variant of quad-tree and oct-tree data structures to provide an efficient representation of terrain in terms of storage requirements and acccss operations. These data structure are applied to flight path planning operations in mission management applications. The algorithms developed for flight path planning have becri implemented in the C programming language for a standard PC. Current research in TRN systems is reviewed and attention is given to the use of hierarchical data structures to cope with the potentially large data base needed for DTED files. Data structure combining quad-trees and oct-trees are developed with an emphasis on data reduction using pointerless trees and the use of locational codes to provide straightforward mapping between quad-trees and oct-trees, in other words, between two-dimensional co-ordinates and three-dimensional co-ordinates. Analysis of these algorithms is described for two DTED files to illustrate storage improvements and to verify a set of database access operations. These data structures are applied to problems of flight path planning where the navigation space comprises objects above a specific altitude and this three-dimensional space is searched for a flight path which avoids the obstacles and satisfies specific operational criteria. Algorithms are developed to extract a visibility graph from the terrain database and to determine the preferred flight path from a set of paths which satisfy defined constraints. Several search techniques are developed which exploit the efficiency of the quad-tree and oct-tree data structures. These methods are extended to real-time flight-path planning where predicted times for access operations are used to direct flight path extraction by varying the tree resolution during computation of the flight path. A comprehensive set of results are provided to illustrate: the storage efficiency of quad-tree and oct-tree data structures the application of pyramid structures to represent navigation space analysis of the time to compute the visibility graph and to extract flight paths integration of these methods with a real-time mission management simulation on a PC The thesis draws conclusions on the efficiency of these techniques for the represcntation of DTEDs and to access objects in TRN systems. It is observed that the use of hierarchical data structures in the form of quad-trees and oct-trees offers significant improvement in accessing DTEDS, for future use in TRN systems. The thesis concludes by outlining areas of further work where the techniques can be further &N, cloped for applications in mission management and navigation using DTED files.
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    Distributed data fusion algorithms for inertial network systems
    (Institution of Engineering and Technology, 2008-01-01T00:00:00Z) Allerton, David J.; Jia, Huamin
    New approaches to the development of data fusion algorithms for inertial network systems are described. The aim of this development is to increase the accuracy of estimates of inertial state vectors in all the network nodes, including the navigation states, and also to improve the fault tolerance of inertial network systems. An analysis of distributed inertial sensing models is presented and new distributed data fusion algorithms are developed for inertial network systems. The distributed data fusion algorithm comprises two steps: inertial measurement fusion and state fusion. The inertial measurement fusion allows each node to assimilate all the inertial measurements from an inertial network system, which can improve the performance of inertial sensor failure detection and isolation algorithms by providing more information. The state fusion further increases the accuracy and enhances the integrity of the local inertial states and navigation state estimates. The simulation results show that the two-step fusion procedure overcomes the disadvantages of traditional inertial sensor alignment procedures. The slave inertial nodes can be accurately aligned to the master node.
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    Redundant Multi-Mode Filter for a Navigation System
    (IEEE Institute of Electrical and Electronics, 2007-01-01T00:00:00Z) Allerton, David J.; Jia, Huamin
    An approach is introduced to the design of a multi-mode navigation filter to combine a low-cost skewed redundant inertial measurement unit (SRIMU) with a multifunctional GPS (MF-GPS) receiver in order to implement a fault-tolerant aircraft navigation system, which can achieve the required navigation performance of conventional systems in terms of accuracy, integrity, continuity, and availability. The MF-GPS receiver provides raw GPS measurements for pseudo- range and range rate to compute the navigation solutions (position and velocity) and also multi-antenna carrier phase interferometric measurements to estimate the aircraft attitude solution, if the carrier phase data is reliable. A multi- mode navigation filter is designed which combines state and measurement fusion methods and processes the SRIMU and raw MF-GPS outputs to provide reliable position, velocity and attitude information, and also kinematic parameters required in control, guidance, and navigation applications. The feasibility and performance of this integrated design is assessed and evaluated by using simulation. The accuracy of inertial gyros used in the evaluation ranges from 1 ± /h to 30 ± /h, including low-cost inertial sensor technologies. The simulation studies presented here show that a multi-mode navigation filter can achieve sufficient reliability and accuracy and that SRIMU/MF-GPS integrated navigation systems may provide a cost-effective system for future regional aircraft, general aviation aircraft, and unmanned aerial vehicle