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Atmospheric Polarization And Solar Position As Kalman Updates To A Navigation Solution, Thomas J. Wheeler
Atmospheric Polarization And Solar Position As Kalman Updates To A Navigation Solution, Thomas J. Wheeler
Theses and Dissertations
Simulation and physical testing of a sensor that measures relative position of the Sun and polarization of light in the atmosphere as a navigational aid in a Kalman filter.
Pedestrian Navigation Using Artificial Neural Networks And Classical Filtering Techniques, David J. Ellis
Pedestrian Navigation Using Artificial Neural Networks And Classical Filtering Techniques, David J. Ellis
Theses and Dissertations
The objective of this thesis is to explore the improvements achieved through using classical filtering methods with Artificial Neural Network (ANN) for pedestrian navigation techniques. ANN have been improving dramatically in their ability to approximate various functions. These neural network solutions have been able to surpass many classical navigation techniques. However, research using ANN to solve problems appears to be solely focused on the ability of neural networks alone. The combination of ANN with classical filtering methods has the potential to bring beneficial aspects of both techniques to increase accuracy in many different applications. Pedestrian navigation is used as a …
Context Aware Routing Management Architecture For Airborne Networks, Joan A. Betances
Context Aware Routing Management Architecture For Airborne Networks, Joan A. Betances
Theses and Dissertations
This thesis advocates the use of Kalman filters in conjunction with network topology information derived from the Air Tasking Order (ATO) during the planning phase for military missions. This approach is the basis for an algorithm that implements network controls that optimize network performance for Mobile Ad hoc Networks (MANET). The trajectories of relevant nodes (airborne platforms) participating in the MANET can be forecasted by parsing key information contained in the ATO. This information is used to develop optimum network routes that can significantly improve MANET performance. Improved MANET performance in the battlefield enables decision makers to access information from …
Assessment Of The Effects Of Plasma Bubbles On Gaim-Gm, Kenneth R. Fenton
Assessment Of The Effects Of Plasma Bubbles On Gaim-Gm, Kenneth R. Fenton
Theses and Dissertations
Plasma bubbles are regions of depleted plasma density generated in the post-sunset equatorial region of the ionosphere. Bubbles significantly affect total electron count (TEC) and consequently alter communication and navigation capabilities. Here, the Global Assimilation of Ionospheric Measurements Gauss-Markov (GAIM-GM) model is studied in order to assess its capability to accurately model equatorial plasma bubbles. GAIM-GM uses the Ionospheric Forecast Model (IFM) as a background state modified through the application of a Kalman Filter to incorporate ionospheric observations such as Global Positioning System (GPS) total electron content (TEC) values. GPS TEC values representative of plasma bubble conditions are modeled and …
Closed-Loop Adaptive Optics Control In Strong Atmospheric Turbulence, Todd M. Venema
Closed-Loop Adaptive Optics Control In Strong Atmospheric Turbulence, Todd M. Venema
Theses and Dissertations
A self-referencing interferometer based closed-loop adaptive optics controller is developed which is designed to operate effectively under strong turbulence conditions. The aberrated optical field is modeled stochastically and then estimates of the state of the system are developed using a steady-state, fixed-gain Kalman filter. The phase of the optical field is considered the state of the system which is wrapped in a limited range of (-π, π]. This phase is unwrapped through the use of a least-squares reconstructor which has been modified to work effectively in the presence of branch points associated with strong turbulence. The conjugate of the optical …
Tightly Integrating Optical And Inertial Sensors For Navigation Using The Ukf, Sedat Ebcin
Tightly Integrating Optical And Inertial Sensors For Navigation Using The Ukf, Sedat Ebcin
Theses and Dissertations
The motivation of this research is to address the benefits of tightly integrating optical and inertial sensors where GNSS signals are not available. The research begins with describing the navigation problem. Then, error and measurement models are presented. Given a set of features, a feature detection and projection algorithm is developed which utilizes inertial measurements to predict vectors in the feature space between images. The unscented Kalman filter is applied to the navigation system using the inertial measurements and feature matches to estimate the navigation trajectory. Finally, the image-aided navigation algorithm is tested using a simulation and an experiment. As …
Stochastic Estimation And Control Of Queues Within A Computer Network, Nathan C. Stuckey
Stochastic Estimation And Control Of Queues Within A Computer Network, Nathan C. Stuckey
Theses and Dissertations
An extended Kalman filter is used to estimate size and packet arrival rate of network queues. These estimates are used by a LQG steady state linear perturbation PI controller to regulate queue size within a computer network. This paper presents the derivation of the transient queue behavior for a system with Poisson traffic and exponential service times. This result is then validated for ideal traffic using a network simulated in OPNET. A more complex OPNET model is then used to test the adequacy of the transient queue size model when non-Poisson traffic is combined. The extended Kalman filter theory is …
Theory Of Effectiveness Measurement, Richard K. Bullock
Theory Of Effectiveness Measurement, Richard K. Bullock
Theses and Dissertations
Effectiveness measures provide decision makers feedback on the impact of deliberate actions and affect critical issues such as allocation of scarce resources, as well as whether to maintain or change existing strategy. Currently, however, there is no formal foundation for formulating effectiveness measures. This research presents a new framework for effectiveness measurement from both a theoretical and practical view. First, accepted effects-based principles, as well as fundamental measurement concepts are combined into a general, domain independent, effectiveness measurement methodology. This is accomplished by defining effectiveness measurement as the difference, or conceptual distance from a given system state to some reference …
New Tracking Filter Algorithm Using Input Parameter Estimation, Corey M. Broussard
New Tracking Filter Algorithm Using Input Parameter Estimation, Corey M. Broussard
Theses and Dissertations
A new method for the design of tracking filters for maneuvering targets, based on kinematic models and input signals estimation, is developed. The input signal's level, u is considered a continuous variable and consequently the input estimation problem is posed as a purely parameter estimation problem. Moreover, the application of the new tracking filter algorithm is not contingent on distinguishing maneuvering and non-maneuvering targets, and does not require the detection of maneuver onset. The filter will automatically detect the onset of a maneuver. Furthermore, an estimate of the target's acceleration is also obtained with reasonable precision. This opens the door …
Generalized Residual Multiple Model Adaptive Estimation Of Parameters And States, Charles D. Ormsby
Generalized Residual Multiple Model Adaptive Estimation Of Parameters And States, Charles D. Ormsby
Theses and Dissertations
This dissertation develops a modification to the standard Multiple Model Adaptive Estimator (MMAE) which allows the use of a new "generalized residual" in the hypothesis conditional probability calculation. The generalized residual is a linear combination of traditional Kalman filter residuals and "post-fit" Kalman filter residuals which are calculated after measurement incorporation. This modified MMAE is termed a Generalized Residual Multiple Model Adaptive Estimator (GRMMAE). The dissertation provides a derivation of the hypothesis conditional probability formula which the GRMMAE uses to calculate probabilities that each elemental filter in the GRMMAE contains the correct parameter value. Through appropriate choice of a single …
Algorithm Development For On-Line Control Of The Airborne Laser, Michael W. Oppenheimer
Algorithm Development For On-Line Control Of The Airborne Laser, Michael W. Oppenheimer
Theses and Dissertations
The use of adaptive optics entails the design of a controller. This requires the development of a model of the plant to be controlled, which, in this case, Consists of the atmosphere through which light is traveling. In optics, Zemike polynornials are used as a basis set for the expansion of wavefront phase distortions. Due to the turbulence induced stochastic nature of the underlying process involved, the spatial-temporal correlation functions of the Zemike polynomial phase expansion coefficients must be evaluated if a proper stochastic model of the plant is to be developed and adaptive optics is to be employed. In …
New Algorithms For Moving-Bank Multiple Model Adaptive Estimation, Juan R. Vasquez
New Algorithms For Moving-Bank Multiple Model Adaptive Estimation, Juan R. Vasquez
Theses and Dissertations
The focus of this research is to provide methods for generating precise parameter estimates in the face of potentially significant parameter variations such as system component failures. The standard Multiple Model Adaptive Estimation (MMAE) algorithm uses a bank of Kalman filters, each based on a different model of the system. A new moving-bank MMAE algorithm is developed based on exploitation of the density data available from the MMAE. The methods used to exploit this information include various measures of the density data and a decision-making logic used to move, expand, and contract the MMAE bank of filters. Parameter discretization within …
Practical Implementation Of Multiple Model Adaptive Estimation Using Neyman-Pearson Based Hypothesis Testing And Spectral Estimation Tools, Peter D. Hanlon
Practical Implementation Of Multiple Model Adaptive Estimation Using Neyman-Pearson Based Hypothesis Testing And Spectral Estimation Tools, Peter D. Hanlon
Theses and Dissertations
This study investigates and develops various modifications to the Multiple Model Adaptive Estimation (MMAE) algorithm. The standard MMAE uses a bank of Kalman filters, each based on a different model of the system. Each of the filters predict the system response, based on its system model, to a given input and form the residual difference between the prediction and sensor measurements of the system response. Model differences in the input matrix, output matrix, and state transition matrix, which respectively correspond to an actuator failure, sensor failure, and an incorrectly modeled flight condition for a flight control failure application, were investigated …
A Comparison Of Loose And Tight Gps/Ins Integration Using Real Ins And Gps Data, Warren H. Nuibe
A Comparison Of Loose And Tight Gps/Ins Integration Using Real Ins And Gps Data, Warren H. Nuibe
Theses and Dissertations
An extended Kalman filter (EKE) is used to combine the information obtained from a Global Positioning System (GPS) receiver and an Inertial Navigation System (INS) to provide a navigation solution. This research compares the results of a tightly-coupled GPS/INS integrated system with a loosely-coupled integrated system, using real world data. A fair comparison is accomplished by using the same sets of data, and keeping the integration structures as close as possible. Both integrations are feedforward and have the same error states in the navigation Kalman filters. Differences between the two, such as navigation solutions and tuning values, are shown in …
Reducing Lag In Virtual Displays Using Multiple Model Adaptive Estimation, David W. Kyger
Reducing Lag In Virtual Displays Using Multiple Model Adaptive Estimation, David W. Kyger
Theses and Dissertations
Multiple Model Adaptive Estimation is an effective method for reducing lag in virtual environment displays. Lag in displays (the time from head motion to the appearance of the proper image on the display) is a significant detriment to realism in virtual environments. Increasing the speed of the computers which control the virtual display is not a final answer. No matter how fast the processors work, there will always be demands to do more. Predicting angular head positions (look-angles) can reduce the lag by allowing the computer to calculate the appropriate scene before it is needed on the display. Single predictors …
Multiple Model Adaptive Estimation And Head Motion Tracking In A Virtual Environment: An Engineering Approach, James E. Russell
Multiple Model Adaptive Estimation And Head Motion Tracking In A Virtual Environment: An Engineering Approach, James E. Russell
Theses and Dissertations
Software engineering tools and techniques were applied to design and implement an application that reduces lag typically present in virtual environment displays. The application was a Multiple Model Adaptive Estimator (MMAE), composed of three Kalman filters, that predicted head orientation one sample period into the future. The environment rendering software used these predictions to generate the environment display. Each of the filters in the MMAE was designed for a different assumed head motion type (benign, moderate, or heavy), which allowed the MMAE to adapt to changes in head movement characteristics. The use of Ada 9X as an implementation language for …
Feasibility Analysis For Predicting A Kinetic Kill Zone For Aircraft Homing Missile Defense, Mark E. Ennis
Feasibility Analysis For Predicting A Kinetic Kill Zone For Aircraft Homing Missile Defense, Mark E. Ennis
Theses and Dissertations
An extended Kalman filter is used to predict a kinetic kill zone for use in aircraft self defense versus homing missiles. The analysis is limited to an in-the-plane analysis and focuses on finding the model parameters which have the largest impact on the predicted kill zone. No attempt is made to optimize the design of the filter model itself. The analysis computes the kill zone relative to an assumed aircraft trajectory using strictly filter computed statistics. No Monte-Carlo simulations are used throughout the thesis. The filter assumed to be on the evading aircraft, uses an onboard laser radar (ladar) to …
Multiple Model Adaptive Estimation Applied To The Lambda Urv For Failure Detection And Identification, David W. Lane
Multiple Model Adaptive Estimation Applied To The Lambda Urv For Failure Detection And Identification, David W. Lane
Theses and Dissertations
Multiple Model Adaptive Estimation (MMAE) is a method of estimating unknown system parameters by modeling all possible parameter configurations in several models. The parameters for this research are failure status conditions associated with flight control actuators and sensors on the LAMBDA Unmanned Research Vehicle, an experimental aircraft operated by Wright Laboratory Flight Controls Division at Wright-Patterson Air Force Base, Ohio. Six actuator failures and eight sensor failures are modeled, along with the fully functional aircraft, in fifteen elemental Kalman filters. These filters propagate and update their own aircraft state estimates in real time. A probability computation representing the likelihood of …
Failure Detection, Isolation, And Recovery In An Integrated Navigation System, William B. Mosle Iii
Failure Detection, Isolation, And Recovery In An Integrated Navigation System, William B. Mosle Iii
Theses and Dissertations
An Inertial Navigation System (INS), the Global Positioning System (GPS), and a ground based transponder system (RRS) can all be used to provide the user with a navigation solution. Yet by integrating these three navigation systems with an extended Kalman filter (EKF), a navigation solution is attained that benefits from the information of all three subsystems. This research develops a multiple model EKF failure detection, isolation, and recovery (FDIR) algorithm using a Chi-Square failure test to provide robust navigation solution to measurement failures. The algorithm specifically counters failures in the GPS and RRS range measurements. Analysis is conducted using a …
Stochastic Estimation Applied To The Land Speed Of Sound Record Attempt By A Rocket Car, David A. Reinholz
Stochastic Estimation Applied To The Land Speed Of Sound Record Attempt By A Rocket Car, David A. Reinholz
Theses and Dissertations
Optimal linear smoothing theory is applied to the data from the Speed of Sound record attempt of a three-wheeled rocket car on 17 December 1979. A forward-backward estimation method is used which employs a seven state forward-running extended Kalman filter and a Meditch-form backward recursive 'fixed-interval' smoothing algorithm. Data for this analysis is supplied by a longitudinal accelerometer mounted on the vehicle and tracking radar measurements of range, azimuth, and elevation. States of interest include two components of vehicle position and velocity, accelerometer time-correlated error, and radar range and azimuth bias errors. Two iterations of the forward-backward smoothing algorithm provide …