Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 5 of 5
Full-Text Articles in Engineering
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 …
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 …
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 …
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 …