SHIP STATE AND COVARIANCE PROPAGATION USING TIME SERIES ANALYSIS AND FORECASTING Katre, Aniruddha The Navy's Unmanned Combat Aerial System (N-UCAS) program is currently developing technology for autonomous shipboard landing of unmanned aerial vehicles (UAVs). A high accuracy and high integrity relative navigation algorithm using carrier phase di erential GPS measurements and high rate inertial sensor data has been implemented to land the UAV. Such an algorithm requires ship state information to be broadcast to the aircraft via a VHF data link. The data link is susceptible to failure for reasons such as interference from jamming. This thesis considers the problem of precise ship state propagation on board an aircraft during a data link outage occuring when it is too late for the aircraft to abort its landing approach. Accurately quantifying the estimate error covariance is important for a high integrity and accuracy navigation algorithm. Therefore this thesis focuses on algorithms that can propagate the ship state as well as determine the propagation error covariance. Initially, a simple state propagation using kinematic equations for linear motion is tested. Seakeeping and Maneuvering theories used to model the dynamics of a sea vessel are also considered. However, analysis shows that due to constraints imposed by a data link outage and complexity in accurately modeling some parameters in the ship dynamic model, these two approaches are infeasible. As an alternative to kinematic and dynamic modeling, Time Series Analysis and Forecasting methods for ship state propagation are investigated. This work introduces parametric modeling and forecasting of a time series using linear stochastic models. Maximum likelihood estimate (MLE) and outer product of gradients (OPG) algorithms are implemented for faithful parameterization of time series using ARIMA models. Expressions for forecasting and forecast error variance quanti cation are also developed. These algorithms are then tested using ship data provided by the N-UCAS program. M.S. in Mechanical and Aerospace Engineering, May 2014 Pervan, Boris S. 2014 2014-05 Thesis application/pdf islandora:6495 http://hdl.handle.net/10560/3280 MMAE / Mechanical, Materials, and Aerospace Engineering Illinois Institute of Technology en In Copyright http://rightsstatements.org/page/InC/1.0/ Restricted Access