Approved for public release; distribution is unlimited / The United States Navy is committed to implementing and using unmanned vehicles (UVs). Battlegroups have deployed and will continue to deploy with UVs because of their potential effectiveness. However, current UV doctrine does not set forth a standardized set of techniques and procedures for UV information exchange during maritime missions. The focus of this study is to analyze the structure of information flow for unmanned systems and suggest an exchange architecture to successfully inform and build decision maker understanding based on data from UVs in support of these missions. Through analysis of the knowledge-information-data (KID) model, and definition of highlevel functions and tasks created from fleet input, this thesis develops an IDEF0 and PERT representation. It outlines tasks and roles for successfully accomplishing information exchange from UV payload sensors to tactical decision makers. The study concludes with suggested measures of effectiveness and performance to determine the strength and validity of the architecture. / Ensign, United States Navy

As the U.S. Navy develops new technologies which enhance automation and reduce crew size onboard naval vessels, unmanned vehicles will become increasingly valuable in conducting maritime operations. Effective launch and recovery systems (LARS) are necessary for unmanned vehicles to efficiently conduct operations at sea. The Towed Body system is a LARS with a wide range of applications for unmanned vehicle operations. The Towed Body can be evaluated as a small vessel with horizontal and vertical control surfaces. Since it is being towed, the directional stability of the Towed Body requires unique consideration due to the presence of the towing force. This thesis examines the effect of varying the longitudinal location of the vertical control surfaces, as well as the effective aspect ratio, size, and number of vertical control surfaces. The results identify critical stability values for the various fin configurations.

Thesis (M. Sc.)--University of Alberta, 2009. / Title from pdf file main screen (viewed on Dec. 23, 2009). "A thesis submitted to the Faculty of Graduate Studies and Research in partial fulfillment of the requirements for the degree of Master of Science, Department of Mechanical Engineering, University of Alberta." Includes bibliographical references.

Thesis (M.S. in Systems Technology (Command, Control, and Communications))--Naval Postgraduate School, June 2004. / Thesis advisor(s): Orin Marvel. Includes bibliographical references (p. 41-43, 45-46). Also available online.

Thesis (M.S. in Applied Science (Operations Research))--Naval Postgraduate School, June 2004. / Thesis advisor(s): Susan M. Sanchez. Includes bibliographical references (p. 79-80). Also available online.

Thesis (M.S. in Aeronautical Engineering)--Naval Postgraduate School, September 1990. / Thesis Advisor(s): Howard, Richard M. Second Reader: Pagenkopf, Eric L. "September 1990." Description based on title screen as viewed on December 18, 2009. DTIC Descriptor(s): Unmanned, Flight Testing, Angles, Steady State, Measurement, Vibration, Maneuverability, Marine Corps, Aircraft, Scale Models, Structural Properties, Tail Assemblies, Theses, Angle Of Attack, Estimates, Fuels, Endurance(General), Flight, Response, Scale, Weight, Airframes, Airspeed, Instrumentation, Recording Systems, Sideslip, Maneuvers, Behavior, Flow, Vehicles, Wings, Altitude, Failure(Mechanics), Radio Signals, Remote Control, Control Surfaces, Directional, Booms(Equipment), Propellers, Data Bases, Data Processing. DTIC Identifier(s): Remotely Piloted Vehicles, Unmanned Air Vehicles, Aerodynamic Control Surfaces, Aerodynamic Characteristics, Flight Testing, Pitch(Motion). Yaw, Flight Maneuvers, Theses. Includes bibliographical references (p. 55). Also available in print.

No description available.

No description available.

[Abstract]Agricultural crops exhibit within-field spatial variation. This variation partly results from relevant bio-physical and environmental factors that influence thecrop during the growing season. The plant integrates the effects of nutrition, water, pests and disease, and displays the results in the foliage. Remote sensing techniques allow the foliage to be monitored and the crop status to be assessed.While the use of conventional remote sensing systems has found many applications in agriculture, it is constrained by a number of issues and problems related to spatial resolution, repeat cycle, minimum area acquired, timeliness of data, etc. Thus, this research explores the potential of developing and assessing low-cost sensing technologies to overcome these limitations. The specificobjectives were to: a) identify, evaluate, and analyse the different options for a low-cost low-altitude (LCLA) remote sensing system that has potential for precision agriculture, b) develop a LCLA remote sensing system that is appropriate for use in mapping selected crop attributes (i.e. grain protein, yield, maturity and crop type), and c) evaluate the accuracy of classification and prediction of the cereal crop attributes.A low-cost sensor system was developed that incorporated two consumer digital still cameras. One camera captured the colour portion of the spectrum, while the other one (with the addition of a band-pass filter) captured the nearinfrared light. Both cameras were modified to be remotely triggered and externally powered. This sensor arrangement utilised 1.0 megapixel cameras in the earlier investigations and then 5.0 megapixel cameras in most recent missions. The sensors were equally well suited to mounting on a remotely controlled aircraft or suspended beneath a helium balloon.Various approaches were taken to determine and evaluate the relationships between imagery and crop attributes. Statistical methods included the use of correlation and discriminant function analysis, along with partial least squares regression. Image analysis techniques included the use of both pixel-based (supervised approach) and object-orientated (multi-resolution segmentation) classifications.The results showed that low-cost low-altitude remote sensing systems (incorporating consumer digital cameras with helium balloons or remotely controlled aircraft) have great capacity to quantify variability in cereal graincrops. Excellent relationships were found between the ‘at-harvest’ yield (R2=0.902) and protein content (R2=0.660) of wheat using a single image recorded at flowering. Partial least squares regression, using the crossvalidatedapproach, produced a stronger relationship with a prediction accuracy of 94.2% for yield and 88.5% for protein. This relationship exceeded all other studies reported in the literature.The same LCLA system has also accurately discriminated (using statistical methods) between: a) different nutrition levels in a wheat crop with 75.6% of the cases correctly classified, and b) between different cereal grain species (with differing nutrition levels) with 86.3% accuracy. These classification accuracies are comparable with, or exceeding other more expensive and/or complicated methods. Attempting to discriminate using image analysisprocedures, the pixel-based methods yielded an overall accuracy of 65.9% when classifying cereal grain crop species comprising of nine classes. When merged to six classes, the accuracy improved to 82.1%. Using an objectorientated approach has improved the overall accuracy to 81.0% for the ninecategory classification. This study also demonstrated LCLA’s ability to assessthe various growth stages of a barley crop prior to maturity with 83.5% of cases correctly classified.This study concluded that it is feasible to accurately assess selected cereal grain crop attributes using low-cost consumer technologies. The accuracies achievedusing this system were comparable with, or exceeded, other reported studies that used more complicated and expensive sampling systems. Further work is needed to continue refining the initial work on a fully autonomous unmannedaerial vehicle (UAV) started in the later part of this study, to extend the use of the LCLA system into broader scale applications.

Thesis (M.S.)--University of Nevada, Reno, 2007. / "August, 2007." Includes bibliographical references (leaf 57). Online version available on the World Wide Web.