Thesis (M.S.)--Naval Postgraduate School, 2002. / Thesis advisor(s): Gordon Bradley, John Hiles, Arnold Buss. Includes bibliographical references (p. 107-108). Also available online.

For decades our military has been designed and funded as a conventionally superior force on the battlefield employing the most devastating and advanced weapon systems the world has ever seen (World, War I, II, Operation Desert Storm, and Phase I of Operation Iraqi Freedom). However, in low intensity conflicts (LICs) or irregular warfare (IW) campaigns, U.S. forces are faced with an irregular enemy, one that does not choose to fight our forces directly but rather through unconventional or indirect methods. For over 60 years, the Department of Defense has had an appalling record of protecting its air bases and personnel while deployed around the world in support of low intensity conflicts. However, the way the military defends and protects these air bases still revolves around a Cold War threat, a conventional threat. The strategy of global power projection and forward presence are the cornerstone to U.S. defense. To enhance combat capabilities in the Air Force and to defeat irregular warfare (IW) forces in any environment, the answer lies within the concept of Integrated Swarming Operations (ISO); the complete integration of a highly trained security force, skilled in the employment of successful counterinsurgency tactics, techniques, and procedures (TTPs), with today's most sophisticated Command, Control, Communications, Computer and Intelligence, Surveillance, and Reconnaissance (C4ISR) platforms into a battlefield swarm. In doing so, ISO allows security forces to achieve their three critical air base defense Mission Essential Tasks (METs) of 1) tactical ISR, 2) intercepting the threat, and 3) application of force as well as the Air Force's Integrated Base Defense (IBD) Objectives of "See First, Understand First, and Act First." / US Air Force (USAF) author.

Thesis (M.S. in Electrical Engineering)--Naval Postgraduate School, June 2005. / Thesis Advisor(s): Phillip E. Pace Includes bibliographical references (p. 109). Also available online.

Unmanned Aerial Vehicles (UAVs) are becoming vital warfare platforms because they significantly reduce the risk of human life while accomplishing important missions. A UAV can be used for example, as stand-in sensor for the detection of mobile, low-probability-of-intercept battlefield surveillance and fire control emitters. With many UAVs acting together as a swarm, the location and frequency characteristics of each emitter can be accurately determined to continuously provide complete battlefield awareness. The swarm should be able to act autonomously while searching for targets and relaying the information to all swarm members. In this thesis, two methods of autonomous control of a UAV swarm were investigated. The first method investigated was the Particle Swarm Optimization (PSO) algorithm. This technique uses a non-linear approach to minimize the error between the location of each particle and the target by accelerating particles through the search space until the target is found. When applied to a swarm of UAVs, the PSO algorithm did not produce the desired performance results. The second method used a linear algorithm to determine the correct heading and maneuver the swarm toward the target at a constant velocity. This thesis shows that the second approach is more practical to a UAV swarm. New results are shown to demonstrate the application of the algorithm to the swarm movement.