The AEGIS Cruiser Air-Defense Simulation is a program that models the operations of a Combat Information Center (CIC) team performing the ADC duties in a battle group using Multi-Agent System (MAS) technology implemented in the Java programming language. Set in the Arabian Gulf region, the simulation is a top-view, dynamic, graphics-driven software implementation that provides a picture of the CIC team grappling with a challenging, complex problem. Conceived primarily as a system to assist ships, waterfront training teams, and battle group staffs in ADC training and doctrine formulation, the simulation was designed to gain insight and understanding into the numerous factors (skills, experience, fatigue, aircraft numbers, weather, etc.) that influence the performance of the overall CIC team and watchstanders. The program explores the team's performance under abnormal or high intensity/stress situations by simulating their mental processes, decision-making aspects, communications patterns, and cognitive attributes. Everything in the scenario is logged, which allows for the reconstruction of interesting events (i.e. watchstander mistakes, chain-of-error analysis) for use in post-scenario training as well as the creation of new, more focused themes for actual CIC team scenarios. The simulation also tracks various watchstander and CIC team performance metrics for review by the user. / Lieutenant, United States Navy

Systems engineering introduces the notion of top-down design, which involves viewing an entire system comprised of its components as a whole functioning unit. This requires an understanding of how those components efficiently interact, with optimization of the process emphasized rather than solely focusing on micro-level system components. The traditional approach to the systems engineering process involves requirements decomposition and flow down across a hierarchy of decision making levels, in which needs and requirements at one level are transformed into a set of system product and process descriptions for the next lower level. This top-down requirements flow approach therefore requires an iterative process between adjacent levels to verify that the design solution satisfies the requirements, with no direct flow between nonadjacent hierarchy levels. This thesis introduces a methodology that enables decision makers anywhere across a system-of-systems hierarchy to rapidly and simultaneously manipulate the design space, however complex. A hierarchical decision making process will be developed in which a system-of-systems, or multiple operationally and managerially independent systems, interact to affect a series of top level metrics. This takes the notion of top-down requirements flow one step further to allow for simultaneous bottom-up and top-down design, enabled by the use of neural network surrogate models to represent the complex design space. Using a proof-of-concept case study of employing a guided projectile for mortar interception, this process will show how the iterative steps that are usually required when dealing with flowing requirements from one level to the next lower in the systems engineering process are eliminated, allowing for direct manipulation across nonadjacent levels in the hierarchy. For this system-of-systems environment comprised of a Monte Carlo based design space exploration employing rapid neural network surrogate models, both bottom-up and top-down design analysis may be executed simultaneously. This process enables any response to be treated as an independent variable, meaning that information can flow in either direction within the hierarchy.

Within the air defense domain, the Weapon-Target Allocation problem is a fundamental problem. This problem deals with the allocation of a set ofiring units or weapons to a set of hostile targets so that the total expected effect on targets is maximized. The Weapon-Target Allocation problem has been proven to be NP-Complete by Lloyd and Witsenhausen [14]. In this thesis, the use of various algorithms including search algorithms, maximum marginal return algorithms, evolutionary algorithms and bipartite graph matching algorithms are demonstrated to solve the problem. Algorithms from the literature are adjusted to the problem and implemented. In addition, existing algorithms are improved by taking care of the maximum allowed time criterion. A testbed is developed to be able to compare the algorithms. The developed testbed allows users to implement new algorithms and compare the algorithms that are selected by the users easily. Using the testbed, implemented algorithms are compared based on optimality and performance criteria. The results are examined and by combining the algorithms that give better results, a new algorithm is proposed to solve the problem more effciently. The proposed algorithm is also compared to the other algorithms and computational results of the algorithms are presented.

Thesis (M.S. in Joint Campaign Planning and Strategy)--Joint Forces Staff College, Joint Advanced Warfighting School, 2007. / Title from title screen; viewed on July 9, 2007. "05 April 2007." Electronic version of original print document. Includes bibliographical references (p. 71-76).

No description available.

Doctor of Philosophy / Traditional military descriptions of conflict tend to focus on the movement of soldiers and armies across battlefields. When the airplane emerged, it forced military theorists to contend with a new, vertical, dimension of conflict. In America, the United States Air Force assumed an important role in this vertical dimension as the country's delivery mechanism for nuclear weapons. However, at the same time that politicians, academics, and military officials debated the offensive uses for aircraft a second debate occurred describing how best to use military means to defend the North American continent. Those who advocated for a defensive system to protect North American, including the President Eisenhower, strongly advocated for a continent-wide test of the new air defense system. That test was conducted once a year between 1960 and 1962 during which all civilian air travel across the U.S. and Canada was suspended. The tests were called the "Sky Shield" exercises. This research shows how a prevailing mood of fear and vulnerability gave air defense proponents the political capital to build a continental air defense network and test it during the Sky Shield exercises. Further, it describes the enduring legacy of this domestically-focused Cold War defense program. The research finds that America's approach to Cold War continental defense was strong when it was aligned with the White House's nuclear strategy, but when successive political leaders changed nuclear strategies that decision negatively influenced continental defense programs. This research is useful because it examines a relatively under-explored area of Cold War defense programs. Traditionally these studies focus on offensive capabilities far from American shores. This study instead examines homeland defense and how it changed during the Cold War as a function of changing nuclear programs and changing threats to the United States.

During its first few decades, the People¡¦s Liberation Army Air Force strategy was primarily formulated to support the ground forces¡¦ needs. Serious changes in the way the PLAAF thought about its future really began as a result of Deng Xiaoping¡¦s 1985 ¡§strategic decision¡¨ that directed the armed forces to change from preparation for an ¡§early, major, and nuclear war¡¨ to preparation for ¡§local war.¡¨ These changes included writing new teaching materials, conducting research on combination of offensive and defensive capabilities, and doing research on campaign and strategic theory. Wang Hai initiated the concept of combination of offensive and defensive operations in 1987, but it did not receive much publicity. Since the Gulf war, the PLAAF has been grappling with the demands of a radically changed its strategy that underscored the technological obsolescence of their armaments and so fundamentally affected the missions of the air forces that its traditional training principles and objective were largely inapplicable to. In late 1999, the PLAAF¡¦s commander, Liu Shunyao, began to emphasize the need to fight offensive battles and declare PLAAF¡¦s strategy of combination of offensive and defensive operations to build a People¡¦s Liberation Army capable of waging ¡§local war under high-tech conditions.¡¨ In a future high-tech local war, the PLAAF will be called up as the first one to encounter the enemy and fight until the last minute. It is gradually transitioning from a support service into an independent one and from a national territory air defense type of air force into one that conducts combination of offensive and defensive operations. The PLAAF is working on its way to reform its military conformation, adjust its military training guidelines and renew its old equipment. By establishing an all-weather and attack-defense air force to battle in a modern high-tech environment, it is expected to acquire the full ability to perform ¡§local war under high-tech conditions.¡¨ The purposes of the thesis are as follows: 1. Illustrate the tendency and contents of current air power theories and wars. 2. Illustrate the stages of PLAAF¡¦s development and the roles and performances it takes on in the wars. 3. Clarify the theoretic contents of PLAAF¡¦s air power in each stage. 4. Conclude the present and future contents and actions of the PLAAF¡¦s air power on the theoretic and practical aspects. 5. Analyze the future developments and challenges of PLAAF¡¦s air power. Expected to focus on the discussion on the theoretic and practical aspects, the thesis was organized as a modal for explaining the PLAAF¡¦s air power and to be used as the referential basis to illustrate the developments of the past, present and future PLAAF¡¦s air power.

In this thesis, an error analysis based method is proposed to calculate single shot hit probability (PSSH) values of a fire control system. The proposed method considers that a weapon and a threat are located in three dimensional space. They may or may not have relative motion in three dimensions with respect to each other. The method accounts for the changes in environmental conditions. It is applicable in modeling and simulation as well as in top down design of a fire control system to reduce the design cost. The proposed method is applied to a specific fire control system and it is observed that PSSH values highly depend on the distance between the weapon and the threat, hence they are time varying. Monte Carlo simulation is used to model various defense scenarios in order to evaluate a heuristic developed by G&uuml / lez (2007) for weapon-threat assignment and scheduling of weapons&rsquo / shots. The heuristic uses the proposed method for PSSH and time of flight computation. It is observed that the difference between the results of simulation and heuristic depends on the scenario used.

In this thesis, mathematical modeling and heuristic approaches are developed for surface-to-air weapon-target allocation problem with time varying single shot hit probabilities (SSHP) against linearly approaching threats. First, a nonlinear mathematical model for the problem is formulated to maximize sum of the weighted survival probabilities of assets to be defended. Next, nonlinear objective function and constraints are linearized. Time varying SSHP values are approximated with appropriate closed forms and adapted to the linear model obtained. This model is tested on different scenarios and results are compared with those of the original nonlinear model. It is observed that the linear model is solved much faster than the nonlinear model and produces reasonably good solutions. It is inferred from the solutions of both models that engagements should be made as late as possible, when the threats are closer to the weapons, to have SSHP values higher. A construction heuristic is developed based on this scheme. An improvement heuristic that uses the solution of the construction heuristic is also proposed. Finally, all methods are tested on forty defense scenarios. Two fastest solution methods, the linear model and the construction heuristic, are compared on a large scenario and proposed as appropriate solution techniques for the weapon-target allocation problems.

It is in military engagements the task of the air defense to protect valuable assets such as air bases from being destroyed by hostile aircrafts and missiles. In order to fulfill this mission, the defenders are equipped with sensors and firing units. To infer whether a target is hostile and threatening or not is far from a trivial task. This is dealt with in a threat evaluation process, in which the targets are ranked based upon their estimated level of threat posed to the defended assets. Once the degree of threat has been estimated, the problem of weapon allocation comes into the picture. Given that a number of threatening targets have been identified, the defenders need to decide on whether any firing units shall be allocated to the targets, and if so, which firing unit to engage which target. To complicate matters, the outcomes of such engagements are usually stochastic. Moreover, there are often tight time constraints on how fast the threat evaluation and weapon allocation processes need to be executed. There are already today a large number of threat evaluation and weapon allocation (TEWA) systems in use, i.e. decision support systems aiding military decision makers with the threat evaluation and weapon allocation processes. However, despite the critical role of such systems, it is not clear how to evaluate the performance of the systems and their algorithms. Hence, the work in thesis is focused on the development and evaluation of TEWA systems, and the algorithms for threat evaluation and weapon allocation being part of such systems. A number of algorithms for threat evaluation and static weapon allocation are suggested and implemented, and testbeds for facilitating the evaluation of these are developed. Experimental results show that the use of particle swarm optimization is suitable for real-time target-based weapon allocation in situations involving up to approximately ten targets and ten firing units, while it for larger problem sizes gives better results to make use of an enhanced greedy maximum marginal return algorithm, or a genetic algorithm seeded with the solution returned by the greedy algorithm. / Fredrik Johansson forskar också vid Skövde Högskola, Informatics Research Centre / Fredrik Johansson also does research at the University of Skövde, Informatics Research Centre