<p>The mental workload for fighter pilots in modern air combat is extremely high. The pilot has to make fast dynamic decisions under high uncertainty and high time pressure. This is hard to perform in close encounters, but gets even harder when operating beyond visual range when the sensors of an aircraft become the pilot's eyes and ears. Although sensors provide good estimates for position and speed of an opponent, there is a big loss in the assessment of a situation. Important tactical events or situations can occur without the pilot noticing, which can change the outcome of a mission completely. This makes the development of an automated situation assessment system very important for future fighter aircraft. </p><p>This Master Thesis investigates the possibilities to design and implement an automated situation assessment system in a fighter aircraft. A Fuzzy-Bayesian hybrid technique is used in order to cope with the stochastic environment and making the development of the tactical situations library as clear and simple as possible.</p>

Thesis (Ph. D.)--University of Missouri-Columbia, 2000. / Typescript. Vita. Includes bibliographical references (leaves 210-216). Also available on the Internet.

Thesis (Ph. D.)--University of Missouri-Columbia, 2000. / Typescript. Vita. Includes bibliographical references (leaves 210-216). Also available on the Internet.

Thesis ( Ph.D. ) -- University of Texas at Arlington, 2008.

ITC/USA 2012 Conference Proceedings / The Forty-Eighth Annual International Telemetering Conference and Technical Exhibition / October 22-25, 2012 / Town and Country Resort & Convention Center, San Diego, California / A major intelligence challenge we face in today's national security environment is the threat of terrorist attack against our national assets, especially our citizens. This paper addresses global reconnaissance which incorporates an autonomous Intelligent Agent/Data Fusion solution for recognizing potential risk of terrorist attack through identifying and reporting imminent persona-oriented terrorist threats based on data reduction/compression of a large volume of low latency data possibly from hundreds, or even thousands of data points.

With the advent of Network-Centric Warfare (NCW) concepts, Command and Control (C2) Systems need efficient methods for communicating between heterogeneous systems. To extract or exchange various levels of information within the networks requires interoperability between human and machine as well as between machine and machine. This dissertation explores the Information Exchange Framework (IEF) concept of distributed data fusion sensor networks in Network-centric environments. It is used to synthesize integrative battlefield pictures by combining the Battle Management Language (BML) and System Entity Structure (SES) ontology framework for C2 systems. The SES is an ontology framework that can facilitate information exchange in a network environment. From the perspective of the SES framework, BML serves to express pragmatic frames, since it can specify the information desired by a consumer in an unambiguous way. This thesis formulates information exchange in the SES ontology via BML and defines novel pruning and transformation processes of the SES to extract and fuse data into higher level representations. This supports the interoperability between human users and other sensor systems. The efficacy of such data fusion and exchange is illustrated with several battlefield scenario examples.A second intercommunication issue between sensor systems is how to ensure efficient and effective message passing. This is studied by using Cursor-on-Target (CoT), an effort to standardize a battlefield data exchange format. CoT regulates only a few essential data types as standard and has a simple and efficient structure to hold a wide range of message formats used in dissimilar military enterprises. This thesis adopts the common message type into radar sensor networks to manage the target tracking problem in distributed sensor networks.To demonstrate the effectiveness of the proposed Information Exchange Framework for data fusion systems, we illustrate the approach in an air defense operation scenario using DEVS modeling and simulation. The examples depict basic air defense operation procedure. The demonstration shows that the information requested by a commander is delivered in the right way at the right time so that it can support agile decision making against threats.

Global position system (GPS) is widely used in land vehicles but suffers deterioration in its accuracy in urban canyons; mostly due to satellite signal blockage and signal multipath. To obtain accurate, reliable, and continuous positioning solutions, GPS is usually augmented with inertial sensors, including accelerometers and gyroscopes to monitor both translational and rotational motions of a moving vehicle. Due to space and cost requirements, micro-electro-mechanical-system (MEMS) inertial sensors, which are typically inexpensive are presently utilized in land vehicles for various reasons and can be used for integration with GPS for navigation purposes. Kalman filtering (KF) usually used to performs this integration. However, the complex error characteristics of these MEMS based sensors lead to divergence of the positioning solution. Furthermore, the residual GPS pseudorange correlated errors are always ignored, thus reducing the GPS overall positioning accuracy. This thesis targets enhancing the performance of integrated MEMS based INS/GPS navigation systems through exploring new non-linear modelling approaches that can deal with the non-linear and correlated parts of INS and GPS errors. The research approach in this thesis relies on reduced inertial sensor systems (RISS) incorporating single axis gyroscope, vehicle odometer, and accelerometers is considered for the integration with GPS in one of two schemes; either loosely-coupled where GPS position and velocity are used for the integration or tightly-coupled where GPS pseudorange and pseudorange rates are utilized. A new method based on parallel cascade identification (PCI) is developed in this research to enhance the performance of KF by modelling azimuth errors for the RISS/GPS loosely-coupled integration scheme. In addition, PCI is also utilized for the modelling of residual GPS pseudorange correlated errors. This thesis develops a method to augment a PCI – based model of GPS pseudorange correlated errors to a tightly-coupled KF. In order to take full advantage of the PCI based models, this thesis explores the Particle filter (PF) as a non-linear integration scheme that is capable of accommodating the arbitrary sensor characteristics, motion dynamics, and noise distributions. The performance of the proposed methods is examined through several road test experiments in land vehicles involving different types of inertial sensors and GPS receivers. / Thesis (Ph.D, Electrical & Computer Engineering) -- Queen's University, 2012-07-31 16:09:16.559

A Cyber-Physical System integrates computations and dynamics of physical processes. It is an engineering discipline focused on technology with a strong foundation in mathematical abstractions. It shares many of these abstractions with engineering and computer science, but still requires adaptation to suit the dynamics of the physical world. In such a dynamic system, mobility management is one of the key issues against developing a new service. For example, in the study of a new mobile network, it is necessary to simulate and evaluate a protocol before deployment in the system. Mobility models characterize mobile agent movement patterns. On the other hand, they describe the conditions of the mobile services. The focus of this thesis is on mobility modeling in cyber-physical systems. A macroscopic model that captures the mobility of individuals (people and vehicles) can facilitate an unlimited number of applications. One fundamental and obvious example is traffic profiling. Mobility in most systems is a dynamic process and small non-linearities can lead to substantial errors in the model. Extensive research activities on statistical inference and filtering methods for data modeling in cyber-physical systems exist. In this thesis, several methods are employed for multimodal data fusion, localization and traffic modeling. A novel energy-aware sparse signal processing method is presented to process massive sensory data. At baseline, this research examines the application of statistical filters for mobility modeling and assessing the difficulties faced in fusing massive multi-modal sensory data. A statistical framework is developed to apply proposed methods on available measurements in cyber-physical systems. The proposed methods have employed various statistical filtering schemes (i.e., compressive sensing, particle filtering and kernel-based optimization) and applied them to multimodal data sets, acquired from intelligent transportation systems, wireless local area networks, cellular networks and air quality monitoring systems. Experimental results show the capability of these proposed methods in processing multimodal sensory data. It provides a macroscopic mobility model of mobile agents in an energy efficient way using inconsistent measurements.

This thesis presents the design, development, and testing of a multi-agent systems laboratory that will enable the experimental investigation of Networked Control Systems. Networked Control Systems (NCS) are integrations of computation, networking, and physical dynamics, in which embedded devices are networked to sense, monitor, execute collaborative tasks, and interact with the physical world. As the potential for applications of NCS has increased, so has the research interest in this area. Possible applications include search and rescue, scientific data collection, and health care monitoring systems. One of the primary challenges in applying NCS is designing distributed algorithms that will enable the networked devices to achieve global objectives. Another challenge is in ensuring that distributed algorithms have the necessary robustness to achieve those global objectives in dynamic and unpredictable environments. A multi-agent systems laboratory provides the researcher with a means to observe the behavior and performance of distributed algorithms as they are executed on a set of networked devices. Through this observation, the researcher may discover robustness issues that were not present in computer simulation. The objective of this research is to design and implement the infrastructure for a multi-agent systems laboratory to observe distributed algorithms implemented on networked devices.

Thesis (Ph. D.)--Rutgers University, 2007. / "Graduate Program in Computer Science." Includes bibliographical references (p. 86-91).