APPLYING MACHINE LEARNING FOR COP/CTP DATA FILTERING

Student Thesis (NPS NRP Project Related)Accurate tracks and targeting are key to providing decision-makers with the confidence to execute their missions. Increasingly, multiple intelligence, surveillance, and reconnaissance (ISR) assets across different intelligence sources are being used to increase the accuracy of track location, resulting in the need to develop methods to exploit heterogeneous sensor data streams for better target state estimation. One of the algorithms commonly used for target state estimation is the Kalman Filter (KF) algorithm. This algorithm performs well if its covariance matrices are accurate approximations of the uncertainty in sensor measurements. Our research complements the artificial intelligence/machine learning (AI/ML) efforts the U.S. Navy is conducting by quantitatively assessing the potential of using an ML model to predict sensor measurement noise for KF state estimation. We used a computer simulation to generate sensor tracks of a single target and trained a neural network to predict sensor error. The hybrid model (ML-KF) was able to outperform our baseline KF model that uses normalized sensor errors by approximately 20% in target position estimation. Further research in enhancing the ML model with external environment variables as inputs could potentially create an adaptive state estimation system that is capable of operating in varied environment settings.NPS Naval Research ProgramThis project was funded in part by the NPS Naval Research Program.Outstanding ThesisCaptain, Singapore ArmyApproved for public release. Distribution is unlimited

A Bayesian Abduction Model For Sensemaking

This research develops a Bayesian Abduction Model for Sensemaking Support (BAMSS) for information fusion in sensemaking tasks. Two methods are investigated. The first is the classical Bayesian information fusion with belief updating (using Bayesian clustering algorithm) and abductive inference. The second method uses a Genetic Algorithm (BAMSS-GA) to search for the k-best most probable explanation (MPE) in the network. Using various data from recent Iraq and Afghanistan conflicts, experimental simulations were conducted to compare the methods using posterior probability values which can be used to give insightful information for prospective sensemaking. The inference results demonstrate the utility of BAMSS as a computational model for sensemaking. The major results obtained are: (1) The inference results from BAMSS-GA gave average posterior probabilities that were 103 better than those produced by BAMSS; (2) BAMSS-GA gave more consistent posterior probabilities as measured by variances; and (3) BAMSS was able to give an MPE while BAMSS-GA was able to identify the optimal values for kMPEs. In the experiments, out of 20 MPEs generated by BAMSS, BAMSS-GA was able to identify 7 plausible network solutions resulting in less amount of information needed for sensemaking and reducing the inference search space by 7/20 (35%). The results reveal that GA can be used successfully in Bayesian information fusion as a search technique to identify those significant posterior probabilities useful for sensemaking. BAMSS-GA was also more robust in overcoming the problem of bounded search that is a constraint to Bayesian clustering and inference state space in BAMSS

Filling the Ontology Space for Coalition Battle Management Language

The Coalition Battle Management Language is a language for representing and exchanging plans, orders, and reports across live, constructive and robotic forces in multi-service, multi-national and multi-organizational operations. Standardization efforts in the Simulation Interoperability Standards Organization seek to define this language through three parallel activities: (1) specify a sufficient data model to unambiguously define a set of orders using the Joint Command, Control, and Consultation Information Exchange Data Model (JC3IEDM) as a starting point; (2) develop a formal grammar (lexicon and production rules) to formalize the definition of orders, requests, and reports; (3) develop a formal battle management ontology to enable conceptual interoperability across software systems. This paper focuses on the third activity, development of a formal battle management ontology, by describing an ontology space for potential technical approaches. An ontology space is a notional three dimensional space with qualitative axes representing: (1) the Ontological Spectrum; (2) the Levels of Conceptual Interoperability Model; and (3) candidate representation sources that can contribute to conceptual interoperability for the Coalition Battle Management Language. The first dimension is the Ontological Spectrum, which shows increasing levels of semantic formalism using various ontology representation artifacts. The second dimension is the Levels of Conceptual Interoperability Model, which describes varying levels of interoperability that can be attained across systems. The third dimension is a survey of likely candidate sources to provide the representation elements required for interoperability. This third dimension will be further described in relation to the artifact capabilities of the second dimension and the conceptual interoperability capabilities of the first dimension to highlight what is possible for ontological representation in C-BML with existing sources, and what needs to be added. The paper identifies requirements for building the ontology artifacts (starting with a controlled vocabulary) for conceptual interoperability, the highest level described in the LCIM, and gives a path ahead for increasingly logical artifacts

Exploring Fog of War Concepts in Wargame Scenarios

This thesis explores fog of war concepts through three submitted journal articles. The Department of Defense and U.S. Air Force are attempting to analyze war scenarios to aid the decision-making process; fog modeling improves realism in these wargame scenarios. The first article Navigating an Enemy Contested Area with a Parallel Search Algorithm [1] investigates a parallel algorithm\u27s speedup, compared to the sequential implementation, with varying map configurations in a tile-based wargame. The parallel speedup tends to exceed 50 but in certain situations. The sequential algorithm outperforms it depending on the configuration of enemy location and amount on the map. The second article Modeling Fog of War Effects in AFSIM [2] introduces the FAT for the AFSIM to introduce and manipulate fog in wargame scenarios. FAT integrates into AFSIM version 2.7.0 and scenario results verify the tool\u27s fog effects for positioning error, hits, and probability affect the success rate. The third article Applying Fog Analysis Tool to AFSIM Multi-Domain CLASS scenarios [3] furthers the verification of FAT to introduce fog across all war fighting domains using a set of CLASS scenarios. The success rate trends with fog impact for each domain scenario support FAT\u27s effectiveness in disrupting the decision-making process for multi-domain operations. The three articles demonstrate fog can affect search, tasking, and decision-making processes for various types of wargame scenarios. The capabilities introduced in this thesis support wargame analysts to improve decision-making in AFSIM military scenarios

Improving the Analyst and Decision-Maker’s Perspective through Uncertainty Visualization

This thesis constructs the Taxonomy of Uncertainty and an approach for enhancing the information in decision support systems. The hierarchical categorization of numerous causes for uncertainty defines the taxonomy, which fostered the development of a technique for visualizing uncertainty. This technique is fundamental to expressing the multi-dimensional uncertainty that can be associated with any object. By including and intuitively expressing uncertainty, the approach facilitates and enhances intuition and decision-making without undue information overload. The resulting approach for enhancing the information involves recording uncertainty, identifying the relevant items, computing and visualizing uncertainty, and providing interaction with the selection of uncertainty. A prototype embodying this approach to enhancing information by including uncertainty was used to validate these efforts. Evaluation responses of a small sample space support the thesis that the decision-maker\u27s knowledge is enhanced with enlightening information afforded by including and visualizing uncertainty, which can improve the decision-making process. Although the concept was initially conceived to help decision support system users deal with uncertainty, this methodology and these ideas can be applied to any problem where objects with many potential reasons for uncertainty are the focus of the decision-making

Airborne Directional Networking: Topology Control Protocol Design

This research identifies and evaluates the impact of several architectural design choices in relation to airborne networking in contested environments related to autonomous topology control. Using simulation, we evaluate topology reconfiguration effectiveness using classical performance metrics for different point-to-point communication architectures. Our attention is focused on the design choices which have the greatest impact on reliability, scalability, and performance. In this work, we discuss the impact of several practical considerations of airborne networking in contested environments related to autonomous topology control modeling. Using simulation, we derive multiple classical performance metrics to evaluate topology reconfiguration effectiveness for different point-to-point communication architecture attributes for the purpose of qualifying protocol design elements

IMMACCS: A Multi-Agent Decision-Support System

This report describes work performed by the Collaborative Agent Design Research Center for the US Marine Corps Warfighting Laboratory (MCWL), on the IMMACCS experimental decision-support system. IMMACCS (Integrated Marine Multi-Agent Command and Control System) incorporates three fundamental concepts that distinguish it from existing (i.e., legacy) command and control applications. First, it is a collaborative system in which computer-based agents assist human operators by monitoring, analyzing, and reasoning about events in near real-time. Second, IMMACCS includes an ontological model of the battlespace that represents the behavioral characteristics and relationships among real world entities such as friendly and enemy assets, infrastructure objects (e.g., buildings, roads, and rivers), and abstract notions. This object model provides the essential common language that binds all IMMACCS components into an integrated and adaptive decision-support system. Third, IMMACCS provides no ready made solutions that may not be applicable to the problems that will occur in the real world. Instead, the agents represent a powerful set of tools that together with the human operators can adjust themselves to the problem situations that cannot be predicted in advance. In this respect, IMMACCS is an adaptive command and control system that supports planning, execution and training functions concurrently. The report describes the nature and functional requirements of military command and control, the architectural features of IMMACCS that are designed to support these operational requirements, the capabilities of the tools (i.e., agents) that IMMACCS offers its users, and the manner in which these tools can be applied. Finally, the performance of IMMACCS during the Urban Warrior Advanced Warfighting Experiment held in California in March, 1999, is discussed from an operational viewpoint

2007 Annual Report of the Graduate School of Engineering and Management, Air Force Institute of Technology

The Graduate School\u27s Annual Report highlights research focus areas, new academic programs, faculty accomplishments and news, and provides top-level sponsor-funded research data and information

Game Theory and Prescriptive Analytics for Naval Wargaming Battle Management Aids

NPS NRP Technical ReportThe Navy is taking advantage of advances in computational technologies and data analytic methods to automate and enhance tactical decisions and support warfighters in highly complex combat environments. Novel automated techniques offer opportunities to support the tactical warfighter through enhanced situational awareness, automated reasoning and problem-solving, and faster decision timelines. This study will investigate how game theory and prescriptive analytics methods can be used to develop real-time wargaming capabilities to support warfighters in their ability to explore and evaluate the possible consequences of different tactical COAs to improve tactical missions. This study will develop a conceptual design of a real-time tactical wargaming capability. This study will explore data analytic methods including game theory, prescriptive analytics, and artificial intelligence (AI) to evaluate their potential to support real-time wargaming.N2/N6 - Information WarfareThis research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

SUPPORTING MISSION PLANNING WITH A PERSISTENT AUGMENTED ENVIRONMENT

Includes supplementary materialIncludes Supplementary MaterialThe Department of the Navy relies on current naval practices such as briefs, chat, and voice reports to provide an overall operational assessment of the fleet. That includes the cyber domain, or battlespace, depicting a single snapshot of a ship’s network equipment and service statuses. However, the information can be outdated and inaccurate, creating confusion among decision-makers in understanding the service and availability of equipment in the cyber domain. We examine the ability of a persistent augmented environment (PAE) and 3D visualization to support communications and cyber network operations, reporting, and resource management decision-making. We designed and developed a PAE prototype and tested the usability of its interface. Our study examined users’ comprehension of 3D visualization of the naval cyber battlespace onboard multiple ships and evaluated the PAE’s ability to assist in effective mission planning at the tactical level. The results are highly encouraging: the participants were able to complete their tasks successfully. They found the interface easy to understand and operate, and the prototype was characterized as a valuable alternative to their current practices. Our research provides close insights into the feasibility and effectiveness of the novel form of data representation and its capability to support faster and improved situational awareness and decision-making in a complex operational technology (OT) environment between diverse communities.Lieutenant, United States NavyLieutenant, United States NavyApproved for public release. Distribution is unlimited