SBIR-STTR Award

We propose a highly innovative modeling and analysis framework for distributed collaborative systems with aid of data-mining and data-fusion concept. Our approach has two major highly coupled parts: 1) Data fusion module. Mutliple-sensor data are fused to perform situation awareness. To generate the intent inference of the targets, we will extend Markov games via incorporating Multi-Cumulant Pareto Nash strategies and Graph concept. From a perspective of distributed decision making problem, we dynamically adapt Hierarchical Task Network and Auction algorithm for optimal meta-task decomposition and assignment. A collaborative search and tracking oriented sensor management algorithm based on Pursuit-Evasion game will be exploited to improve the performance of the multi-layered sensing system. 2) Data-mining module. Adaptation and pattern/feature recognition are carried out to dynamically select (or mine) appropriate features or feature sets and quickly associate them with the adversary intent and executable actions. In some time-critical scenarios, firstly, a primitive adversary intent estimation and the associated friendly force collaborative response actions can be quickly provided by the Data-mining module. Then, a refinement based on data-fusion will be carried out to improve the performance of the decision aids tool. Additionally, we will incorporate a semantic and textual processing technique to convert meta-tasks into actionable fusion processes

Benefit:
The proposed game theoretic decision aid tool for cooperative system modeling, simulation, and analysis has tremendous applications potential in many military applications. It can also be directly used for developing of advanced mission planning and emergency preparedness decision support systems such as Space Situational Awareness Fusion Intelligent Research Environment [SAFIRE] program, BMDS system, Future Combat System (FCS), Joint Strike Fighter (JSF) program, JSSEO program, and AEGIS program. DCM and Lockheed Martin are building a mentor-protégé program. We will leverage this relationship to identify the end customer, and work with these teams to transition our technoloy into their program. The DOD contact who knows the details of our work and who knows the above programs is Dr. Erik Blasch from AFRL. Other potential commercial applications include inter-satellite communications, multi-layered sensing, disaster assessment, air traffic control system, the national weather service, physical security systems, law enforcement agency, emergency control center, border and coast patrol, pollution monitoring, remote sensing and global awareness. We expect the aggregated market size will be similar to that of military applications.

Keywords:
Collaborative Systems, Meta-Task Decomposition And Assignment, Team Dynamics And Tactics, Multi-Agent Architecture, Data Fusion, Multi-Cumulant Pareto Nash Strategies, Hierach

In the Phase 1 study, we have successfully developed and demonstrated innovative algorithms and software tools that (1) built upon space-based target tracking software, (2) updated with game theoretic framework to automate decision aids for collaborative system understanding to enhance system effectiveness and robustness. The proposed framework has several modules for realistic space surveillance operations: Data mining, data fusion, meta-task decomposition, knowledge base extraction and population, and GMAT based simulation and visualization. With this innovative structure as well as the incorporation of game theoretic models for target maneuver detection and sensor management, the space operations center can track multiple targets and adapt to the dynamic and uncertain environment in an optimal way. In the Phase II research, we will: 1) enhance our game theoretic approach proposed in Phase I, carry out expanded evaluation with more complex scenarios, and develop a performance metrics to automatically evaluate the space situational awareness (SSA) performance of our approach; 2) Improve the function of true plug-and-play so that it can be integrated into the SAFIRE test bed which is service-oriented architecture, as well as (3) advance the game-theoretic target tracking to incorporate threats and operational needs.

Benefits:
Our first category application target will be the Space Situational Awareness Fusion Intelligent Research Environment (SAFIRE) program, Joint Space Operations Center (JSOC), and specifically the JSOC Situation Assessment Reporting System (JSARS). Beyond this first application, the proposed collaborative system modeling and analysis tool for SSA has potential in many military applications. Our industry partner, Lockheed Martin, has teamed with DCM on several Game Theory based developments because of the potential applications they see in major programs where they are the Prime Contractor.  In addition, DCM and Lockheed Martin are building a mentor-protégé program. We will leverage this relationship to identify the end customer, and work with these teams to transition our Phase 2 technology into their program. The DoD contact who knows the details of our work and who knows the above programs is Dr. Erik Blasch from AFRL. Other potential commercial applications include inter-satellite communications, multilayered sensing, disaster management, air traffic control, law enforcement, border and coast patrol, network intrusion detection, and business intelligence.  

Keywords:
Collaborative System, Dynamic Resource Allocation, Data Fusion, Space Situation Assessment; Game Theory, Target Tracking, Maneuvering Target Detection