SBIR-STTR Award

For large-scale complex systems, situation awareness calls for a holistic approach to information collection, decision making and resource management. In this project, several key technical innovations are proposed to attain predictive and responsive situation awareness. We holistically put together several critical functional blocks to cope with dynamic spatial-temporal battlefield: I) large-scale fast data acquisition using compressive and active sensing; II) cooperative in-networking processing among network nodes using distributed optimization and control; III) game-theoretic competition for combat; and, IV) unified network-centric resource management governing all of I) II) and III). These functionalities are intertwined in attaining robust situation awareness; as a result, this project will provide a unified treatment to these functional blocks through distributed network optimization and gaming. Agglomerating all these functionalities, we introduce novel information-awareness metrics to enable responsive situation awareness under mission-critical conditions.

Benefit:
The proposed awareness based space sensor resources management algorithms have tremendous potential applications in the military sector. It can be directly used for the development of advanced mission planning and emergency preparedness decision support systems such as Space Situational Awareness Fusion Intelligent Research Environment (SAFIRE) program, US Space surveillance Network and Space Command and Control programs, Predictive Awarness & Net-Centric Analysis for Colalborative Intel Assessment (PANACIA), JSARS,  Century ASW Concept of Operations (CONOPs), BMDS system, Future Combat System (FCS), Joint Strike Fighter (JSF) program, and JSSEO program. During the Phase I, we will work closely with Lockheed Martin MS2, who is a primary contractor on the Aegis weapon system, the Littoral Combat Ship, and C2 lead for the DDG-1000 program. We have developed a concrete and realistic plan to transition our technology to their programs (See support letter). 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. The market for military applications is quite large.Other potential commercial applications include medical diagnosis, quality inspection, 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:
Integrated Sensors, Situation Awareness, Information-Awareness Metric, Compressive Sensing, Active Sensing, Information Fusion, Game Theory, Gmat.

In phase 1, we have developed a holistic approach to systematically employ distributed sensor management techniques for large scale networks, with technical innovations on network utility optimization, efficient distributed computational methods, and robust and scalable information propagation. To attain predictive and responsive space situation awareness (SSA), the DCM team design, Awareness-based Compressed Data Collection and Dynamic Resource Management (ACDC-DRM), jointly addresses compressive and active sensing with network resource management in a unified manner, which represents an emerging data collection paradigm that is important, and indispensable in many cases, to the success of resource-constrained, large-scale sensor networks monitoring dynamic and/or localized phenomena. Our phase 1 work consists of: 1) compressive and active sensing algorithms for efficient data acquisition and reconstruction of a large-scale complex target-field, 2) in-network cooperative multi-sensor searching and tracking algorithm with information-based awareness metrics; and 3) game-theoretic dynamic sensor resource allocation approach for intelligent targets. In addition, a prototype based on open-source software has been implemented to illustrate the algorithms. In Phase II, we plan to coordinate with government POCs, academic researchers and industrial partners on research and development, as well as updating various open-standard database collection routines. We will also refine the key algorithms in our ACDC-DRM design, extend the system capability using theoretical performance guidelines quantified under various operating conditions, and develop an executive prototype for realistic network scenarios.

Benefit:
The first potential commercialization application is JSTAR and SAFIRE program. The second potential application is other DoD application such as ARL. The third potential application is AEGIS program and other programs where LM is the Prime Contractor. Lockheed Martin MS2 is prime contractor on the Aegis weapon system, the Littoral Combat Ship, and C2 lead for the DDG-1000 program. We have developed a strong and realistic plan to transition our technology to their programs. During the first stage of Phase II, LM MS2 will study and quantify through simulation and analysis how the ACDC-DRM can enhance the performance of their network centric platform. Assuming a successful Phase II, during the Phase III LM MS2 will build on the results of the Phase II work to implement and test the technology in real-world systems. Beyond the AEGIS first application, the innovations we are developing will improve situation awareness, planning, decision support for many military applications and we will aggressively pursue these other applications. As a metric of success, the technology is also applicable to commercial systems. Our target application will focus on disaster management, intelligent air traffic control system, and network defense.

Keywords:
C2isr; Sensor Management; Search, Tracking, And Classification; Game Theory, Compressive Sampling; Performance Metrics; Communication And Security; Soa