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Equipping the Marine Corps for Intelligence Fusion

Michael S. Groen

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Abstract

Abstract : The current Marine Corps approach to providing responsive fused intelligence to tactical operations can be improved through a number of changes in the systems development process and a distributed collaborative network architecture. Central to the issue is recognizing intelligence fusion as an information management problem rather than an information technology problem. Achieving knowledge dominance through intelligence fusion, instead of information superiority through more data, will require a number of changes to overcome the identified weaknesses of our current processes. An analysis of the national intelligence community, joint doctrine, and private industry reveal a tendency to provide centralized coordination and sponsorship, with decentralized execution on the battlefield to maximize responsiveness. The Marine Corps can make adjustments to both the systems development process and intelligence functional sponsorship to better fuse the products of stovepipe intelligence disciplines into a coherent and complete intelligence estimate. Among the systems development changes required are the development of an intelligence roadmap to guide budgetary priorities, the return to the functional roots of intelligence by taking the I out of C4I, and the establishment of an intelligence proponancy board. These changes will provide a unity of effort which replaces a natural focus on intelligence systems with a focus on fused intelligence products. Equipping the Marine Corps for intelligence fusion also requires a new systems architecture that is designed for distributed fusion. The current Marine Corps approach to intelligence fusion is manually intensive, rigidly controlled from the top, and segregated by individual discipline. MEF intelligence resources concentrate on their primary customer, the MEF commander. This operational level picture of the battlefield, however, may not meet the needs of dispersed tactical maneuver elements. Maximum use of automation for repet

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Abstract : The current Marine Corps approach to providing responsive fused intelligence to tactical operations can be improved through a number of changes in the systems development process and a distributed collaborative network architecture. Central to the issue is recognizing intelligence fusion as an information management problem rather than an information technology problem. Achieving knowledge dominance through intelligence fusion, instead of information superiority through more data, will require a number of changes to overcome the identified weaknesses of our current processes. An analysis of the national intelligence community, joint doctrine, and private industry reveal a tendency to provide centralized coordination and sponsorship, with decentralized execution on the battlefield to maximize responsiveness. The Marine Corps can make adjustments to both the systems development process and intelligence functional sponsorship to better fuse the products of stovepipe intelligence disciplines into a coherent and complete intelligence estimate. Among the systems development changes required are the development of an intelligence roadmap to guide budgetary priorities, the return to the functional roots of intelligence by taking the I out of C4I, and the establishment of an intelligence proponancy board. These changes will provide a unity of effort which replaces a natural focus on intelligence systems with a focus on fused intelligence products. Equipping the Marine Corps for intelligence fusion also requires a new systems architecture that is designed for distributed fusion. The current Marine Corps approach to intelligence fusion is manually intensive, rigidly controlled from the top, and segregated by individual discipline. MEF intelligence resources concentrate on their primary customer, the MEF commander. This operational level picture of the battlefield, however, may not meet the needs of dispersed tactical maneuver elements. Maximum use of automation for repet

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Available abstract

Abstract : The current Marine Corps approach to providing responsive fused intelligence to tactical operations can be improved through a number of changes in the systems development process and a distributed collaborative network architecture. Central to the issue is recognizing intelligence fusion as an information management problem rather than an information technology problem. Achieving knowledge dominance through intelligence fusion, instead of information superiority through more data, will require a number of changes to overcome the identified weaknesses of our current processes. An analysis of the national intelligence community, joint doctrine, and private industry reveal a tendency to provide centralized coordination and sponsorship, with decentralized execution on the battlefield to maximize responsiveness. The Marine Corps can make adjustments to both the systems development process and intelligence functional sponsorship to better fuse the products of stovepipe intelligence disciplines into a coherent and complete intelligence estimate. Among the systems development changes required are the development of an intelligence roadmap to guide budgetary priorities, the return to the functional roots of intelligence by taking the I out of C4I, and the establishment of an intelligence proponancy board. These changes will provide a unity of effort which replaces a natural focus on intelligence systems with a focus on fused intelligence products. Equipping the Marine Corps for intelligence fusion also requires a new systems architecture that is designed for distributed fusion. The current Marine Corps approach to intelligence fusion is manually intensive, rigidly controlled from the top, and segregated by individual discipline. MEF intelligence resources concentrate on their primary customer, the MEF commander. This operational level picture of the battlefield, however, may not meet the needs of dispersed tactical maneuver elements. Maximum use of automation for repet

Key concepts: Military intelligence, Intelligence analysis, Process (computing), Competitive intelligence, Dominance (genetics), Intelligence cycle, Computer science, Software deployment

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