Optimizing the allocation of sensor assets for the unit of action
Tutton, Stephanie J.
Carlyle, W. Matthew
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The U.S. Army's Objective Force is being developed as a faster, lighter, more rapidly deployable alternative to the current force structure. The development of a strategy for the allocation of the Unit of Action's organic sensing assets is necessary to achieve the maximum situational awareness and information dominance required for successful combat operations on the future battlefield. This thesis presents a methodology for finding an appropriate mix and allocation strategy for organic Unit of Action sensors in a given scenario. Three aggregate levels are identified: sensors, platforms, and packages and performance measures are developed at each level. Two optimization models were developed, (1) a Sensor Allocation Model that, given a fixed mix or inventory, allocates assets to target areas on the battlefield, and (2) a Sensor Mix Model that suggests an organic mix of sensors for consideration in developing the Objective Force structure. These models have the additional potential for use as an operational decision support tool for unit commanders. The notional data set used for model development included ten platform types, ten target clusters, ten target categories, four enemy orders of battle, and four outcomes, however these inputs are easily modified based on the requirements of the user or analyst.
RightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
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