A Distributed Network Enabled Weapon-Target Assignment for Combat Formations

A distributed decision-making capability resulting in near-optimal weapon-target assignments for formations of unmanned combat vehicles is proposed. The decision-making is based on a modified version of the cross-entropy method distributed over the formations. For the formations to agree about a single consistent target assignment, a new consensus algorithm is proposed so that exact agreement can be reached in finite time through a communications graph that is at least weakly connected. The decision-making algorithm enables the blue-team combat vehicles to engage, or visit, all ordered sequence of targets while grouping into formations of varying dimensions oil their way to the sites. The additional degree of freedom in the formulation of the optimization problem allows mitigating the risks of destruction of the combat vehicles when facing hostile red units. The weapon-target assignment aims at maximizing a global utility function that expresses the overall weapons effects. Constraints on the autonomy of each formation is taken into account in the formulation of the optimization problem. The engagement; dynamics is represented by means of an attrition model. It is shown through numerical simulations that the proposed weapon-target assignment outperforms, in specific cases, the solution to a travel salesman problem, where all the vehicles are grouped into a, single formation. The numerical simulations also suggest that the performance of the proposed algorithm is dependent oil the number of formations per blue team, and on the number of vehicles per formation.