A dual neural network ‘adaptive critic approach’ is used in this study to generate midcourse guidance commands for a missile to reach a predicted impact point while maximizing its final velocity. The adaptive critic approach is based on approximate dynamic programming. The first network, called a ‘critic’, network, outputs the Lagrangian multipliers arising in an optimal control formulation whi...

Executive Summary The ability to differentiate adequately between true targets and false ones (discrimination) in the midcourse phase of attacking missiles 1 flight is a key requirement for a successful ballistic missile defense. This ability is of particular importance for the proposed initial configuration of the Strategic Defense System (SDS phase 1) because (1) the preponderance of the reen...

A midcourse maneuver controller is obtained using deep reinforcement learning to maintain the survivability of a ballistic missile. First, abstracted as Markov decision process (MDP) with an unknown system state equation. Then, formed by Dueling Double Deep Q (D3Q) neural network used approximate state-action value function MDP. In order make controller’s intelligence improved learning, space, ...

By appropriately modifying the generalized explicit guidance and developing it further, an optimal midcourse guidance law is proposed in this paper to ensure terminal impact angle constrained engagement of missiles with near-zero lateral acceleration in the terminal phase. This guidance law generates a desired intermediate point in space as well as the desired angles which needs to be achieved ...

Our understanding of infectious diseases follows a natural course—the initial discovery of the cause, the exploration of the natural history and biology of the etiologic agent, and finally the cure or solution. The discovery of Sin Nombre virus (SNV), one of the viruses causing hantavirus pulmonary syndrome (HPS), is unparalleled in terms of the rapid progress of the scientific investigation le...

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