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The relevant literature on missile defense is limited in that it primarily consists of policy-oriented prescriptive studies that support or oppose the deployment of missile defense in a host country. To address this deficiency, the current research compares two controversial cases of US missile defense deployment in Poland and the Republic of Korea. A theoretical framework is developed based on the alliance security dilemma to explain why certain allies accept US missile defense. The framework is used to evaluate two key aspects of missile defense deployment: whether a missile defense target is a shared adversary and the degree of reliance on the alliance. These variables are utilized as measures of entrapment and abandonment fears to explain why allies accept US missile defense systems. [ABSTRACT FROM AUTHOR]

Recent advances in radar seeker technologies have considerably improved missile precision and efficacy during target interception. This is especially concerning in the arenas of protection and safety, where appropriate countermeasures against enemy missiles are required to ensure the protection of naval facilities. In this study, we present a reinforcement-learning-based strategy for deploying decoys to enhance the survival probability of a target ship against a missile threat. Our approach involves the coordinated operation of three decoys, trained using the Multi-Agent Deep Deterministic Policy Gradient (MADDPG) and Multi-Agent Twin Delayed Deep Deterministic Policy Gradient (MATD3) algorithms. The decoys operate in a leader–follower dynamic with a circular formation to ensure effective coordination. We evaluate the strategy across various parameters, including decoy deployment regions, missile launch directions, maximum decoy speeds, and missile speeds. The results indicate that, decoys trained with the MATD3 algorithm demonstrate superior performance compared to those trained with the MADDPG algorithm. Insights suggest that our decoy deployment strategy, particularly when utilizing MATD3-trained decoys, significantly enhances defensive measures against missile threats. [ABSTRACT FROM AUTHOR]

The decision by South Korean authorities to deploy a Terminal High Altitude Area Defense (THAAD) missile battery in 2016 unleashed a storm of protest, both domestically and internationally. Attempts to resolve these debates by showing the 'truth' of the THAAD system obscure the considerable investment of time and resources needed to stabilize technological meanings in the face of rival interpretations. This article synthesizes work in the field of Science and Technology Studies (STS) to present an integrated model of technopolitics explaining how doing politics through 'things' consists of interlinked rhetorical, performative, and material stabilization techniques each seeking to make the object simple, nonpolitical, and ultimately invisible or banal. In the case of THAAD, the single battery deployed to South Korea was the tip of a broader US technopolitical project to materially bind together its regional allies and contain North Korea and China. However, opponents inside and outside of the Korean peninsula tried to destabilize this project by employing their own rhetorical, performative, and de-materialization strategies. This resulted in a partial victory for both sides insofar as the broader US missile defense technopolitical project on the peninsula was paused but not defeated. [ABSTRACT FROM AUTHOR]

This paper investigates interception missiles’ trajectory tracking guidance problem under wind field and external disturbances in the boost phase. Indeed, the velocity control in such trajectory tracking guidance systems of missiles is challenging. As our contribution, the velocity control channel is designed to deal with the intractable velocity problem and improve tracking accuracy. The global prescribed performance function, which guarantees the tracking error within the set range and the global convergence of the tracking guidance system, is first proposed based on the traditional PPF. Then, a tracking guidance strategy is derived using the integral sliding mode control techniques to make the sliding manifold and tracking errors converge to zero and avoid singularities. Meanwhile, an improved switching control law is introduced into the designed tracking guidance algorithm to deal with the chattering problem. A back propagation neural network (BPNN) extended state observer (BPNNESO) is employed in the inner loop to identify disturbances. The obtained results indicate that the proposed tracking guidance approach achieves the trajectory tracking guidance objective without and with disturbances and outperforms the existing tracking guidance schemes with the lowest tracking errors, convergence times, and overshoots.

Recent advances in radar seeker technologies have considerably improved missile precision and efficacy during target interception. This is especially concerning in the arenas of protection and safety, where appropriate countermeasures against enemy missiles are required to ensure the protection of naval facilities. In this study, we present a reinforcement-learning-based strategy for deploying decoys to enhance the survival probability of a target ship against a missile threat. Our approach involves the coordinated operation of three decoys, trained using the Multi-Agent Deep Deterministic Policy Gradient (MADDPG) and Multi-Agent Twin Delayed Deep Deterministic Policy Gradient (MATD3) algorithms. The decoys operate in a leader–follower dynamic with a circular formation to ensure effective coordination. We evaluate the strategy across various parameters, including decoy deployment regions, missile launch directions, maximum decoy speeds, and missile speeds. The results indicate that, decoys trained with the MATD3 algorithm demonstrate superior performance compared to those trained with the MADDPG algorithm. Insights suggest that our decoy deployment strategy, particularly when utilizing MATD3-trained decoys, significantly enhances defensive measures against missile threats.

During the Cold War, the Soviet Union invested heavily in its air defense systems, so its rightful successor, Russia, has now some of the most advanced air and missile defense systems in the world. Among them, the S-400 “Triumf” surface-to-air missile system is perhaps the most criticized, shrouded in mystery, and feared system in Russia’s arsenal. Developed and then presented as capable of engaging a variety of aerial threats, the system gained a reputation, at least declaratively, of being able to counter US and NATO ambitions to win a conflict through airspace dominance.

• This paper explores a three-dimensional tracking guidance strategy against high-maneuvering hypersonic vehicles. • The proposed guidance method utilizes a velocity control channel to increase tracking precision. • The wind field is accurately modeled to simulate the actual environment in the near-space to prevent impractical scenarios. • The backpropagation neural network extended state observer is proposed to estimate the uncertainty disturbance and design an adaptive control law to compensate for the tracking errors. • The proposed strategy combines fast nonsingular terminal sliding mode control and adaptive techniques to improve non-singularity, tracking accuracy, and estimation precision. This paper presents a three-dimensional disturbance observer-based adaptive tracking guidance scheme for the trajectory tracking problem of a missile intercepting a hypersonic vehicle with the wind field, autopilot lag dynamics, and input saturation. Unlike most of the existing missile trajectory tracking guidance systems without velocity controllability and external wind field model, the wind field model is added to the dynamic model, and the velocity control channel is introduced into the three-dimensional trajectory tracking guidance problem to prevent impractical scenarios and increase tracking precision. The proposed tracking guidance methodology incorporates the sliding mode and adaptive control techniques, in which the sliding mode motion is finite time stable independently of the tracking guidance system's initial conditions. Also, the super twisting switch control law is added to cope with the chattering problem. In this context, external uncertainty disturbances and unmeasured states are lumped into lump disturbance and estimated using the backpropagation neural network extended state observer. To this end, numerical simulations demonstrate the tracking to reach zero between 3 s and 5 s against various uncertainties in engineering practical, and position tracking errors are within 0.15 m, superior to the existing tracking guidance methods. [ABSTRACT FROM AUTHOR]