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Regional Missile Defense from a Global Perspective explains the origins, evolution, and implications of the regional approach to missile defense that has emerged since the presidency of George H. W. Bush, and has culminated with the missile defense decisions of President Barack Obama. The Obama administration's overarching concept for American missile defense focuses on developing both a national system of limited ground-based defenses, located in Alaska and California, intended to counter limited intercontinental threats, and regionally-based missile defenses consisting of mobile ground-based technologies like the Patriot PAC-3 system, and sea-based Aegis-equipped destroyer and cruisers. The volume is intended to stimulate renewed debates in strategic studies and public policy circles over the contribution of regional and national missile defense to global security. Written from a range of perspectives by practitioners and academics, the book provides a rich source for understanding the technologies, history, diplomacy, and strategic implications of the gradual evolution of American missile defense plans. Experts and non-experts alike—whether needing to examine the offense-defense tradeoffs anew, to engage with a policy update, or to better understand the debate as it relates to a country or region—will find this book invaluable. While it opens the door to the debates, however, it does not find or offer easy solutions—because they do not exist.

The recognition of warheads in the target cloud of the ballistic midcourse phase remains a challenging issue for missile defense systems. Considering factors such as the differing dimensions of the features between sensors and the different recognition credibility of each sensor, this paper proposes a weighted decision-level fusion architecture to take advantage of data from multiple radar sensors, and an online feature reliability evaluation method is also used to comprehensively generate sensor weight coefficients. The weighted decision-level fusion method can overcome the deficiency of a single sensor and enhance the recognition rate for warheads in the midcourse phase by considering the changes in the reliability of the sensor’s performance caused by the influence of the environment, location, and other factors during observation. Based on the simulation dataset, the experiment was carried out with multiple sensors and multiple bandwidths, and the results showed that the proposed model could work well with various classifiers involving traditional learning algorithms and ensemble learning algorithms.

Given the increasing tensions between world powers, missile defense is a topic that is more relevant than ever. However, information on the subject is often fragmented, confusing and untrustworthy. On the other hand, we believe that an informed overview of the current status is important for decision makers and citizens alike. A missile is essentially a guided rocket and therefore the term can be used to describe a very wide range of weapon systems. In this paper, we focus on long-range and intercontinental threats, which we believe are more important and problematic to defend against. We provide an overview of the two most common types of sensors, space-based infrared sensors and radars, and highlight their peculiarities and, most importantly, their drawbacks that severely limit their effectiveness.

Existing missile defense target threat assessment methods ignore the target timing and battlefield changes, leading to low assessment accuracy. In order to overcome this problem, a dynamic multi-time fusion target threat assessment method is proposed. In this method, a new interval valued intuitionistic fuzzy weighted averaging operator is proposed to effectively aggregate multi-source uncertain information; an interval-valued intuitionistic fuzzy entropy based on a cosine function (IVIFECF) is designed to determine the target attribute weight; an improved interval-valued intuitionistic fuzzy number distance measurement model is constructed to improve the discrimination of assessment results. Specifically, first of all, we define new interval-valued intuitionistic fuzzy operation rules based on algebraic operations. We use these rules to provide a new model of interval-valued intuitionistic fuzzy weighted arithmetic averaging (IVIFWAA) and geometric averaging (IVIFWGA) operators, and prove a number of algebraic properties of these operators. Then, considering the subjective and objective weights of the incoming target, a comprehensive weight model of target attributes based on IVIFECF is proposed, and the Poisson distribution method is used to solve the time series weights to process multi-time situation information. On this basis, the IVIFWAA and IVIFWGA operators are used to aggregate the decision information from multiple times and multiple decision makers. Finally, based on the improved TOPSIS method, the interval-valued intuitionistic fuzzy numbers are ordered, and the weighted multi-time fusion target threat assessment result is obtained. Simulation results of comparison show that the proposed method can effectively improve the reliability and accuracy of target threat assessment in missile defense.

It is crucial for a ballistic missile defense system to discriminate the true warhead from decoys. Although a decoy has a similar shape to the warhead, it is believed that the true warhead can be separated by its micro-Doppler features introduced by the precession and nutation. As is well known, the accuracy of the phase-derived range method, to extract micro-Doppler curves, can reach sub-wavelength. However, it suffers from an inefficiency of energy integration and high computational costs. In this paper, a novel phase-derived range method, using high-order multi-frame track-before-detect is proposed for micro-Doppler curve extraction under a low signal-to-noise ratio (SNR). First, the sinusoidal micro-Doppler range sequence is treated as the state, and the dynamic model is described as a Markov chain to obtain the envelopes and then the ambiguous phases. Instead of processing the whole frames, the proposed method only processes the latest frame at an arbitrary given time, which reduces the computational costs. Then, the correlation of all pairs of adjacent pulses is calculated along the slow time dimension to find the number of cells that the point scatterer crosses, which can be further used in phase unwrapping. Finally, the phase-derived range method is employed to get the micro-Doppler curves. Simulation results show that the proposed method is capable of extracting the micro-Doppler curves with sub-wavelength accuracy, even if SNR = −15 dB, with a lower computational cost.

This paper develops a model of short-range ballistic missile defense and uses it to study the performance of Israel's Iron Dome system. The deterministic base model allows for inaccurate missiles, unsuccessful interceptions, and civil defense. Model enhancements consider the trade-offs in attacking the interception system, the difficulties faced by militants in assembling large salvos, and the effects of imperfect missile classification by the defender. A stochastic model is also developed. Analysis shows that system performance can be highly sensitive to the missile salvo size, and that systems with higher interception rates are more \"fragile\" when overloaded. The model is calibrated using publically available data about Iron Dome's use during Operation Pillar of Defense in November 2012. If the systems performed as claimed, they saved Israel an estimated 1,778 casualties and $80 million in property damage, and thereby made preemptive strikes on Gaza about eight times less valuable to Israel. Gaza militants could have inflicted far more damage by grouping their rockets into large salvos, but this may have been difficult given Israel's suppression efforts. Counter-battery fire by the militants is unlikely to be worthwhile unless they can obtain much more accurate missiles.

Hypersonic delivery systems are a grave concern because they are potentially fast and maneuverable enough to evade existing defensive systems. As the US military considers upgrading its nuclear arsenal, hypersonic delivery systems are one possible option. Increased research on hypersonic technologies over the past two decades demonstrates there is technical feasibility for hypersonic conventional weapons. The case for nuclear-armed hypersonic weapons (NAHW) is more complicated. This article considers NAHWs from the point of view of deterrence thinking and suggests a NAHW is consistent with current US thinking about deterrence with respect to existing ballistic missiles, cruise missiles, and missile defense systems. However, we conclude that there are few advantages to hypersonic nuclear delivery systems relative to existing nuclear weapon delivery systems.

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.

The 2018 National Defense Strategy calls renewed strategic competition with major powers the central challenge of our time. The 2019 Missile Defense Review (MDR) represents the Trump administrations attempt to adapt US missile defense policy, posture, and programs to this challenge. Upon the documents public release in January 2019, President Trump stated that it marked \"a new era\" for missile defense. Unfortunately, actions within the review fall short of meeting both current and emerging threats, particularly with respect to layering and integration. Much remains to be done before that new era of missile defense can begin. By contrast, the US has for a quarter century been pushing active defenses against longer missiles apart from any explicit connection to Russia and China. Despite a few caveats in the 2010 Ballistic MDR and some programs to defend against antiship missiles, the focus across the Bush and Obama administrations was on limited ballistic missile threats from rogue states.

Charting a course through US administrations from the late 1990s to the present day, this article considers the George W. Bush administration’s thinking on nuclear deterrence in the aftermath of the terrorist attacks of 9/11: What was distinctive about the Bush administration’s thinking and approach to nuclear deterrence? To what extent, and to what effect have the Bush administration’s approaches proved enduring? The article considers the prima facie contradictory nature of the administration’s deterrence objectives against the backdrop of a shifting security environment, characterised by the proliferation of WMDs to ‘rogue states’ and non-state actors, nuclear multipolarity, disruptive emerging technologies, and long-held US commitments to its global allies and partners—ensuring the centrality of nuclear weapons in US national security policy, despite sustained efforts to reduce this reliance.