This paper examines how Russia has employed its space and counterspace capabilities during the conflict in Ukraine. It begins with an assessment of the role of space in Russian military theory and doctrine, followed by a discussion of the role and functions of Russia’s Space Forces, how they are organized, and their inventory of “orbital groupings.” The paper then provides a detailed analysis of the military’s space-related capabilities and activities in Ukraine by functional area (reconnaissance, communications, navigation, and counterspace). It concludes with an assessment of Russia’s potential future courses of action in the space domain.
The space dimension is crucial in nuclear relations between the US and Russia. Space systems support vital functions like early warning, communication, reconnaissance, and targeting directly connected to strategic stability. However, shifting geopolitics and the disappearance of arms control agreements put the space dimension under strain. The Russian invasion of Ukraine showcases modern warfare's reliance on space assets. It also influences space dynamics and US-Russian relations. Although the current impact on strategic stability is limited, it is important to consider it. The most essential element of strategic stability in the space domain—the taboo against kinetic satellite attacks—endures, but there are reasons for concern. The broad use of civilian satellites for military purposes, Russia’s evolving stance regarding targeting space objects, cyber-attacks against space infrastructure, the disappearance of provisions for noninterference with space assets, and sanctions affecting space industry—all of these in their separate ways could lead to crisis and undermine strategic stability. On top of this, the lack of dedicated channels for US-Russian dialogue on space security diminishes prospects for crisis prevention or mitigation.
This paper examines the Russian military logistics system since 2010 with emphasis on its performance in Ukraine. It includes a detailed assessment of Russia’s military logistics system based on major reforms introduced in 2010, highlighted by the merger of the Technical and Logistics Services toform a unified material-technical services (MTO). Over the next decade, Russia’s logistics system underwent further reforms including changes in structure, order of battle, command and control, and transportation and storage systems, to improve performance and better align logistics with the new brigade structure introduced after the Georgia War. Next, the paper examines the performance of Russian military logistics during the 2022 Ukraine campaign. Russia’s MTO forces performed poorly during the initial invasion in part due to deficiencies in force design and doctrine and in part to the immense challenges presented by the initial invasion plan. Russian logistics fared better once the campaign refocused on the Donbas, which greatly simplified the logistics task. MTO operations had to adjust further after introduction of US HIMARS, which necessitated moving key logistics nodes further to the rear, and during mobilization, to accommodate the mass influx of new personnel. Despite many setbacks, Russian logistics has been generally successful in sustaining combat operations in Ukraine, while MTO leaders are now using lessons learned to inform future reform efforts.
Since Russia’s full-scale invasion of Ukraine, artificial intelligence has reportedly been used to analyze different types of data to enhance decision-making and inform targeting, to process enemy communications, in facial recognition technology, and in cyber defense, to name a few. Drawing on open-source information and scholarly research, this report, authored by Margarita Konaev of Georgetown’s Center for Security and Emerging Technology, surveys the use of AI in the war in Ukraine and assesses the potential implications of these systems and capabilities for conflict escalation and strategic stability. Although AI has played an important role in enhancing battlefield information processing, it is difficult to estimate whether these technologies are being used at scale and to what effect. Although in its current form, the use of AI has had a limited effect on the risk of escalation, this may change with more extensive deployment, especially of untested systems, which highlights the value of confidence building measures to minimize the risk of inadvertent escalation.
In this CNA Occasional Paper, Anatoly Zak, a noted expert on the Russian space program, examines Russia’s military and dual-purpose spacecraft. He discusses the resurgence of the Russian space program in the past two decades, both the military and civilian components. The paper identifies different satellite classes operated by both the country’s military and the civilian space agency, providing a detailed overview of radar imagery and early warning technologies in service today. Zak provides a detailed description of antisatellite capabilities in Russian service, and goes over some of the significant detriments to further progress, such as corruption and quality control issue in the Russian space service. He argues that the “growing pains” of the Russian space industry in the post-Soviet period could eventually be resolved or at least mitigated, allowing more effective use of available resources, cutting the development time, and producing more reliable systems in the future.
The US,and Russia have all recognized the revolutionary promise of artificial intelligence (AI). It is likely, as each seeks areas of advantage through AI, that they will explore nuclear applications of AI. Consequently, the US State Department’s Bureau of Arms Control, Verification, and Compliance (AVC) asked CNA to conduct research and analysis that would sharpen its understanding of how AI could affect nuclear risks and how AVC could reduce those risks and capture security-enhancing benefits. This report characterizes how all three competitors are using AI in nuclear operations; how they might do so in the future; and how their uses of AI could increase, decrease, or otherwise affect nuclear risks. It also recommends ways the US government might mitigate the risks of AI-enabled nuclear operations and capturing possible risk-reducing benefits.
