Contemporary counter-unmanned aircraft systems (C-UAS) defense systems have become increasingly inadequate against coordinated swarm attacks, as evidenced by recent conflicts in Ukraine, in the Middle East, and over the Red Sea. The growing disparity between low-cost threat platforms and expensive interceptors, such as the \$2 million SM-2 missiles currently being deployed against Iranian Shahed-136 drones, creates an economically unsustainable defense posture, particularly for naval assets. We propose using hierarchical interceptors, where standard low-cost rockets are repurposed to carry and release multiple smaller, autonomous, and intelligent missile interceptors to target entire swarms of threats simultaneously. To leverage the benefits of swarm behavior, such as collaborative sensing or threat corralling, the interceptor swarm warrants the development of efficient hierarchical clustering, planning, and assignment algorithms.
We present a large-scale air defense simulator platform to visualize and analyze these swarm-vs.-swarm engagements. Built in Unity, this simulator platform enables systematic comparison of different swarm algorithms by generating detailed metrics for each engagement, including outcomes from batch Monte Carlo simulations. Some key features of the simulator include the ability for threats to detect and evade oncoming interceptors and automatic reassignment of interceptors to threats that escape or are initial missed. Furthermore, the simulation is highly configurable, supporting a variety of interceptor and threat models as well as diverse engagement scenarios. Particular consideration was given to implement an autonomous, distributed, and modular air defense strategy as the simulator is intended to serve as a test bed for future swarm algorithm development.
Keywords: interceptor swarms, swarm vs. swarm, hierarchical command structure, counter-unmanned aircraft systems (C-UAS), micromissiles