BPN990: Anti-Drone Radar-Guided Micromissiles

Abstract: 

Since drones can be flown remotely or autonomously and can navigate dangerous environments without any risk to human operators, they are attractive for military applications, including surveillance, reconnaissance, and combat missions. At the same time, enemy drones pose a growing serious threat to civilians and soldiers. Current anti-drone warfare is either inaccurate, expensive, or large in size, so this project aims to build a low-cost, crayon-sized radar-guided microrocket to target drones up to 100 meters away.

To effectively and tractably counter hundreds of threats, we propose a hierarchical interceptor strategy, where larger carrier interceptors release multiple smaller, autonomous, and intelligent missile interceptors as they approach a swarm of threats. To visualize these swarm-on-swarm engagements and evaluate the performance of different interceptor swarm algorithms, we are developing a configurable large-scale air defense simulation platform (https://github.com/PisterLab/micromissiles-unity). The simulator supports a variety of interceptor and threat models as well as engagement scenarios and is intended as a test bed for future swarm algorithm development.

Project currently funded by: Membership Fees

Author: 
Cedric Murphy
Jenna Dickman
Asa Garner
Eric Yang
Publication date: 
August 14, 2025
Publication type: 
BSAC Project Materials (Current)
Citation: 
PREPUBLICATION DATA - ©University of California 2025

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