Operational Planning and Optimization of Small Domain Swarm Defense Strategies is a Naval Post Graduate School Thesis by Michael J. Wish.
The focus of this thesis is on the scenario of a drone defending a high-value target from multiple attacking drones. Equipped with short-range weapons, the defending drone must efficiently destroy each of the attacking drones. This problem lies at the intersection of various open problems in applied mathematics, including optimal motion planning in the face of attrition and solving a “traveling salesman problem” (TSP) with moving targets. Our research aims to analyze this problem by breaking it down into its component problems and providing proof-of-concept solutions for each component.
The primary results of this thesis include a modeling framework that allows for optimization without requiring constraints. Additionally, we compare the effectiveness of different cost functions for optimization, such as minimizing the chance of high-value unit destruction versus a metric based on the path of the defender relative to attackers. Lastly, we solve the moving-target TSP under certain limits by mapping it onto a standard TSP or using machine learning.
Publication Date- December 2022
Operational Planning and Optimization of Small Domain Swarm Defense Strategies contains the following major sections:
- Introduction
- Unconstrained Optimization and Cost Function Analysis
- Travelling Physicist Problem
- Machine Learning Approach
- Conclusions
Approved for public release. Distribution is unlimited.
C-UAS Hub does not own this content and provides a link for users at the bottom of the page to access it in its original location. This allows the author(s) to track important article metrics related to their work. All credit goes to its rightful owner.
Author- Michael J. Wish
For additional multimedia resources, please visit the Multimedia Library.
Post Image- Army Drone On The Sky Background (Image Credit: Adobe Stock- Thecountryside)
